A Sensor Utilization Scheme for the Coverage Guarantee Criteria in Wireless Sensor Network

IEEE Title:

A Sensor Utilization Scheme for the Coverage Guarantee Criteria in Wireless Sensor Network

Modified Title:

Random Coverage of Cluster in WSN using Energy aware routing protocol

Objective of the project:

To improve the lifetime and to maximize the energy consumption in wireless sensor network

Abstract

A cluster-based wireless sensor network (WSN) where each sensor node takes turn to be

cluster head. The main function of the cluster head is to oversee the communication within and

between clusters while the remaining sensor nodes are involved in sensing of the surrounding

environment. We address the sensor utilization problem where non-cluster head nodes in a

cluster make decision to whether to be active and join the sensing process. The decision is based

on the remaining energy of a sensor, and a performance criterion. Here, we use the probability

that given point in the cluster is covered by at least N sensors. By using a probabilistic model, it

can be analytically calculated. Since only the high energy and necessary sensors are used, the

Ambit lick Solutions
Mail Id: Ambitlick@gmail.com , Ambitlicksolutions@gmail.Com

energy consumption can be greatly decreased. Using energy aware routing protocol overall

energy usage and lifetime can be improved.

Literature review:

1. A Survey on Routing Protocols and Challenge of Holes in Wireless Sensor Networks:

Extensive usage of wireless sensor networks is the reason of development of many

routing protocols. In this paper, the working of few routing protocols has been discussed, which

are energy aware and some of them also provide reliability in data transmission. Performance of

various protocols has been presented through simulation results that have been reported by

leading researchers for the purpose of their comparison. The challenges faced by wireless sensor

networks are also discussed in the paper. These challenges (i.e. coverage holes, routing holes,

jamming holes, black/sink holes and worm holes) effect the performance of routing protocols.

2. An Energy Aware Routing Protocol with Sleep Scheduling for Wireless Sensor

Networks:

Wireless Sensor Networks (WSNs) consist of a large number of small and low cost

sensor nodes powered by small batteries and equipped with various sensing devices. Usually, for

many applications, once a WSN is deployed, probably in an inhospitable terrain, it is expected to

gather the required data for quite some time, say for years. Since each sensor node has limited

energy, these nodes are usually put to sleep to conserve energy, and this helps to prolong the


network lifetime. There are two major approaches to sleep scheduling of sensor nodes, viz. (i)

random (ii) synchronized. Any sleep scheduling scheme has to ensure that data can always be

routed from source to sink. In this paper, we propose a novel approach for sleep scheduling of

sensor nodes using a tree and an energy aware routing protocol which is integrated with the

proposed sleep scheduling scheme. The tree is rooted at the sink node. The internal nodes of the

tree remain awake and the leaf nodes are made to sleep. This provides an assured path from any

node to the sink node. The tree is periodically reconstructed considering the remaining energy of

each node with a view to balance energy consumption of nodes, and removes any failed nodes

from the tree. The proposed approach also considerably reduces average energy consumption

rate of each node as we are able to put more number of nodes to sleep in comparison to other

approaches. Additional fault-tolerance is provided by keeping two paths from each node towards

the sink. Extensive simulation studies of the proposed routing protocol has been carried out using

Castalia simulator, and its performance has been compared with that of a routing protocol, called

GSP, which incorporates sleep scheduling using random approach. The simulation results show

that the proposed approach has longer network lifetime in comparison to that provided by GSP,

and the energy consumption of nodes is also balanced.


3. A QoS-geographic and energy aware routing protocol for Wireless Sensor Networks:

Recent technological advances in miniaturization and wireless communication have made

Wireless Sensor Networks an active research field. The increasing number of multimedia and

real-time applications for Wireless Sensor Networks has led to a growing interest in Quality of

Service for this category of networks. In this paper, we propose a QoS-geographic and energy

aware routing protocol for Wireless Sensor Networks. The proposed protocol performs

admission control, accounts for bandwidth requirements and considers the sensors residual

energy while taking routing decisions. The protocol also optimizes the delay of carried flows by

adopting a selective forwarding approach based on sensor location.

