Telecommunications is increasingly vital to the society at large, and has become essential to
business, academic, as well as social activities. Due to the necessity to have access to
telecommunications, the deployment requires regulations and policy. Otherwise, the deployment
of the infrastructures would contribute to environment, and human complexities rather than
ease of use.
However, the formulation of telecommunication infrastructure deployment regulation and
policy involve agents such as people and processes. The roles of the agents are critical, and are
not as easy as it meant to belief. This could be attributed to different factors, as they produce
and reproduce themselves overtime.
This paper presents the result of a study which focused on the roles of agents in the formulation
of telecommunication infrastructures deployment regulation and policy. In the study, the
interactions that take place amongst human and non-human agents were investigated. The study
employed the duality of structure, of Structuration theory as lens to understand the effectiveness
of interactions in the formulation of regulations, and how policy is used to facilitate the
deployment of telecommunications infrastructure in the South African environment.
Energy Efficient Stable Election Protocol for Clustered Heterogeneous Wireles...IOSR Journals
This document summarizes an energy efficient stable election protocol (EE-SEP) for clustered heterogeneous wireless sensor networks. EE-SEP modifies the existing SEP protocol to improve energy efficiency, stability period, and network lifetime. It does this by calculating the optimal threshold value for selecting cluster heads based on the initial energy of sensor nodes, rather than the weighted election probability used in SEP. Simulations show EE-SEP performs better than SEP by increasing the number of alive nodes over time, reducing energy consumption, and prolonging network lifetime.
ENERGY EFFICIENT AGGREGATION WITH DIVERGENT SINK PLACEMENT FOR WIRELESS SENSO...ijasuc
In WSN the data aggregation is a means for condensing the energy requirement by reducing number of
transmission by combining the data and sending the final required result to the base station. The lifetime
of the WSN can be improved by employing the aggregation techniques. During the process of aggregation
the numbers of transmission are reduced by combining the similar data from the nearby areas. By using
the clustering technique and aggregating the correlated data greatly minimize the energy consumed in
collecting and disseminating the data. In this work, we evaluate the performance of a novel energy
efficient cluster based aggregation protocol (EECAP) for WSN. The main focus in this proposed work is
to study the performance of our proposed aggregation protocol with divergent sink placements such as
when sink is at the centre of the sensing field, corner of the sensing field or at a location selected
randomly in the sensor field. We present experimental results by calculating the lifetime of network in
terms of number of sensing rounds using various parameters such as – average remaining energy of
nodes, number of dead nodes after the specified number of sensing rounds. Finally the performance of
various aggregation algorithms such as LEACH, SEP and our proposed aggregation protocol (EECAP)
are compared with divergent sink placements. The simulation results demonstrates that EECAP exhibits
good performance in terms of lifetime and the energy consumption of the wireless sensor networks and
which can be as equally compared with existing clustering protocols.
Implementing Energy Efficient Strategies in the MANET on-demand routing Proto...IJEEE
Mobile Ad-hoc networks are self-configuring multi-hop wireless networks where, the structure of the network changes dynamically. Because of the nodes in the MANET are mobile and battery operated, energy optimization is one of the major constraints in the MANET. Failure of some nodes operation can greatly impede the performance of the network and even affect the basic availability of the network, i.e., routing. To improve the lifetime of these networks can be improving the energy levels of the individual nodes of the network. This paper presents an analysis of the effects of different design choices for this on- demand routing protocols DSR and AODV in wireless ad hoc networks. In this paper, the energy efficient strategies are implemented in the AODV and DSR protocols to improve the life time of the Mobile ad hoc network. The CBEER-NN is developed using the existing DSR protocol and the AO- EEDTR is developed using the existing AODV protocol. GloMoSIM simulator is used to simulate the proposed MANET environment. This paper also compares the existing DSR and AODV protocols with proposed CBEER- NN and AO-EEDTR protocols. From the simulated results, this paper concludes that the proposed CBEER-NN and AO- EEDTR protocols are improving the life time of the network by improving the average residual energy of the nodes over the existing DSR and AO-EEDTR protocols.
Advance in the WIRELESS SENSOR NETWORK (WISENET) technology is energy efficient routing protocols that promises a wide range of potential applications in both civilian and military areas. In the WISNET the sensor node have a limited transmission range and their processing and storage capabilities as well as their energy sources are limited. So the Equalized Cluster Head Election Routing Protocol (ECHERP) and PEGASIS with Double Cluster Head (PDCH) pursues energy conservation through balanced clustering for Energy Efficiency. In WSN, energy efficient routing protocol is important to increase the network lifetime. ECHERP and PDCH both protocol claims to be energy efficient.
Trilateration-based localization (TBL) has become a corner stone of modern technology. This study
formulates the concern on how wireless sensor networks can take advantage of the computational
intelligent techniques using both single- and multi-objective particle swarm optimization (PSO) with an
overall aim of concurrently minimizing the required time for localization, minimizing energy consumed
during localization, and maximizing the number of nodes fully localized through the adjustment of wireless
sensor transmission ranges while using TBL process. A parameter-study of the applied PSO variants is
performed, leading to results that show algorithmic improvements of up to 32% in the evaluated objectives.
Energy efficient clustering in heterogeneousIJCNCJournal
Cluster head election is a key technique used to reduce energy consumption and enhancing the throughput
of wireless sensor networks. In this paper, a new energy efficient clustering (E2C) protocol for
heterogeneous wireless sensor networks is proposed. Cluster head is elected based on the predicted
residual energy of sensors, optimal probability of a sensor to become a cluster head, and its degree of
connectivity as the parameters. The probability threshold to compete for the role of cluster head is derived.
The probability threshold has been extended for multi-levels energy heterogeneity in the network. The
proposed E2C protocol is simulated in MATLAB. Results obtained in the simulationshowthat performance
of the proposed E2Cprotocol is betterthan stable election protocol (SEP), and distributed energy efficient
clustering (DEEC) protocol in terms of energy consumption, throughput, and network lifetime.
This document summarizes a research paper that proposes an enhanced cross-layer protocol (ECLP) for wireless sensor networks. ECLP integrates medium access control and routing to improve energy efficiency and reduce latency. It uses an adaptive duty cycling scheme with adaptive timeouts and reservation requests. It also designs a tree-based energy-aware routing algorithm to prolong the network lifetime while minimizing control overhead for data delivery. Simulation results show ECLP outperforms other existing algorithms in terms of energy efficiency and latency.
Chain Based Wireless Sensor Network Routing Using Hybrid Optimization (HBO An...IJEEE
In Wireless Sensor Network, due to the
energy restriction of each nodes, efficient routing is very
important in order to save the energy of the hybrid
optimization technique. The results of new protocol i.e.
hybrid have been compared with EEPB and IEEPB.
Simulation results show that the lifetime of Hybrid is better
as compared to EEPB and IEEPB.
Energy Efficient Stable Election Protocol for Clustered Heterogeneous Wireles...IOSR Journals
This document summarizes an energy efficient stable election protocol (EE-SEP) for clustered heterogeneous wireless sensor networks. EE-SEP modifies the existing SEP protocol to improve energy efficiency, stability period, and network lifetime. It does this by calculating the optimal threshold value for selecting cluster heads based on the initial energy of sensor nodes, rather than the weighted election probability used in SEP. Simulations show EE-SEP performs better than SEP by increasing the number of alive nodes over time, reducing energy consumption, and prolonging network lifetime.
ENERGY EFFICIENT AGGREGATION WITH DIVERGENT SINK PLACEMENT FOR WIRELESS SENSO...ijasuc
In WSN the data aggregation is a means for condensing the energy requirement by reducing number of
transmission by combining the data and sending the final required result to the base station. The lifetime
of the WSN can be improved by employing the aggregation techniques. During the process of aggregation
the numbers of transmission are reduced by combining the similar data from the nearby areas. By using
the clustering technique and aggregating the correlated data greatly minimize the energy consumed in
collecting and disseminating the data. In this work, we evaluate the performance of a novel energy
efficient cluster based aggregation protocol (EECAP) for WSN. The main focus in this proposed work is
to study the performance of our proposed aggregation protocol with divergent sink placements such as
when sink is at the centre of the sensing field, corner of the sensing field or at a location selected
randomly in the sensor field. We present experimental results by calculating the lifetime of network in
terms of number of sensing rounds using various parameters such as – average remaining energy of
nodes, number of dead nodes after the specified number of sensing rounds. Finally the performance of
various aggregation algorithms such as LEACH, SEP and our proposed aggregation protocol (EECAP)
are compared with divergent sink placements. The simulation results demonstrates that EECAP exhibits
good performance in terms of lifetime and the energy consumption of the wireless sensor networks and
which can be as equally compared with existing clustering protocols.
