1. PROJECT REPORT ON WIRELESS SENSOR NETWORK
Submitted By
RAMESH VERMA
University Roll no-09165001058
ANIL KUMAR
University Roll no-16500110066
PRAVIND KUMAR
University Roll no-09165001021
B.TECH(Computer Science & Engineering)
CALCUTTA INSTITUTE OF ENGINEERING & MANAGEMENT
24/1A , CHANDI GHOSH ROAD, KOLKATA-700040

2. ACKNOWLEDGEMENT
The satisfaction that accompanies the successful completion of any task
would be incomplete without the mention of people whose ceaseless
cooperation made it possible, whose constant guidance and encouragement
crown all effort with success. So, I acknowledge all those whose guidance
and encouragement has made successful in winding up this. I owe a huge
debt of thanks to a large number of people without whom none of this
would have been possible.
we are grateful to our project guide Mrs. Moumita Mallick for the
guidance, inspiration and constructive suggestion that helped us in the
preparation of this project. We are also thankful to all our respected faculty
members of CSE department for valuable suggestions and enthusiastic
interest during the entire process of seminar.
I also thank our friends who have helped in successful completion of the
project.

3. CALCUTTA INSTITUTE OF
ENGINEERING & MANAGEMENT
24/1A ,CHANDI GHOSH ROAD, KOLKATA-700040
CERTIFICATE
This is to certify that Ramesh Verma, Pravind Kumar and Anil Kumar
students of Calcutta Institute of Engineering and Management
24/1A, Chandi Ghosh Road, Kolkata-700040 Under West Bengal
University of Technology have successfully completed a project on
“WIRELESS SENSOR NETWORKS” in 8th semester at Department of
Computer Science & Engineering in the year 2012-2013.
The results embodied in this project report have not been submitted
to any other University or Institute for the award of any Degree or
Diploma.
………………………………………… …………………………………………
Mr. Abhijeet Mitra Ms. Moumita Mallick
(H.O.D.) Computer Science & Engineering Department
Computer Science & Engineering Department

4. ABSTRACT
Wireless sensor network consists of widely dispersed very small
sensors that have limited processing power and energy
resources. The development of wireless sensor networks was
motivated by military applications such as battlefield
surveillance; today such networks are used in many industrial
and consumer applications, such as industrial process
monitoring and control, machine health monitoring, and so on.
It is very important to have an optimal network in order to use
its processing power at maximum. This paper is based on the
LEACH (Low Energy Adaptive Clustering Hierarchy) which is
one of the routing protocol under hierarchical routing
topologies in wireless sensor networks. The basic steps of leach
protocol along with some of its disadvantages . Finally we have
proposed an algorithm to overcome energy problem in sensor
nodes. The proposed protocol adds feature to LEACH to
reduce consumption of network resource in each rounds.

5. CONTENTS
INTRODUCTION
NETWORK DESIGN OBJECTIVES
ROUTING PROTOCOLS
TYPES OF ROUTING PROTOCOL
1. Location Based Protocol
2. Data Centric Based Protocol
3. Hierarchical Based Protocols
4. Mobility Based Protocols
5. Multipath Based Protocols
6. QOS Based protocols
LEACH(Low Energy Adaptive Clustering Hierarchical) PROTOCOL
1. Design
2. Set-up phase
3. Steady state phase
4. weakness
DECSA(Distance-Energy Cluster Structure Algorithm)
1. Algorithm
2. Initialisation stage
3. Stable working stage
CONCLUSION
REFERENCES

6. INTRODUCTION
Wireless sensor network consist of many widely distributed sensors, which are
used to monitor various kinds ambient conditions like temperature , humidity,
etc and then transform them into electric signal. A sensor is equipped with a
radio transceiver, a small microcontroller, and an energy source, usually a
battery. Usually sensors are physically small and expensive. Small sensor are
not as reliable as more expensive macrosensors, but small size and small cost of
an individual sensor, allow production and deployment in large numbers. A
wireless sensor network contains hundreds or thousands of these sensors
devices that have that have ability to communicate either directly to the base
station or among each other. The nodes in WSNs are usually battery operated
sensing devices with limited energy resources and replacing and replenishing
the batteries is usually is not an option. The energy efficiency is one of the most
designing power efficient protocol is critical for prolonging the lifetime.
Usually, sensor nodes are scattered in the sensing field, being the area where we
want to monitor some ambient conditions. Sensor nodes have to coordinate
among themselves to get information about the physical environment . The
information collected by sensor nodes is routed to the base station either
directly or through other sensor nodes. The base station is a fixed node or
mobile node, which is capable node to connect the sensor node to an
infrastructure networks or to the internet where the user can access and process
data. The large number of nodes and their random placement in space offers
great redundancy in data transmission.
Consequently WSN are generally adaptive networks that use data aggregation
and hierarchy to reduce energy consumption. WSN creates a local network
hierarchy on one or more levels represented by nodes chosen by certain criteria
that are aggregating and sending data to a central base station(BS).
Communication is mostly from node to BS, the BS sends requests to obtain data
from nodes but not the answer of a particular node is important, the area of origin
is. All data is aggregated by the cluster-head before reaching the BS.