4. Distributed Deployment Schemes for Mobile Wireless Sensor Networks to Ensure

Multilevel Coverage:

One of the research issues in wireless sensor networks (WSNs) is how to efficiently

deploy sensors to cover an area. In this paper, we solve the k-coverage sensor deployment

problem to achieve multi-level coverage of an area I. We consider two sub-problems: k-coverage

placement and distributed dispatch problems. The placement problem asks how to determine the

minimum number of sensors required and their locations in I to guarantee that I is k-covered and

the network is connected; the dispatch problem asks how to schedule mobile sensors to move to

the designated locations according to the result computed by the placement strategy such that the

energy consumption due to movement is minimized. Our solutions to the placement problem


consider both the binary and probabilistic sensing models, and allow an arbitrary relationship

between the communication distance and sensing distance of sensors. For the dispatch problem,

we propose a competition-based and a pattern-based schemes. The former allows mobile sensors

to bid for their closest locations, while the latter allows sensors to derive the target locations on

their own. Our proposed schemes are efficient in terms of the number of sensors required and are

distributed in nature. Simulation results are presented to verify their effectiveness.

5. Random coverage with guaranteed connectivity: joint scheduling for wireless sensor

networks:

Sensor scheduling plays a critical role for energy efficiency of wireless sensor networks.

Traditional methods for sensor scheduling use either sensing coverage or network connectivity,

but rarely both. In this paper, we deal with a challenging task: without accurate location

information, how do we schedule sensor nodes to save energy and meet both constraints of

sensing coverage and network connectivity? Our approach utilizes an integrated method that

provides statistical sensing coverage and guaranteed network connectivity. We use random

scheduling for sensing coverage and then turn on extra sensor nodes, if necessary, for network

connectivity. Our method is totally distributed, is able to dynamically adjust sensing coverage

with guaranteed network connectivity, and is resilient to time asynchrony. We present analytical

results to disclose the relationship among node density, scheduling parameters, coverage quality,


detection probability, and detection delay. Analytical and simulation results demonstrate the

effectiveness of our joint scheduling method

SYSTEM ANALYSES:

Existing System:

Source Dependent Broadcasting Protocols

Proposed System:

A broadcasting node uses existing source dependent broadcasting protocols to select a set

of forwarding nodes to cover all its 2-hop neighbors. Then, it adjusts its transmission

power to reach its furthest forwarding node.

The node determines whether its current forwarding nodes as well as transmission power

are able to cover all its immediate neighbors. If yes, it continues to broadcast the

message. Otherwise, it attempts to find additional forwarding nodes to reach those

uncovered neighbors or simply extends its current transmission power to reach the

furthest uncovered neighbor.

Variable Transmission Power Protocols.

Power law model


o
Precv = Ptx / rn

Enhanced PABLO

Enhanced Inside-Out Power Adaptive Approach (E-INOP)

Algorithm :

Dominant Pruning (DP) Protocol :

The earliest deterministic broadcasting protocols. A node that receives a broadcast

message from source node and selects a minimum number of forwarding nodes from Network to

cover all nodes. The greedy algorithm is adopted to select forwarding nodes from the network to

cover all nodes.

1) Node v establishes the set B(u; v) and U(u; v) using

N(N(v)), N(u), and N(v):

U(u; v) = N(N(v)) �N(u) � N(v)

B(u; v) = N(v) � N(u)


2) Node v then executes the greedy algorithm to select forwarding nodes from B(u; v) to cover

all nodes in U(u; v).

Total Dominant Pruning (TDP) Protocol

TDP is more effective than DP in reducing redundant broadcasting but it incurs

additional overhead in piggybacking each data message with a list of 2-hop neighbors of the

senders.

The TDP algorithm is:


N(N(v)) and N(N(u)):

U(u; v) = N(N(v)) �N(N(u))

B(u; v) = N(v) �N(u)

2) Node v then executes the greedy algorithm to select forwarding nodes from B(u; v) to

cover all nodes in U(u; v).

Partial Dominant Pruning (PDP) Protocol

PDP algorithm does not require additional overhead, like TDP. Instead of just excluding

nodes in network. the 2-hop neighbor set to be covered.


The PDP algorithm is summarized below:


N(N(v)), N(u), N(v), and N(N(u) N(v)):

U(u; v) = N(N(v))�N(u)�N(v)�N(N(u)N(v))

B(u; v) = N(v) � N(u)

2) Node v then executes the greedy algorithm to select forwarding nodes from B(u; v) to cover

all nodes in U(u; v).


A Sensor Utilization Scheme for the Coverage Guarantee Criteria in Wireless Sensor Network

Recommandé

Recommandé

Contenu connexe

Plus de ambitlick

Plus de ambitlick (20)

Dernier

Dernier (20)

A Sensor Utilization Scheme for the Coverage Guarantee Criteria in Wireless Sensor Network