Implementing Energy Efficient Strategies in the MANET on-demand routing Proto...IJEEE
Mobile Ad-hoc networks are self-configuring multi-hop wireless networks where, the structure of the network changes dynamically. Because of the nodes in the MANET are mobile and battery operated, energy optimization is one of the major constraints in the MANET. Failure of some nodes operation can greatly impede the performance of the network and even affect the basic availability of the network, i.e., routing. To improve the lifetime of these networks can be improving the energy levels of the individual nodes of the network. This paper presents an analysis of the effects of different design choices for this on- demand routing protocols DSR and AODV in wireless ad hoc networks. In this paper, the energy efficient strategies are implemented in the AODV and DSR protocols to improve the life time of the Mobile ad hoc network. The CBEER-NN is developed using the existing DSR protocol and the AO- EEDTR is developed using the existing AODV protocol. GloMoSIM simulator is used to simulate the proposed MANET environment. This paper also compares the existing DSR and AODV protocols with proposed CBEER- NN and AO-EEDTR protocols. From the simulated results, this paper concludes that the proposed CBEER-NN and AO- EEDTR protocols are improving the life time of the network by improving the average residual energy of the nodes over the existing DSR and AO-EEDTR protocols.
Advance in the WIRELESS SENSOR NETWORK (WISENET) technology is energy efficient routing protocols that promises a wide range of potential applications in both civilian and military areas. In the WISNET the sensor node have a limited transmission range and their processing and storage capabilities as well as their energy sources are limited. So the Equalized Cluster Head Election Routing Protocol (ECHERP) and PEGASIS with Double Cluster Head (PDCH) pursues energy conservation through balanced clustering for Energy Efficiency. In WSN, energy efficient routing protocol is important to increase the network lifetime. ECHERP and PDCH both protocol claims to be energy efficient.
Trilateration-based localization (TBL) has become a corner stone of modern technology. This study
formulates the concern on how wireless sensor networks can take advantage of the computational
intelligent techniques using both single- and multi-objective particle swarm optimization (PSO) with an
overall aim of concurrently minimizing the required time for localization, minimizing energy consumed
during localization, and maximizing the number of nodes fully localized through the adjustment of wireless
sensor transmission ranges while using TBL process. A parameter-study of the applied PSO variants is
performed, leading to results that show algorithmic improvements of up to 32% in the evaluated objectives.
Energy efficient clustering in heterogeneousIJCNCJournal
Cluster head election is a key technique used to reduce energy consumption and enhancing the throughput
of wireless sensor networks. In this paper, a new energy efficient clustering (E2C) protocol for
heterogeneous wireless sensor networks is proposed. Cluster head is elected based on the predicted
residual energy of sensors, optimal probability of a sensor to become a cluster head, and its degree of
connectivity as the parameters. The probability threshold to compete for the role of cluster head is derived.
The probability threshold has been extended for multi-levels energy heterogeneity in the network. The
proposed E2C protocol is simulated in MATLAB. Results obtained in the simulationshowthat performance
of the proposed E2Cprotocol is betterthan stable election protocol (SEP), and distributed energy efficient
clustering (DEEC) protocol in terms of energy consumption, throughput, and network lifetime.
This document summarizes a research paper that proposes an enhanced cross-layer protocol (ECLP) for wireless sensor networks. ECLP integrates medium access control and routing to improve energy efficiency and reduce latency. It uses an adaptive duty cycling scheme with adaptive timeouts and reservation requests. It also designs a tree-based energy-aware routing algorithm to prolong the network lifetime while minimizing control overhead for data delivery. Simulation results show ECLP outperforms other existing algorithms in terms of energy efficiency and latency.
Chain Based Wireless Sensor Network Routing Using Hybrid Optimization (HBO An...IJEEE
In Wireless Sensor Network, due to the
energy restriction of each nodes, efficient routing is very
important in order to save the energy of the hybrid
optimization technique. The results of new protocol i.e.
hybrid have been compared with EEPB and IEEPB.
Simulation results show that the lifetime of Hybrid is better
as compared to EEPB and IEEPB.
Energy Performance of LDPC Scheme in Multi-Hop Wireless Sensor Network with T...IJECEIAES
Conservation of the energy is one of the main design issues in wireless sensor networks. The limited battery power of each sensor node is a challenging task in deploying this type of network. The challenge is crucial in reliable wireless network when implementing efficient error correcting scheme with energy consuming routing protocol. In this work, we investigated the energy performance of LDPC code in multi-hop wireless sensor network. We proposed a model of two base stations to prolong the lifetime and build a reliable and energy-efficient network. Through performed MATLAB simulations, we examine the energy effectiveness of multiple base stations model on reliable wireless sensor network performance in different network dimensions.
An Improved Energy Efficient Wireless Sensor Networks Through Clustering In C...Editor IJCATR
One of the major reason for performance degradation in Wireless sensor network is the overhead due to control packet and packet delivery degradation. Clustering in cross layer network operation is an efficient way manage control packet overhead and which ultimately improve the lifetime of a network. All these overheads are crucial in a scalable networks. But the clustering always suffer from the cluster head failure which need to be solved effectively in a large network. As the focus is to improve the average lifetime of sensor network the cluster head is selected based on the battery life of nodes. The cross-layer operation model optimize the overheads in multiple layer and ultimately the use of clustering will reduce the major overheads identified and their by the energy consumption and throughput of wireless sensor network is improved. The proposed model operates on two layers of network ie., Network Layer and Transport Layer and Clustering is applied in the network layer . The simulation result shows that the integration of two layers reduces the energy consumption and increases the throughput of the wireless sensor networks.
Enhancing Survivability, Lifetime, and Energy Efficiency of Wireless NetworksIJRES Journal
In this paper, we focus on improving wireless networks survivability in terms of increasing network lifetime and its energy efficiency via clustering the network in an efficient way. Clustering the network is the procedure of partitioning it into groups, where each of them is known as a cluster. Each cluster elects the station with the highest power to be a cluster head. The remaining stations follow the nearest cluster head. Instead of having each station sends its packets to a remote receiver, the cluster head receives packets from all stations within its cluster, aggregates them, and forwards the resulting packets to the remote receiver. The most significant benefit of clustering the network that we focus on is to decrease distances between sending and receiving stations, which in turn reduces the transmission energy. This reduction in the energy yields an increase in the network lifetime and its survivability.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Mobile Ad-Hoc Network (MANET) is a self-configuring network of mobile devices connected through wireless. Nowadays mobile devices in mobile Ad-hoc network are battery operated. Battery is an important factor in MANET. Dynamic topology of mobile ad-hoc network and limited battery capacity are constrained on network life time. In this paper, we have presented variants of power aware techniques in an on-demand reactive routing protocol i.e. AODV which aims to prolong network lifetime. AODV is reactive protocol and it establish route on demand.
Ad hoc networks are self-configuring networks and each node executes routing functionalities by itself;
they are powered by battery, which is prone to decrease with time. In this paper, a power aware routing
algorithm called Dynamic path switching is proposed which attempt to extend the lifetime of network in
MANET. It creates a new path based on the energy level of the nodes. Along with DPS the Transmission
power control technique is incorporated which varies the transmission power based on the distance. It
reduces power consumption further. The proposed techniques are incorporated in Zone Routing Protocol
(ZRP) and simulated by using NS-2 simulator to obtain the QOS parameters.
An Adaptive Energy Aware Clustering Based Reliable Routing for in-Network Agg...Editor IJCATR
Wireless Sensor Network (WSN) consists of spatially distributed autonomous devices that cooperatively sense physical or
environmental conditions. Due to the non-uniform node deployment, the energy consumption among nodes are more
imbalanced in cluster-based wireless sensor networks this factor will affect the network life time. Cluster-based routing and EADC
algorithm through an efficient energy aware clustering algorithm is employed to avoid imbalance network distribution. Our proposed
protocol EADC aims at minimizing the overall network overhead and energy expenditure associated with the multi hop data retrieval
process while also ensuring balanced energy consumption among SNs and prolonged network life time .A optimal one-hop based
selective node in building cluster structures consisted of member nodes that route their measured data to their assigned cluster head is
identified to ensure efficient communication. The proposed routing algorithm increases forwarding tasks of the nodes in scarcely
covered areas by forcing cluster heads to choose nodes with higher energy and fewer member nodes and finally, achieves
imbalanced among cluster head and improve the network life time.
Coverage and Connectivity Aware Neural Network Based Energy Efficient Routing...graphhoc
There are many challenges when designing and deploying wireless sensor networks (WSNs). One of the key challenges is how to make full use of the limited energy to prolong the lifetime of the network, because energy is a valuable resource in WSNs. The status of energy consumption should be continuously monitored after network deployment. In this paper, we propose coverage and connectivity aware neural network based energy efficient routing in WSN with the objective of maximizing the network lifetime. In the proposed scheme, the problem is formulated as linear programming (LP) with coverage and connectivity aware constraints. Cluster head selection is proposed using adaptive learning in neural networks followed by coverage and connectivity aware routing with data transmission. The proposed scheme is compared with existing schemes with respect to the parameters such as number of alive nodes, packet delivery fraction, and node residual energy. The simulation results show that the proposed scheme can be used in wide area of applications in WSNs.
34 9141 it ns2-tentative route selection approach for edit septianIAESIJEECS
Wireless Sensor Networks (WSNs) assume a crucial part in the field of mechanization and control where detecting of data is the initial step before any automated job could be performed. So as to encourage such perpetual assignments with less vitality utilization proportion, clustering is consolidated everywhere to upgrade the system lifetime. Unequal Cluster-based Routing (UCR) [7] is a standout amongst the most productive answers for draw out the system lifetime and to take care of the hotspot issue that is generally found in equivalent clustering method. In this paper, we propose Tentative Route (TRS) Selection approach for irregular Clustered Wireless Sensor Networks that facilitates in decision an efficient next relay to send the data cumulative by Cluster Heads to the Base Station. Simulation analysis is achieved using the network simulator to demonstrate the effectiveness of the TRS method.