7. NETWORK DESIGN OBJECTIVES
Most sensor networks are application specific and have different application
requirements. Thus, all or part of the following main design objectives is
considered in the design of sensor networks:
Small node size: Since sensor nodes are usually deployed in a harsh or hostile
environment in large numbers, reducing node size can facilitate node
deployment. It will also reduce the power consumption and cost of sensor
nodes.
Low node cost: Since sensor nodes are usually deployed in a harsh or hostile
environment in large numbers and cannot be reused, reducing cost of sensor
nodes is important and will result into the cost reduction of whole network.
Low power consumption: Since sensor nodes are powered by battery and it is
often very difficult or even impossible to charge or recharge their batteries, it is
crucial to reduce the power consumption of sensor nodes so that the lifetime of
the sensor nodes, as well as the whole network is prolonged.
Scalability: Since the number sensor nodes in sensor networks are in the order
of tens, hundreds, or thousands, network protocols designed for sensor networks
should be scalable to different network sizes.
Reliability: Network protocols designed for sensor networks must provide error
control and correction mechanisms to ensure reliable data delivery over noisy,
error-prone, and time-varying wireless channels.
Self-configurability: In sensor networks, once deployed, sensor nodes should
be able to autonomously organize themselves into a communication network
and reconfigure their connectivity in the event of topology changes and node
failures.
Adaptability: In sensor networks, a node may fail, join, or move, which would
result in changes in node density and network topology. Thus, network
protocols designed for sensor networks should be adaptive to such density and
topology changes.
Channel utilization: Since sensor networks have limited bandwidth resources,
communication protocols designed for sensor networks should efficiently make
use of the bandwidth to improve channel utilization.
Fault tolerance: Sensor nodes are prone to failures due to harsh deployment
environments and unattended operations. Thus, sensor nodes should be fault
tolerant and have the abilities of self testing, self-calibrating, self-repairing, and
self-recovering.

8. Security: A sensor network should introduce effective security mechanisms to
prevent the data information in the network or a sensor node from unauthorized
access or malicious attacks.
TYPES OF ROUTING PROTOCOLS
CATEGORY PROTOCOLS
Location-based Protocols MECN, SMECN, GAF, GEAR, Span,
TBF,BVGF, GeRaF
Data-centric protocols SPIN, Directed Diffusion, Rumor
Routing, COUGAR,ACQUIRE, EAD,
Information-Directed Routing,
Gradient-Based Routing, Energy-
aware Routing, Information-Directed
Routing, Quorum-Based Information
Dissemination, Home Agent Based
Information Dissemination
Hierarchical based protocols LEACH, PEGASIS, HEED, TEEN,
APTEEN
Mobility-based protocols SEAD, TTDD, Joint Mobility and
Routing, Data MULES, Dynamic
Proxy Tree-Base Data Dissemination
Multipath-based protocols Sensor-Disjoint Multipath, Braided
Multipath, N-to-1Multipath Discovery
Heterogeneity-based protocols IDSQ, CADR, CHR
QOS-based protocols SAR, SPEED, Energy-aware routing
LOCATION -BASED PROTOCOLS
In location-based protocols, sensor nodes are addressed by means of their
locations. Location information for sensor nodes is required for sensor networks
by most of the routing protocols to calculate the distance between two particular
nodes so that energy consumption can be estimated. We present a sample of
location-aware routing protocols proposed for WSNs.
Data centric based protocols
Data -centric protocols differ from traditional address-centric protocols in the
manner that the data is sent from source sensors to the sink. In address-centric
protocols, each source sensor that has the appropriate data responds by sending
its data to the sink independently of all other sensors. However, in data-centric
protocols, when the source sensors send their data to the sink, intermediate

9. sensors can perform some form of aggregation on the data originating from
multiple source sensors and send the aggregated data toward the sink. This
process can result in energy savings because of less transmission required to
send the data from the sources to the sink.
Hierarchical Protocols
Hierarchical or cluster-based routing, originally proposed in wireless networks,
are well-known techniques with special advantages related to scalability and
efficient communication. It is based on clustering of sensor nodes. Clustering is
an energy-efficient communication protocol that can be used by the sensors to
report their sensed data to the sink. In this section, we describe a sample of
layered protocols in which a network is composed of several clumps (or
clusters) of sensors. Each clump is managed by a special node, called cluster
head, which is responsible for coordinating the data transmission activities of all
sensors in its clump.
Multipath-based Protocols
In this routing protocols we use multiple paths rather than a single path in order
to enhance the network performance. The fault tolerance (resilience) of a
protocol can be resolved here. There is always an alternate path exists between a
source and a destination when the primary path fails. This can be increased by
maintaining multiple paths between the source and the destination at the
expense of an increased energy consumption and traffic generation. These
alternate paths are kept alive by sending periodic messages. Hence, network
reliability can be increased at the expense of increased overhead of maintaining
the alternate paths.
Heterogeneity-based ProtocolsIn heterogeneity sensor network architecture,
there are two types of sensors namely line-powered sensors which have no
energy constraint, and the battery-powered sensors having limited lifetime, and
hence should use their available energy efficiently by minimizing their potential
of data communication and computation. .
QoS-based routing : In QoS-based routing protocols, the network has to
balance between energy consumption and data quality. In particular, the
network has to satisfy certain QoS metrics, e.g., delay, energy, bandwidth, etc.
when delivering data to the BS.

10. LEACH(Low Energy Adaptive Clustering Hierarchy)
Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol for sensor
networks is proposed by W. R.Heinzelman et.al which minimizes energy
dissipation in sensor networks. It is very famous hierarchical routing algorithms
for sensor networks which make clusters of the sensor nodes based on the
received signal strength. The 5% of the total number of nodes becomes the
cluster head which act as router to the sink. Energy consumption is less as
transmission will only be done by cluster head.
Design: LEACH organizes nodes into clusters with one node from each cluster
serving as a cluster-head (CH) shown in figure . It randomly selects some
predetermined number of nodes as cluster heads. Cluster heads then advertise
themselves and other nodes join one of those cluster heads whose signal they
found strongest(i.e. the CH which is nearest to them)
.
Operation: LEACH operation is broken into rounds, with each round having a
set-up phase and a steady state phase.
Set-up phase: During this phase, each node decides whether or not to become a
cluster head (CH) for the current round. This decision is based on choosing a
random number between 0 and 1, if number is less than a threshold T(s), the
node become a cluster head for the current round.
The threshold is defined as follows [1]:
T(s) =p/1-p(r mod (1/p)) if s €G
Where p is the desired percentage of cluster heads (e.g.0.05), r is = the current
round, and G is the set of nodes that have not been cluster heads in the last 1/p
rounds. The cluster head node sets up a TDMA schedule and transmits this
schedule to all the nodes in its cluster, completing the setup phase which is then
followed by a steady-state operation.

11. Flow chart of the Set-up phase of the LEACH Protocol
Steady-state phase: each cluster-head waits to receive data from all nodes in its
cluster and then sends the aggregated or compressed result back to a BS.

12. Weaknesses: Clustering is a good approach which, if implemented properly,
can lead to energy efficient networking in WSNs. Despite the significant overall
energy savings, however, the assumptions made by the protocol raise a number
of issues as :
LEACH assumes that all nodes can communicate with each other and are able
to reach the sink (therefore, it is only suitable for small size networks), LEACH
assumes that all nodes have data to send and so assign a time slot for a node
even though some nodes might not have data to transmit, LEACH assumes that
all nearby nodes have correlated data which is not always true, LEACH requires
that all nodes are continuously listening ( this is not realistic in a random
distribution of the sensor nodes, for example, where cluster-heads would be
located at the edge of the network), there is no mechanism to ensure that the
elected cluster heads will be uniformly distributed over the network (hence,
there is the possibility that all cluster heads will be
concentrated in one part of the network), periodic dynamic clustering carries
significant overhead which may off-set energy gains derived by the clustering
option.
RELATED WORK
In this research, we assume that set of sensor nodes are randomly deployed in
the square field to continuously monitor the phenomenon under inspection. We
know that in LEACH algorithm, each node randomly decides to become a
cluster head(CH).Once a node decides to become a cluster head ,it aggregates
the data received from various nodes inside the cluster and send it to the base
station. However, completely independent random cluster head select can't
guarantee the number and the distribution of cluster head in each round. It may
selects a node which is far away from base station and has low residual
energy to become the cluster head, which will cause the uneven energy loss of
nodes in the network and form monitoring blind spot, even will influence the
whole performance of the network. In order to improve this kind of situation,
different from LEACH, in this paper, we will use a three level hierarchy
structure network model, which divides the nodes into four categories: Base
Station(BS) , Base Station Cluster head(BCH), ordinary cluster head node (CH),
and common sensor node (SN). Following figure shows the network model of
DECSA algorithm.