ENERGY EFFICIENT ROUTING ALGORITHM FOR MAXIMIZING THE MINIMUM LIFETIME OF WIR...ijasuc
In wireless sensor network, devices or nodes are generally battery powered devices. These nodes have
limited amount of initial energy that are consumed at different rates, depending on the power level. The
lifetime of the network is defined as the time until the first node fails (or runs out of battery). In this paper
different type of energy efficient routing algorithms are discussed and approach of these algorithms is to
maximize the minimum lifetime of wireless sensor network. Special attention has been devoted for
algorithms formulate the routing problem as a linear programming problem, which uses the optimal flow
path for data transmission and gives the optimum results. Advantages, limitations as well as comparative
study of these algorithms are also discussed in this paper.
Design and Performance Analysis of Energy Aware Routing Protocol for Delay Se...ijcncs
This document presents a study on an energy aware routing protocol called Energy Aware DSR (EADSR) for wireless sensor networks. EADSR is an extension of the Dynamic Source Routing (DSR) protocol that adds energy awareness to improve network lifetime. The study compares the performance of DSR and EADSR through simulations. Results show that EADSR outperforms DSR in terms of energy savings and avoids early network partitioning caused by nodes draining their energy quickly. EADSR selects routes based on the total energy of nodes along the path and notifies neighbors when a node's energy is low to find alternative routes before it fails.
Gateway based multi hop distributed energy efficient clustering protocol for ...ijujournal
Wireless sensor network consists of application oriented and cheap micro-devices called sensors nodes having potential of connecting the physical world with virtual world by their sensing abilities. These sensor nodes are having restrained battery sources. Efficient energy management is current area of research in wireless sensor networks. Here we advice one such energy aware multi-hop protocol (G-DEEC) for two
level heterogeneous networks. In G-DEEC, the Base Station is placed out of sensing area and rechargeable
gateway nodes are placed inside field with other randomly deployed sensor nodes. Simulation shows the proposed protocol G-DEEC is better than single-hop DEEC in terms of number of half dead nodes, alive nodes and dead nodes; thereby showing improvement in network lifetime and stability.
Optimized Cluster Establishment and Cluster-Head Selection Approach in WSNIJCNCJournal
In recent years, limited resources of user products and energy-saving are recognized as the major challenges of Wireless Sensor Networks (WSNs). Clustering is a practical technique that can reduce all energy consumption and provide stability of workload that causes a larger difference in energy depletion among other nodes and cluster heads (CHs). In addition, clustering is the solution of energy-efficient for maximizing the network longevity and improvising energy efficiency. In this paper, a novel OCE-CHS (Optimized Cluster Establishment and Cluster-Head Selection) approach for sensor nodes is represented to improvise the packet success ratio and reduce the average energy-dissipation. The main contribution of this paper is categorized into two processes, first, the clustering algorithm is improvised that periodically chooses the optimal set of the CHs according to the speed of the average node and average-node energy. This is considerably distinguished from node-based clustering that utilizes a distributed clustering algorithm to choose CHs based on the speed of the current node and remaining node energy. Second, more than one factor is assumed for the detached node to join the optimal cluster. In the result section, we discuss our clustering protocols implementation of optimal CH-selection to evade the death of SNs, maximizing throughput, and further improvise the network lifetime by minimizing energy consumption.
Opportunistic routing algorithm for relay nodejpstudcorner
The document proposes an energy-efficient opportunistic routing algorithm called ENS_OR for wireless sensor networks. ENS_OR selects relay nodes based on an "energy equivalent node" concept from opportunistic routing theory to minimize energy consumption and maximize network lifetime. It prioritizes nodes as forwarders according to their transmission distance from equivalent nodes and remaining energy levels. Simulations and testbed results show ENS_OR significantly improves energy savings and connectivity over existing routing schemes.
In wireless sensor network energy cutback is considered as a principle intensive challenge which is studied largely in the Wireless Sensor Networks (WSN) literature. Wireless Sensor Networks (WSNs) are pertinent in numerous arenas where WSNs may be used for sensing, ciphering, and communication elements that give a user or administrator the ability to instrument, observe, and retort to events and phenomena in a specific environment. But sensor devices are resource curbed, positioned in an open and unattended environment, different types of attacks and conventional techniques against these attacks are not desirable due to the resource constrained nature of these kinds of networks. An energy-balanced routing method based on forward-aware factor (FAF-EBRM) in which the next-hop node is elected according to the awareness of link weight and forward energy density. FAF-EBRM is compared with Ladder Diffusion Algorithm, which balances the energy utilization, sustain the function era and guarantees high QoS of WSN. The FAF-EBRM is proposed with Secure Routing Layer (SRL) Protocol which ensures that the secure data transmission is achieved without releasing private sensor readings and without introducing significant overhead on the battery-limited sensors.
WEIGHTED DYNAMIC DISTRIBUTED CLUSTERING PROTOCOL FOR HETEROGENEOUS WIRELESS S...ijwmn
This document describes a new clustering protocol called WDDC (Weighted Dynamic Distributed Clustering) for heterogeneous wireless sensor networks. WDDC selects cluster heads based on the ratio of a node's residual energy to the average network energy, and also considers the distance between nodes and the base station. WDDC divides the network lifetime into two zones and changes its behavior dynamically between the zones. Simulation results show WDDC outperforms other clustering protocols like SEP and DEEC in terms of energy efficiency and extending network lifetime.
A Proactive Greedy Routing Protocol Precludes Sink-Hole Formation in Wireless...ijwmn
The International Journal of Wireless & Mobile Networks (IJWMN) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Wireless & Mobile Networks. The journal focuses on all technical and practical aspects of Wireless & Mobile Networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced wireless & mobile networking concepts and establishing new collaborations in these areas.
A gateway based energy efficient multi hop routing protocol for wireless sensor networks (WSNs) is
introduced. The main aim of our paper is to design a protocol which minimizes energy consumption.
Gateway nodes are deployed in sensing field.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
This document discusses finding an optimum transmission range in a wireless sensor network to balance delay and energy consumption. It analyzes how transmission range, node deployment, number of hops, and forwarding techniques affect energy usage. The researchers deployed sensor nodes in a grid and evaluated greedy forwarding and residual energy forwarding under varying transmission ranges. They found that an optimal range exists that uses less energy per transmission while minimizing the number of hops needed to reach destinations.
Energy Performance of LDPC Scheme in Multi-Hop Wireless Sensor Network with T...IJECEIAES
Conservation of the energy is one of the main design issues in wireless sensor networks. The limited battery power of each sensor node is a challenging task in deploying this type of network. The challenge is crucial in reliable wireless network when implementing efficient error correcting scheme with energy consuming routing protocol. In this work, we investigated the energy performance of LDPC code in multi-hop wireless sensor network. We proposed a model of two base stations to prolong the lifetime and build a reliable and energy-efficient network. Through performed MATLAB simulations, we examine the energy effectiveness of multiple base stations model on reliable wireless sensor network performance in different network dimensions.
An Improved Energy Efficient Wireless Sensor Networks Through Clustering In C...Editor IJCATR
One of the major reason for performance degradation in Wireless sensor network is the overhead due to control packet and packet delivery degradation. Clustering in cross layer network operation is an efficient way manage control packet overhead and which ultimately improve the lifetime of a network. All these overheads are crucial in a scalable networks. But the clustering always suffer from the cluster head failure which need to be solved effectively in a large network. As the focus is to improve the average lifetime of sensor network the cluster head is selected based on the battery life of nodes. The cross-layer operation model optimize the overheads in multiple layer and ultimately the use of clustering will reduce the major overheads identified and their by the energy consumption and throughput of wireless sensor network is improved. The proposed model operates on two layers of network ie., Network Layer and Transport Layer and Clustering is applied in the network layer . The simulation result shows that the integration of two layers reduces the energy consumption and increases the throughput of the wireless sensor networks.
Enhancing Survivability, Lifetime, and Energy Efficiency of Wireless NetworksIJRES Journal
In this paper, we focus on improving wireless networks survivability in terms of increasing network lifetime and its energy efficiency via clustering the network in an efficient way. Clustering the network is the procedure of partitioning it into groups, where each of them is known as a cluster. Each cluster elects the station with the highest power to be a cluster head. The remaining stations follow the nearest cluster head. Instead of having each station sends its packets to a remote receiver, the cluster head receives packets from all stations within its cluster, aggregates them, and forwards the resulting packets to the remote receiver. The most significant benefit of clustering the network that we focus on is to decrease distances between sending and receiving stations, which in turn reduces the transmission energy. This reduction in the energy yields an increase in the network lifetime and its survivability.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Mobile Ad-Hoc Network (MANET) is a self-configuring network of mobile devices connected through wireless. Nowadays mobile devices in mobile Ad-hoc network are battery operated. Battery is an important factor in MANET. Dynamic topology of mobile ad-hoc network and limited battery capacity are constrained on network life time. In this paper, we have presented variants of power aware techniques in an on-demand reactive routing protocol i.e. AODV which aims to prolong network lifetime. AODV is reactive protocol and it establish route on demand.
Ad hoc networks are self-configuring networks and each node executes routing functionalities by itself;
they are powered by battery, which is prone to decrease with time. In this paper, a power aware routing
algorithm called Dynamic path switching is proposed which attempt to extend the lifetime of network in
MANET. It creates a new path based on the energy level of the nodes. Along with DPS the Transmission
power control technique is incorporated which varies the transmission power based on the distance. It
reduces power consumption further. The proposed techniques are incorporated in Zone Routing Protocol
(ZRP) and simulated by using NS-2 simulator to obtain the QOS parameters.
An Adaptive Energy Aware Clustering Based Reliable Routing for in-Network Agg...Editor IJCATR
Wireless Sensor Network (WSN) consists of spatially distributed autonomous devices that cooperatively sense physical or
environmental conditions. Due to the non-uniform node deployment, the energy consumption among nodes are more
imbalanced in cluster-based wireless sensor networks this factor will affect the network life time. Cluster-based routing and EADC
algorithm through an efficient energy aware clustering algorithm is employed to avoid imbalance network distribution. Our proposed
protocol EADC aims at minimizing the overall network overhead and energy expenditure associated with the multi hop data retrieval
process while also ensuring balanced energy consumption among SNs and prolonged network life time .A optimal one-hop based
selective node in building cluster structures consisted of member nodes that route their measured data to their assigned cluster head is
identified to ensure efficient communication. The proposed routing algorithm increases forwarding tasks of the nodes in scarcely
covered areas by forcing cluster heads to choose nodes with higher energy and fewer member nodes and finally, achieves
imbalanced among cluster head and improve the network life time.
Coverage and Connectivity Aware Neural Network Based Energy Efficient Routing...graphhoc
There are many challenges when designing and deploying wireless sensor networks (WSNs). One of the key challenges is how to make full use of the limited energy to prolong the lifetime of the network, because energy is a valuable resource in WSNs. The status of energy consumption should be continuously monitored after network deployment. In this paper, we propose coverage and connectivity aware neural network based energy efficient routing in WSN with the objective of maximizing the network lifetime. In the proposed scheme, the problem is formulated as linear programming (LP) with coverage and connectivity aware constraints. Cluster head selection is proposed using adaptive learning in neural networks followed by coverage and connectivity aware routing with data transmission. The proposed scheme is compared with existing schemes with respect to the parameters such as number of alive nodes, packet delivery fraction, and node residual energy. The simulation results show that the proposed scheme can be used in wide area of applications in WSNs.
34 9141 it ns2-tentative route selection approach for edit septianIAESIJEECS
Wireless Sensor Networks (WSNs) assume a crucial part in the field of mechanization and control where detecting of data is the initial step before any automated job could be performed. So as to encourage such perpetual assignments with less vitality utilization proportion, clustering is consolidated everywhere to upgrade the system lifetime. Unequal Cluster-based Routing (UCR) [7] is a standout amongst the most productive answers for draw out the system lifetime and to take care of the hotspot issue that is generally found in equivalent clustering method. In this paper, we propose Tentative Route (TRS) Selection approach for irregular Clustered Wireless Sensor Networks that facilitates in decision an efficient next relay to send the data cumulative by Cluster Heads to the Base Station. Simulation analysis is achieved using the network simulator to demonstrate the effectiveness of the TRS method.
ENERGY EFFICIENT ROUTING ALGORITHM FOR MAXIMIZING THE MINIMUM LIFETIME OF WIR...ijasuc
In wireless sensor network, devices or nodes are generally battery powered devices. These nodes have
limited amount of initial energy that are consumed at different rates, depending on the power level. The
lifetime of the network is defined as the time until the first node fails (or runs out of battery). In this paper
different type of energy efficient routing algorithms are discussed and approach of these algorithms is to
maximize the minimum lifetime of wireless sensor network. Special attention has been devoted for
algorithms formulate the routing problem as a linear programming problem, which uses the optimal flow
path for data transmission and gives the optimum results. Advantages, limitations as well as comparative
study of these algorithms are also discussed in this paper.
Design and Performance Analysis of Energy Aware Routing Protocol for Delay Se...ijcncs
This document presents a study on an energy aware routing protocol called Energy Aware DSR (EADSR) for wireless sensor networks. EADSR is an extension of the Dynamic Source Routing (DSR) protocol that adds energy awareness to improve network lifetime. The study compares the performance of DSR and EADSR through simulations. Results show that EADSR outperforms DSR in terms of energy savings and avoids early network partitioning caused by nodes draining their energy quickly. EADSR selects routes based on the total energy of nodes along the path and notifies neighbors when a node's energy is low to find alternative routes before it fails.
Gateway based multi hop distributed energy efficient clustering protocol for ...ijujournal
Wireless sensor network consists of application oriented and cheap micro-devices called sensors nodes having potential of connecting the physical world with virtual world by their sensing abilities. These sensor nodes are having restrained battery sources. Efficient energy management is current area of research in wireless sensor networks. Here we advice one such energy aware multi-hop protocol (G-DEEC) for two
level heterogeneous networks. In G-DEEC, the Base Station is placed out of sensing area and rechargeable
gateway nodes are placed inside field with other randomly deployed sensor nodes. Simulation shows the proposed protocol G-DEEC is better than single-hop DEEC in terms of number of half dead nodes, alive nodes and dead nodes; thereby showing improvement in network lifetime and stability.
Optimized Cluster Establishment and Cluster-Head Selection Approach in WSNIJCNCJournal
In recent years, limited resources of user products and energy-saving are recognized as the major challenges of Wireless Sensor Networks (WSNs). Clustering is a practical technique that can reduce all energy consumption and provide stability of workload that causes a larger difference in energy depletion among other nodes and cluster heads (CHs). In addition, clustering is the solution of energy-efficient for maximizing the network longevity and improvising energy efficiency. In this paper, a novel OCE-CHS (Optimized Cluster Establishment and Cluster-Head Selection) approach for sensor nodes is represented to improvise the packet success ratio and reduce the average energy-dissipation. The main contribution of this paper is categorized into two processes, first, the clustering algorithm is improvised that periodically chooses the optimal set of the CHs according to the speed of the average node and average-node energy. This is considerably distinguished from node-based clustering that utilizes a distributed clustering algorithm to choose CHs based on the speed of the current node and remaining node energy. Second, more than one factor is assumed for the detached node to join the optimal cluster. In the result section, we discuss our clustering protocols implementation of optimal CH-selection to evade the death of SNs, maximizing throughput, and further improvise the network lifetime by minimizing energy consumption.
Opportunistic routing algorithm for relay nodejpstudcorner
The document proposes an energy-efficient opportunistic routing algorithm called ENS_OR for wireless sensor networks. ENS_OR selects relay nodes based on an "energy equivalent node" concept from opportunistic routing theory to minimize energy consumption and maximize network lifetime. It prioritizes nodes as forwarders according to their transmission distance from equivalent nodes and remaining energy levels. Simulations and testbed results show ENS_OR significantly improves energy savings and connectivity over existing routing schemes.
In wireless sensor network energy cutback is considered as a principle intensive challenge which is studied largely in the Wireless Sensor Networks (WSN) literature. Wireless Sensor Networks (WSNs) are pertinent in numerous arenas where WSNs may be used for sensing, ciphering, and communication elements that give a user or administrator the ability to instrument, observe, and retort to events and phenomena in a specific environment. But sensor devices are resource curbed, positioned in an open and unattended environment, different types of attacks and conventional techniques against these attacks are not desirable due to the resource constrained nature of these kinds of networks. An energy-balanced routing method based on forward-aware factor (FAF-EBRM) in which the next-hop node is elected according to the awareness of link weight and forward energy density. FAF-EBRM is compared with Ladder Diffusion Algorithm, which balances the energy utilization, sustain the function era and guarantees high QoS of WSN. The FAF-EBRM is proposed with Secure Routing Layer (SRL) Protocol which ensures that the secure data transmission is achieved without releasing private sensor readings and without introducing significant overhead on the battery-limited sensors.
WEIGHTED DYNAMIC DISTRIBUTED CLUSTERING PROTOCOL FOR HETEROGENEOUS WIRELESS S...ijwmn
This document describes a new clustering protocol called WDDC (Weighted Dynamic Distributed Clustering) for heterogeneous wireless sensor networks. WDDC selects cluster heads based on the ratio of a node's residual energy to the average network energy, and also considers the distance between nodes and the base station. WDDC divides the network lifetime into two zones and changes its behavior dynamically between the zones. Simulation results show WDDC outperforms other clustering protocols like SEP and DEEC in terms of energy efficiency and extending network lifetime.
A Proactive Greedy Routing Protocol Precludes Sink-Hole Formation in Wireless...ijwmn
The International Journal of Wireless & Mobile Networks (IJWMN) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Wireless & Mobile Networks. The journal focuses on all technical and practical aspects of Wireless & Mobile Networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced wireless & mobile networking concepts and establishing new collaborations in these areas.
A gateway based energy efficient multi hop routing protocol for wireless sensor networks (WSNs) is
introduced. The main aim of our paper is to design a protocol which minimizes energy consumption.
Gateway nodes are deployed in sensing field.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
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yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
This document discusses finding an optimum transmission range in a wireless sensor network to balance delay and energy consumption. It analyzes how transmission range, node deployment, number of hops, and forwarding techniques affect energy usage. The researchers deployed sensor nodes in a grid and evaluated greedy forwarding and residual energy forwarding under varying transmission ranges. They found that an optimal range exists that uses less energy per transmission while minimizing the number of hops needed to reach destinations.
Energy Efficient Multipath Routing For Mobile Ad Hoc NetworksZac Darcy
Energy consumption is a significant issue in ad hoc networks since mobile nodes are battery powered. In
order to prolong the lifetime of ad hoc networks, it is the most critical issue to minimize the energy
consumption of nodes. In this paper, we propose an energy efficient multipath routing protocol for
choosing energy efficient path. This system also considers transmission power of nodes and residual energy
as energy metrics in order to maximize the network lifetime and to reduce energy consumption of mobile
nodes. The objective of our proposed system is to find an optimal route based on two energy metrics while
choosing a route to transfer data packets. This system is implemented by using NS-2.34. Simulation results
show that the proposed routing protocol with transmission power and residual energy control mode can
extend the life-span of network and can achieve higher performance when compared to traditional ad-hoc
on-demand multipath distance vector (AOMDV) routing protocol.
Energy Efficient Multipath Routing For Mobile Ad Hoc NetworksZac Darcy
Energy consumption is a significant issue in ad hoc networks since mobile nodes are battery powered. In
order to prolong the lifetime of ad hoc networks, it is the most critical issue to minimize the energy
consumption of nodes. In this paper, we propose an energy efficient multipath routing protocol for
choosing energy efficient path. This system also considers transmission power of nodes and residual energy
as energy metrics in order to maximize the network lifetime and to reduce energy consumption of mobile
nodes. The objective of our proposed system is to find an optimal route based on two energy metrics while
choosing a route to transfer data packets. This system is implemented by using NS-2.34. Simulation results
show that the proposed routing protocol with transmission power and residual energy control mode can
extend the life-span of network and can achieve higher performance when compared to traditional ad-hoc
on-demand multipath distance vector (AOMDV) routing protocol.
Performance Evaluation of Consumed Energy-Type-Aware Routing (CETAR) For Wire...ijwmn
This document evaluates the performance of Consumed-Energy-Type-Aware Routing (CETAR) for wireless sensor networks. CETAR makes routing decisions based on statistics of the energy consumed for different node activities like sensing, transmitting, and routing. It aims to encourage nodes that are not often data sources to serve as routing nodes, in order to preserve the energy of active source nodes and prolong network lifetime. Simulation results show that CETAR can significantly extend the lifetime of routing protocols like Geographic and Energy Aware Routing (GEAR) by taking each node's energy consumption patterns into account.
Design Optimization of Energy and Delay Efficient Wireless Sensor Network wit...IOSR Journals
This document describes a proposed approach to optimize energy efficiency and delay in wireless sensor networks using a combination of particle swarm optimization and cluster-based least spanning tree algorithms. It begins with background on challenges in wireless sensor networks related to limited energy resources. It then presents the system model, including the network and radio power models. The document goes on to describe particle swarm optimization and how it can be applied to set up energy-efficient clusters in each round. The goal is to select cluster heads that minimize a cost function balancing energy usage and delay.
Energy efficient data communication approach in wireless sensor networksijassn
Wireless sensor network has a vast variety of applications. The adoption of energy efficient cluster-based
configuration has many untapped desirable benefits for the WSNs. The limitation of energy in a sensor
node creates challenges for routing in WSNs. The research work presents the organized and detailed
description of energy conservation method for WSNs. In the proposed method reclustering and multihop
data transmission processes are utilized for data reporting to base station by sensor node. The accurate use
of energy in WSNs is the main challenge for exploiting the network to the full extent. The main aim of the
proposed method is that by evenly distributing the energy all over the sensor nodes and by reducing the
total energy dissipation, the lifetime of the network is enhanced, so that the node will remain alive for
longer times inside the cluster. The result shows that the proposed clustering approach has higher stable
region and network life time than Topology-Controlled Adaptive Clustering (TCAC) and Low-Energy
Adaptive Clustering Hierarchy (LEACH) for WSNs.
ENERGY EFFICIENT DATA COMMUNICATION APPROACH IN WIRELESS SENSOR NETWORKSijassn
Wireless sensor network has a vast variety of applications. The adoption of energy efficient cluster-based configuration has many untapped desirable benefits for the WSNs. The limitation of energy in a sensor node creates challenges for routing in WSNs. The research work presents the organized and detailed description of energy conservation method for WSNs. In the proposed method reclustering and multihop data transmission processes are utilized for data reporting to base station by sensor node. The accurate use of energy in WSNs is the main challenge for exploiting the network to the full extent. The main aim of the proposed method is that by evenly distributing the energy all over the sensor nodes and by reducing the total energy dissipation, the lifetime of the network is enhanced, so that the node will remain alive for longer times inside the cluster. The result shows that the proposed clustering approach has higher stable region and network life time than Topology-Controlled Adaptive Clustering (TCAC) and Low-Energy Adaptive Clustering Hierarchy (LEACH) for WSNs.
Implementation and analysis of multiple criteria decision routing algorithm f...prjpublications
This document summarizes a research paper that proposes and evaluates a new routing algorithm called Multiple Criteria Decision Routing (MCDR) for wireless sensor networks. MCDR selects the next node to forward data based on both the node's distance to the sink and its remaining energy. The performance of MCDR is compared to flooding algorithm through simulation. Simulation results show that MCDR has better performance than flooding in terms of energy efficiency and fast data delivery.
Energy-Efficient Hybrid K-Means Algorithm for Clustered Wireless Sensor Netw...IJECEIAES
Energy efficiency is the most critical challenge in wireless sensor network. The transmission energy is the most consuming task in sensor nodes, specifically in large distances. Clustered routing techniques are efficient approaches used to lower the transmission energy and maximize the network’s lifetime. In this paper, a hybrid clustered routing approach is proposed for energy optimization in WSN. This approach is based on KMeans clustering algorithm and LEACH protocol. The simulation results using MATLAB tool have shown that the proposed hybrid approach outperforms LEACH protocol and optimizes the nodes energy and the network lifetime.
Clustering provides an effective method for
extending the lifetime of a wireless sensor network. Current
clustering methods selecting cluster heads with more residual
energy, and rotating cluster heads periodically to distribute the
energy consumption among nodes in each cluster. However,
they rarely consider the hot spot problem in multi hop sensor
networks. When cluster heads forward their data to the base
station, the cluster heads closer to the base station are heavily
burdened with traffic and tend to die much faster. To mitigate
the hot spot problem, we propose a Novel Energy Efficient
Unequal Clustering Routing (NEEUC) protocol. It uses residual
energy and groupsthe nodesinto clusters of unequal layers
MPC-EAR : Maximal Power Conserved And Energy Aware Routing in Ad hoc Networksijsrd.com
Power preservation in wireless ad hoc networks is a decisive factor as energy resources are inadequate at the electronic devices in use. Power-aware routing strategies are fundamentally route selection strategies built on accessible ad hoc routing protocols. This paper proposed a new Maximal Power Conserved And Energy Aware Routing (MPC-EAR ) topology for mobile ad hoc networks that enhances the network life span. Simulation results prove that the projected protocol has a higher performance other minimal energy usage, energy level aware and energy conserving routing protocols such as MTPR, MMECR and CMMECR.
This document presents a clustering approach using a handoff mechanism to enhance network lifetime in wireless sensor networks. It proposes using a mobile-based LEACH-ERE method for clustering and cluster head election to improve energy efficiency. The method considers both fixed and mobile nodes to increase network lifetime, packet delivery ratio, and energy usage effectiveness. It was found that the mobile-based LEACH-ERE approach increases network lifetime and packet delivery ratio compared to the static LEACH protocol, as it consumes less energy over time.
An energy aware scheme for layered chain in underwater wireless sensor networ...IJECEIAES
Extending the network lifetime is a very challenging problem that needs to be taken into account during routing data in wireless sensor networks in general and particularly in underwater wireless sensor networks (UWSN). For this purpose, the present paper proposes a multilayer chain based on genetic algorithm routing (MCGA) for routing data from nodes to the sink. This algorithm consists to create a limited number of local chains constructed by using genetic algorithm in order to obtain the shortest path between nodes; furthermore, a leader node (LN) is elected in each chain followed by constructing a global chain containing LNs. The selection of the LN in the closest chain to the sink is as follows: Initially, the closest node to sink is elected LN in this latter because all nodes have initially the same energy value; then the future selection of the LN is based on the residual energy of the nodes. LNs in the other chains are selected based on the proximity to the previous LNs. Data transmission is performed in two steps: intra-chain transmission and inter-chain transmission. Furthermore, MCGA is simulated for different scenarios of mobility and density of nodes in the networks. The performance evaluation of the proposed technique shows a considerable reduction in terms of energy consumption and network lifespan.
The comparison between routing protocols based on lifetime of wireless sensor...inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Improved aodv based on energy strength and dropping ratioIJLT EMAS
Wireless Sensor Networks are the latest trends in the
market due to the demand for communication and networking
among the wireless network devices. The routing protocols are
used in the Wireless Sensor Networks for efficient
communication of data between sensor nodes. The designs of
routing protocols in Wireless Sensor Networks are very concern
because they are influenced by many challenging factors. To
design the networks, the factors needed to be considered are the
coverage area, mobility, energy power consumption,
communication capabilities etc.. Broadcasting is an inevitable
operation in the route discovery phase of AODV protocol. A
probability based AODV is proposed, it uses nodes remaining
energy and threshold random delay to generate the
rebroadcasting of route request packet. The route request packet
of AODV is modified to gather nodes remaining energy strength.
The performance of probability based AODV is compared with
AODV over packet delivery fraction, normalized routing
overhead, delay and average acquisition latency.
NS-2 based simulator is used to evaluate the performance of
routing protocol.
DATA GATHERING ALGORITHMS FOR WIRELESS SENSOR NETWORKS: A SURVEYijasuc
Recent developments in processor, memory and radio technology have enabled wireless sensor networks
which are deployed to collect useful information from an area of interest. The sensed data must be
gathered and transmitted to a base station where it is further processed for end-user queries. Since the
network consists of low-cost nodes with limited battery power, power efficient methods must be employed
for data gathering and aggregation in order to achieve long network lifetimes. In an environment where in
a round of communication each of the sensor nodes has data to send to a base station, it is important to
minimize the total energy consumed by the system in a round so that the system lifetime is maximized. With
the use of data fusion and aggregation techniques, while minimizing the total energy per round, if power
consumption per node can be balanced as well, a near optimal data gathering and routing scheme can be
achieved in terms of network lifetime. Several application specific sensor network data gathering protocols
have been proposed in research literatures. However, most of the proposed algorithms have been some
attention to the related network lifetime and saving energy are two critical issues for wireless sensor
networks. In this paper we have explored general network lifetime in wireless sensor networks and made an
extensive study to categorize available data gathering techniques and analyze possible network lifetime on
them.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
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Power Grid Model
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Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
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Computer Science & Information Technology (CS & IT)
Sensor nodes of a wireless sensor networks generally work as a unit of a system to complete
certain obligations. Shutdown of any sensor nodes from the network creates data deficiency, and
as a result the whole sensor network produces an erroneous result, incorrect and imperfect vision
of environment and network is became paralyzed. In some applications, like in biomedical sensor
networks, the consequence of paralyzed network cases death penalty. A routing method, which
ensures balanced consumption of energy among the sensor nodes of the WSNs is essential.
2. RELATED WORKS
Energy efficiency is not only an issue of wireless sensor networks, it also a challenging issues in
all forms of networks to meet the green communication requirements. Efficient routing protocol
ensures the efficient and energy-aware communication in wireless sensor networks. Routing
protocols of wireless sensor networks have been studied in reference [1] with introducing some
challenges and future directions. Partial differential equation based geographical routing is
proposed in reference [2]. The model is dependent on a central node, which collects the position
information, residual energy information and then determines the routing path based on the
proposed algorithm. The proposal is based on centralized control unit, which is not suitable for
the WSNs, where there is no central node. A cluster [3][4] based and threshold sensitive routing
protocol is presented in reference [5], where the authors consider power availability, nodes
position, and reachability factors to determine the routing path by using cluster head. Though this
proposal achieved energy efficiency but the proposal didn’t concentrate on networking life time.
A hybrid routing protocol for WSNs is presented in reference [6], which allows a comprehensive
information retrieval of environmental analysis and facilitate users to query of past, present and
future data. This is also an application specific and cluster based routing protocol, which is
focused on efficient path finding by maintaining energy-efficiency but not concerning about
network life time. Some other cluster based routing protocol also proposed in reference [7] and
[8]. Greedy perimeter stateless routing approach for wireless networks is proposed in reference
[9], where it considers the position of source and destination to send data packets, they also
presented better results than shortest-path and ad-hoc routing protocols in respect of routing
protocol overhead, packet delivery rate and path length. They didn’t consider energy efficiency
and energy balancing issues in their routing protocols. The security gaps, and possible attacks of
wireless sensor networks routing are studied in reference [10], the study presented the
countermeasures and challenges of designing routing protocol with ensuring security of the data
packets travelling through huge nodes of WSNs.
Power efficient topologies for sensor networks are presented in reference [11], where the authors
proposed directional source aware routing protocol (DSAP) and deploy it in different 2D and 3D
static network topologies to study power efficient network topology. Though the presented DSAP
minimizes the energy consumption of the nodes of considered networks, but DSAP could not
ensure energy balancing among the nodes of WSNs.
3. SYSTEM MODEL
The system model of the proposed energy efficient and load balanced routing protocol (EELBRP)
for wireless sensor network is discussed in this section. Wireless sensors are deployed in various
patterns based on application requirements. This paper considers that the deployment of sensor
nodes follows two-dimension (2D) topology as on DSAP. The neighbour nodes are defined on
the basis of 1-hop communication model and 2-hop communication model.
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3.1. 1-Hop Communication Model
In 1-hop communication model, shown in figure 1, a sensor node has maximum eight neighbours
within direct communication range. Between the node and the neighbours nodes can participate in
transmissions, receptions and forwarding of data. When a node transmits packet to a neighbour
node other eight neighbours can overhear the packet. In transmission, a node expenses energy for
running transmitter circuits (ETx_circuit) and also expenses energy for sending packets to distance d1
that is one hop distance amplification energy (ETx_amplifier) cost. Thus, to transmit b bits of packet
to its 1-hop neighbour, transmitter node expenses total ETx_tcost energy by equation (1).
(1)
As all the 1-hop neighbour nodes from the sender, overhear the b bits, n1 shows the number of
neighbours except the receivers. The total overhearing energy cost of all neighbour nodes
(ERx_tcost) is equivalent to the total energy consumption of n1 receiver circuits ( ERx_circuit ) as
formulated in equation (2).
(2)
Figure 1. 1-Hop communication model for EELBRP
3.2. 2-Hop Communication Model
The 2-hop communication model for the proposed EELBRP is shown at figure 2, where sensor
node has maximum twenty neighbours. When any node transmits packet other neighbours can
overhear the packet.
(3)
In case of transmission, a node not only expenses energy for running transmitter circuits
(ETx_circuit) but also expenses energy for sending packets to distance d2 that is amplification energy
(ETx_amplifier) cost to transmit packet over d2 distance. Thus, to transmit b bits of packet to any of
its 2-hop neighbours, the transmitter node expenses total ETx_tcost energy by equation (3).
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Computer Science & Information Technology (CS & IT)
In 2-hop communication model, all the 1-hop neighbour nodes n1, and the nodes situated far from
distance d1, also distance d2 nodes n2; overhears the b bits of packet, so the total overhearing
energy cost of all neighbour nodes (E2Rx_tcost) is equivalent to the total energy consumption of (n1
+ n2) receiver circuits ( ERx_circuit ) as formulated in equation (4).
(4)
Figure 2. 2-Hop communication model for EELBRP
4. ROUTING PROTOCOL FOR ENERGY EFFICIENCY AND LOAD BALANCING
In this section, the detail discussion of the proposed EELBRP is presented.
Figure 3. Direction of destination node from source node in 1-hop communication model
The proposed EELBRP is a directional routing protocol, corresponding to the direction of
receiver node; it selects the forwarder nodes from a feasible set of forwarders.
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4.1. Routing Procedure for 1-Hop communication Model
Consider the case (a) of figure 3, where the sender node Sa is 7 and destination node Ra is 25. To
find out the direction of the receiver node, the Cartesian coordinates of sender node Sa(i,j) and the
destination node Ra(i,j) is compared according to algorithm 4.1.
In algorithm 4.1, two direction variables are D1 and D2, and L, R, D, U represent of left, right,
down and up respectively. Based upon the determined values D1 and D2, the feasible set of
forwarder are selected and called as the adjacent list for 1-hop communication Adi_PR1 and that
is Adj_PR1_a={ D1R1,R1,D1,U1R1,D1L1}={13,8,12, 3, 11} is for case (a), where u1=i-1,
d1=i+1,L1=j-1, and r1=j+1.
Similarly, the adjacent list of prioritized nodes for 1-hop communication of case (b), (c), (d) is
defined respectively as
Adj_PR1_b={U1L1,L1,U1,U1R1,D1L1}, Adj_PR1_c={U1R1,R1,U1,U1L1,D1R1},
Adj_PR1_d={D1L1,L1,D1,D1R1,U1R1}.
Algorithm 4.1: Direction(S(i,j), R(i,j))
1. If R(i)<S(i) then D1=L otherwise D1=R
2. If R(j)>S(j) then D2=D otherwise D2=U
3. If D1=R & D2=D then
4.
Adj_PR1_a[S]={d1r1,r1,d1,u1r1,d1L1}
5. Else If D1=L & D2=U then
6.
Adj_PR1_b[S]={u1L1,L1, u1,u1r1,d1L1}
7. Else If D1=R & D2=U then
8.
Adj_PR1_c[S]={u1r1,r1,u1,u1L1,d1r1}
9. Else
10.
Adj_PR1_d[S]={d1L1,L1,d1,d1r1,u1r1}
Among the feasible set of forwarder of Adj_PR1, the best suitable forwarder is selected based
upon the logical distance or air distance or admissible heuristic distance from probable forwarder
to the destination, which is determined in algorithm 4.2. As the assumed WSNs deployed using
2D and stationary topology, each and every node has a logical Cartesian coordinates to find out
logical distance Ld using equation number (5)
Ld[v] ←
(5)
Where R(i,j) is the logical coordinate of receiver node and v(i,j) is the logical coordinate of
feasible forwarder.
Algorithm 4.2: Relax(R, v)
Ld[v] ←
After finding the logical distances from list of feasible forwarder nodes to receiver nodes, the
node with minimum distance is selected as the most suitable forwarder, maintain a minimum
priority queue of suitable forwarders. The routing method is presented in algorithm 4.3 is an alias
of Dijkstra’s algorithm, where T stands for topology or given WSNs , N[T] represents the nodes
of the topology T, and variable Route gradually stores the routing path from sender to receiver.
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Computer Science & Information Technology (CS & IT)
Algorithm 4.3: PE_Routing(T, S, R)
1. Initialize_Routing(T,S) //Function
2. Route←ϕ
3. Min_PR_Q←N[T] //Priority based on logical distance Ld
4. Do
5.
u←Extract_min (Min_PR_Q)
6.
Route←Route ∪ { u }
7.
Direction (u, R)
//Function
8.
For each node v ∈ Adj_PR1[u] ∪ Adj_PR2[u]
9.
Relax(R,v,)
//Function
10. Energy_Status_Update(u, Min_PR_Q) //Function
11. While(u ≠ R)
Algorithm 4.3, consists a procedure for initialization of nodes residual energy variable
Res_energy as maximum energy of the batteries of sensor nodes at starting time. Logical
distances from sender to all other nodes are also initialized as infinite at the beginning of routing
procedure in algorithm 4.4.
Algorithm 4.4: Initialize_Routing(T, S, R)
1. For each node v ∈ N[T]
2.
Res_energy[v]←MaxEnergy
3.
Ld[v]←∞
4. Ld[S]←0
Algorithm 4.3, also consists an energy status updating function for dynamic updates of sensor
nodes residual energy after sending and receiving of data packets. For changing the energy status
of receiver (forwarder) nodes, all the 1-hop neighbor nodes (Adj1) are considered because of the
broadcasting nature of WSNs. Algorithm 4.5 is designed with the energy model formulated in
equation (1) and (2).
Algorithm 4.5: Energy_Status_Update(u)
1. Z←min(Min_PR_Q)
2. For each node a∈Adj1[u]
3.
Res_energy[a]←Res_energy[a]-Eelec* b
4. Res_energy[u]←Res_energy[a]-Eelec* b * (dist1)2(u,Z)
4.2. Routing Procedure for 2-Hop& 1-hop Combine Communication Model
The routing procedure for 2-hop & 1-hop combine communication model of proposed EELBRP
is little bit different from 1-hop communication model. In this combine communication model
sender node always tries to send packets to its one hop neighbours first for forwarding. The
direction of destination node will need to be determined here also in combine model. The
procedure of determining the direction of receiver node is defined in algorithm 4.6.
Consider the case (a) of figure 4, where sender node Sa is 7 and receiver node Ra is 25, we
follow almost same procedure to determine the direction as we discussed in section 4.1, but the
feasible set of forwarders are also included not only the 1-hop but also the 2-hop nodes, which
we call the adjacent list of prioritized nodes for 2-hop communication Adi_PR2 and that is
Adj_PR2_a={d2r1,r2d1,d2,r2}={18,14,17, 9}, where d2=i+2, r2=j+2, u2=i-2, and L2=j-2.
Similarly, the adjacent list of prioritized nodes for 2-hop communication of case (b), (c), (d) is
7. Computer Science & Information Technology (CS & IT)
defined respectively as Adj_PR2_b={u2L1,L2u1,u2,L2},
Adj_PR2_d={ d2L1,L2d1,d2,L2}.
159
Adj_PR2_c={u2r1,r2u1,u2,r2},
Figure 4. Direction of destination node corresponding to source node in 2-hope & 1-hop combine
communication model
Algorithm 4.6: Direction(S(i,j), R(i,j))
1. If R(i)<S(i) then D1=L otherwise D1=R
2. If R(j)>S(j) then D2=D otherwise D2=U
3. If D1=R & D2=D then
4.
Adj_PR1_a[S]={d1r1,r1,d1,u1r1,d1L1}
5.
Adj_PR2_a[S]={d2r1,r2d1,d2,r2}
6. Else If D1=L & D2=U then
7.
Adj_PR1_b[S]={u1L1,L1,u1,u1r1,d1L1}
8.
Adj_PR2_b[S]={u2L1,L2u1,u2,L2}
9. Else If D1=R & D2=U then
10.
Adj_PR1_c[S]={u1r1,r1,u1,u1L1,d1r1}
11.
Adj_PR2_c[S]={u2r1,r2u1,u2,r2}
12. Else
13.
Adj_PR1_d[S]={d1L1,L1,d1,d1r1,u1r1}
14.
Adj_PR2_d[S]={d2L1,L2d1,d2,L2}
Among the feasible set of forwarders of Adj_PR1 and Adj_PR2, the best suitable forwarder is
selected based upon the logical distance from probable forwarder to destination, which is
determined in algorithm 4.7, the logical distance of destination node from 1-hop feasible
forwarders will get higher priority as their distance is customized with negative sign.
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Computer Science & Information Technology (CS & IT)
Algorithm 4.7: Relax(R, v)
1. IF v∈ Adj_PR2[u]
2.
Ld[v]← (
3. Else
4.
Ld[v]← Among the determined logical distances, the feasible forwarder node with minimum distance is
selected as the suitable forwarder towards the receiver. Algorithm 4.8 presents the suitable
forwarder selection procedure considering both of the feasible set of forwarders of Adj_PR1 and
Adj_PR2 at line number 8.
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
Algorithm 4.8: PE_Routing(T, S, R)
Initialize_Routing(T,S) //Function
Route←ϕ
Min_PR_Q←N[T] //Priority based on logical distance Ld
Do
u←Extract_min (Min_PR_Q)
Route←Route ∪ { u }
Direction (u, R)
//Function
For each node v ∈ Adj_PR1[u] ∪ Adj_PR2[u]
Relax(R,v,)
//Function
Energy_Status_Update(u, Min_PR_Q) //Function
While(u ≠ R)
Algorithm 4.8 also calls the energy status updating procedure, which is presented in algorithm
4.9. For changing the energy status of receiver (forwarder) nodes, all the 1-hop neighbor nodes
(Adj1) and 2-hop neighbor nodes (Adj2) are considered because of the broadcasting nature of
WSNs. Algorithm 4.9 is designed with the energy model formulated in equation (3) and (4).
Algorithm 4.9: Energy_Status_Update(u)
1. Z←min(Min_PR_Q)
2. IF Z ∈ Adj_PR1[u]
3.
For each node a∈Adj1[u]
4.
Res_energy[a]←Res_energy[a]-Eelec* b
5. Else
6.
For each node b∈Adj12[u]
7.
Res_energy[a]←Res_energy[a]-Eelec* b
8. Res_energy[u]←Res_energy[a]-Eelec* b * dist2(u,Z)
4.3. Routing Procedure for 2-Hop& 1-Hop Combine Communication Model with
Energy-Awareness
To design an energy aware and energy balanced routing protocol the 2-hop & 1-hop combine
communication model of figure 4 is used. As the Relax function is the controlling function of
suitable forwarder node selection, the Relax function is designed accordingly in algorithm 4.10 to
select forwarders in energy-efficient manner. If residual energy of the prioritized neighboring
node of sender is greater than the threshold-1 (th1) then just follow 2-hop & 1-hop combine
routing procedure to select forwarders, but if residual energy of all of the prioritized neighboring
node of sender is less than the threshold-1 (th1) but greater than threshold-2 (th2) then determine
energy ratio of each of the node, and update logical distance variable based on energy ratio. So, in
such case the routing algorithm 4.8 tries to balance energies of the whole network between
9. Computer Science & Information Technology (CS & IT)
161
threshold-2. Finally, if the residual energy of the entire prioritized neighboring node of sender is
less than the threshold-2 then algorithm determines, which node consumes less energy i.e which
node has much residual energy and update logical distance accordingly. By this procedure, the
node with highest residual energy among feasible forwarder list Adj_PR1 and Adj_PR2 placed in
the 1st position of the minimum priority queue as well as selected as the best suitable forwarder
for balancing energies among its neighbors.
Algorithm 4.10: Relax(R, v)
1. IF Res_energy[v]> th1
2.
IF v∈ Adj_PR2[u]
3.
Ld[v]← -(
4.
Else
5.
Ld[v]←
6. Else IF th2<Res_energy[v]< th1
7.
Ld[v] ←
8. Else
9.
Ld[v] ←Initial_Energy[v]-Res_Energy[v]
5. SIMULATION RESULTS
To evaluate the performance of the proposed EELBRP algorithm, the MATLAB R2010a
simulation tools are used with C++ simulation program to analyze the energy efficiency and
balancing status. The simulation scenario is presented in Table 1.
Table 1. Simulation scenario for performance study of EELBRP algorithm
Simulation Parameters
Topology
Symbols
2D
Values
8 neighbors within 1 hop
20 neighbors within 2 hop
Number of nodes
Horizontal (or vertical)
distance between two nodes
nxn
d1
11x11
0.5 meters
Packet size
Total number of packets
Transmitter circuitry energy
Transmitter amplification energy
b
P
ETx_circuit
ETx_amplifier
512 bits
10,000
50 nJ/bit
100 pJ/bit/m2
ERx_circuit
th1
th2
50 nJ/bit
53 J
25 J
Receiver circuitry energy
Threshold-1
Threshold-2
The performance of proposed EELBRP is studied using two essential performance metric of
wireless sensor networks i.e energy efficiency and network lifetime. Figure 5 and figure 6 shows
the performance of the EELBRP algorithm without using energy balancing procedure. Between
these two figures, the figure 5 shows the residual energies of each of the 11X11=121 nodes of the
wireless sensor networks after handling 10,000 packets of 512 bits and following 1 hop
communication method. The total energy consumption is 4228.360266 Joules and residual energy
is balancing between 27 to 95 Joules.
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Computer Science & Information Technology (CS & IT)
Whereas, figure 6 shows the residual energies of each nodes of the wireless sensor networks after
handling same number of packets of 512 bits and following 2 hop communication method. The
total energy consumption is 5082.707723 Joules and residual energy is balancing between
Residual Energy Distribution in 1-Hop Method using 3D Surf
90
100
80
Total Energy Co nsum ption
90
80
70
70
60
60
50
40
30
50
20
10
8
10
6
40
8
6
4
4
2
30
2
0
Nodes Y Index
0
Nodes X Index
Figure5. Residual Energy of each nodes using EELBRP (1-Hop case)
21 to 90 Joules. In comparison between 1-hop and 2-hop communication method, following the
EELBRP without energy balancing procedure, 1-hop communication method consumes less
energy than 2-hop communication method. In comparison of energy balancing performance, in
both 1-hop and 2-hop cases the energy difference remains around 70 Joules, which means some
of the network nodes dies very firstly then other nodes, and network become paralyzed with short
period of time i.e performance of EELBRP without energy balancing procedure is not impressive
in respect to network lifetime.
Total Residual Energy Distribution in 2-Hop Method using 3D Surf
80
100
Total Energy Consum ption
90
70
80
70
60
60
50
50
40
30
40
20
10
8
10
6
8
4
2
Nodes Y Index
30
6
4
2
0
0
Nodes X Index
Figure 6. Residual Energy of each nodes using EELBRP (2-Hop Case)
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Figure 7 shows the residual energy distribution the nodes of the wireless sensor networks
following the proposed EELBRP with energy balancing procedure, where 1-hop and 2-hop
combine communication model is used rationally to improve network lifetime. The total energy
consumption is 4660.138730 Joules and residual energy is balancing between 65 to 92 Joules. In
comparison to 1-hop communication method, it consumes little bit more energy but in
comparison to 2-hop communication method, it consumes less energy.
But in comparison of energy balancing performance, the residual energy difference among the
sensor nodes of the network is 27 Joules, which means the EELBRP with energy balancing
procedure enhances network lifetime significantly with sacrificing limited total network energy.
Residual Energy Distribution in proposed energy-balance 2-Hop & 1-Hop Mixed Method using 3D Surf
90
90
Total Energy Consumption
85
85
80
75
80
70
65
60
75
55
50
10
70
8
10
6
8
6
4
4
2
2
0
Nodes Y Index
0
Nodes X Index
Figure 7. Residual Energy of each nodes using EELBRP (2-Hop & 1-Hop combine with energy balancing
procedure, where threshold 1 = 53 Joules and threshold 2=25 Joules)
Residual Energy Distribution in proposed energy-balance 2-Hop & 1-Hop Mixed Method using 3D Surf
90
85
Total E nergy Consum ption
100
80
90
75
80
70
70
65
60
60
50
10
55
8
10
6
4
4
2
45
2
0
Nodes Y Index
50
8
6
0
Nodes X Index
Figure 8. Residual Energy of each nodes using EELBRP (2-Hop & 1-Hop combine with energy balancing
procedure, where threshold 1 = 40 Joules and threshold 2=5 Joules)
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Computer Science & Information Technology (CS & IT)
The performance of the EELBRP with energy balancing procedure is also evaluated using
different threshold values. Figure 7~9 shows the network energy performance graph of various
threshold conditions, where the threshold 1 with 53 joules and threshold 2 with 25 joules clearly
shows their suitability and justification of threshold selection in figure 7.
Figure 9. Residual Energy of each nodes using EELBRP (2-Hop & 1-Hop combine with energy
balancing procedure, where threshold 1 = 60 Joules and threshold 2=35 Joules)
Table 2. Comparison of Total Energy Consumption among 2-hop, 1-hop & “2-hop + 1-hop combine with
energy balancing” method
Threshold 1 and
threshold 2
40 J and 5 J
53 J and 25 J
60 J and 35 J
Energy
Consumption
2-hop
communication
Method
1-hop
communication
method
Total
Consumption
5082.70772 J
4228.36026 J
Residual
Energy
distribution
Total
Consumption
21~90
27~95
5082.70772 J
4228.36026 J
21~90
27~95
Residual
Energy
distribution
Total
Consumption
Residual
Energy
distribution
5082.70772 J
4228.36026 J
21~90
27~95
Proposed
EELBRP
with energy
balancing
4357.4121J
Less
consumption
42~94
Imbalance
energy
4660.1387J
Moderate
consumption
65~92
Balanced
energy
4983.0121J
Higher
consumption
69~94
Balanced
energy
The performance study of EELBRP algorithm is summarized in table 2, where the proposed
EELBRP with energy balancing strategy shows its energy balancing power with moderate energy
13. Computer Science & Information Technology (CS & IT)
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consumption. The 2-hop and 1-hop communication method using EELBRP without energy
balancing procedure shows similar energy consumption disregarding threshold values because
EELBRP without energy balancing procedure has no option of selecting energy threshold values.
Residual Energy Distribution in proposed energy-balance 2-Hop & 1-Hop Mixed Method using 3D Surf
90
95
Total Energy Consumption
90
85
80
85
75
70
65
80
60
55
50
10
75
8
10
6
8
6
4
4
2
Nodes Y Index
70
2
0
0
Nodes X Index
Figure 10. Residual energy of each node using DSAP method
The performance of proposed EELBRP algorithm is also compared with the existing
benchmarked DSAP routing algorithm, because DSAP also directional and concerned about
stationary network topologies like EELBRP. Following 1-hop communication and using same
simulation scenario of EELBRP simulation study, the residual energy graph is presented in figure
10. The figure shows that DSAP balancing residual energy distribution between 20 to 89 Joules
and the total energy consumption is 4612.215061 Joules, whereas EELBRP balanced energy
between 27 to 95 and consumes 4228.360266 joules of energy shown in figure 5.
Figure 11. Residual energy graph of power-aware DSAP method
The main cause behind the lower performance of DSAP is the weakness in determination of
directional values (DV) i.e considering networks connection similar like wired networks rather
than using the broadcasting nature of wireless networks effectively. Conversely, EELBRP
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Computer Science & Information Technology (CS & IT)
determine the logical distance from destination node to feasible forwarder nodes and select the
best forwarder to forward data packets towards the destination node.
The performance of power-aware DSAP is also presented in figure 11. The residual energy
distribution the nodes of the wireless sensor networks following power-aware DSAP is 50 to 83
and total energy consumption is 4978.735009 Joules. On the other hand, the proposed EELBRP
with energy balancing procedure keeps lower bound of residual energy to 65 and upper bound to
92, so energy is more balanced in EELBRP and it enhances the network lifetime as well while
maintaining less energy consumption 4660.138730 Joules than power-aware DSAP.
6. CONCLUSIONS
Development of energy aware and energy balanced routing protocol for stationary wireless sensor
networks is the major significant contribution of this study. Considering the ability of dynamic
energy changing capability of sensor nodes, the presented routing protocol is simulated in 1-hop,
2-hop and “2-hop & 1-hop combine” communication method. The proposed EELBRP shows
improved performance by accepting and combining with energy balancing and energy efficiency
perspectives. As the proposed routing protocol is directional, the use of directional antenna
surely reduces the energy consumption of the network in a significant rate.
ACKNOWLEDGEMENTS
This work has been funded by the BK21+ program of the National Research Foundation (NRF) of
Korea.
REFERENCES
[1]
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15. Computer Science & Information Technology (CS & IT)
AUTHORS
*Corresponding Author:
ChongGun Kim received the B.E and the M.E degree in Electronic Engineering from
YeungNam University, Korea in 1981 and 1987 respectively. He received Ph.D degree
in Computer Science and Information Mathematics from University of ElectroCommunications, Tokyo, Japan, in 1991. He has been serving as a Professor at the
Department of Computer Engineering, Yeungnam University since March 1991. In his
doctoral work, he was engaged in research on load balancing of distributed computing
systems. He was a visiting scholar of Virginia Tech., USA and UCSC, USA in 1996 and
2003. His current research interests include Computer Networks, Wireless Sensor
Networks, Network Security, and Distributed Computing Systems.
Alghanmi Ali Omar received the B.S. degree in Computer Science from Kyung Hee
University, Korea in 2012. He received King Abdullah Scholarship from Riyadh, Saudi
Arabia for his Bachelor studies in Computer Science. Currently, he is pursuing his
master degree in Computer Engineering at Yeungnam University in Korea. He also
received King Abdullah Scholarship for his Master studies in Computer Engineering.
His areas of research interests include Wireless Sensor Networks, Network Security,
Information Security, and Energy Balancing Mechanism.
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