13. Figure. Three level hierarchy structure network model of DECSA
DECSA Algorithm
In this section, we describe our proposed clustering algorithm
DECSA(Distance-Energy Cluster Structure Algorithm). DECSA is a distributed
competitive unequal clustering algorithm, it considers both the distance and
residual energy information of nodes. Similar to that of LEACH, DECSA
protocol continues by round and each round can be divided into initialization
stage and stable working stage. In order to minimize energy consumption, the
stable working stage should be greatly longer than the initialization stage.
Initialization stage
In the initialization stage, cluster head is elected and TDMA time slots are
distributed to ordinary member nodes by the cluster head. Within a given time
slot, ordinary member nodes are joined an appropriate cluster. The process of
cluster head select consists of following 2 parts: election of ordinary cluster
head node (CH) and election of Base Station Cluster head (BCH).In the part of
election CH, the main difference between LEACH and DECAS in this part is
DECSA employs both residual energy and distance parameter. First, each
sensor node generates a random number between 0 and 1.If the random
number for a particular node is smaller than the predefined threshold T, then
that sensor node becomes the first round cluster-head, we call it false-cluster-
head there. And then all the nodes in the cluster are respectively calculate their
k(i), and compared it with their current false-cluster-head. If it is greater than
the false-cluster-head’s k(i), then announced that he become the CH of this
cluster. If it is smaller, then the false –cluster- head become the CH. Thus, the
election of cluster head considers both the nodes’ energy consumption and the
communication between the network, comparing the difference of k(i), let
the high residual energy, high efficiency of communication node has the bigger
probability to be elected as CH, it will prolong the lifetime of the network.

14. K(i)=En(i)/d0(i)
Where k(i)is the threshold of elect CH , En(i) is the residual energy of node i,
d0(i) is the average distance between node i with all other nodes in the same
cluster.
After the election of cluster-head, in the part of election base-station-cluster-
head, we use threshold TBCH to select which CH will become the BCH.
We select those CH whose TBCH (i) are larger than the predefined threshold
TBCH0 as the base-station cluster-head( BCH). The rest of the cluster heads as
ordinary cluster head nodes CH. We define TBCH(i) as follow:
TBCH(I)=(En(i)/E0)+(En(i)/d(i))
where En(i) is the current residual energy of node i, E0 is the initial energy of
node in the network, d(i) is the distance between node i with base station.
Stable working stage
In the stable working stage, base station broadcasts the message to the entire
network. After received the messages, according to the different value of TBCH
(i) , base-station-cluster-head select the maximum TBCH cluster-head as its
next hop ,and the rest hop can be selected in the same manner until all of the
cluster head nodes are connected ,forming a complete communication path. In
order to reduce the direct communication between the base station and the
cluster-head which is far away from the base station and has low residual
energy. Common nodes (SN) in the cluster will transmit data packet to their
closest cluster-head, then cluster-head will collect and fusion those data and
transmit them to the base-station cluster- head, rather than transmit them to the
base station directly. And then, base-station-cluster-head will communicate with
the base station. Avoiding the narrowness of the election of base-station cluster
head, balance the consumption of energy and data transmission, the value of
threshold TBCH0 should be dynamic changed according to the real-time
network’s state, thus could guarantee the base-station-cluster head of the whole
network be elected is the most appropriate. The value of TBCH0 should
between the average TBCH and the maximum TBCH in network .Of course, the
difference of the TBCH0 threshold will cause different influence the
performance of the network directly.

15. The graph below shows the comparison of DEGSC and LEACH
Residual energy relationship of nodes between DECSA and LEACH
Above figure shows the residual energy consumption of nodes between
DECSA and LEACH. It clearly depicts that DECSA has a better performance
than LEACH in terms of energy consumption. The number of remain alive node
in LEACH algorithm is far more less than the number in DECSA algorithm, it
reduces about 40% of the energy consumption.
CONCLUSION
In this paper, we proposed a cluster routing algorithm DECSA considering both
the distance and residual energy of nodes, improved the process of cluster head
election and the process of data transmission of network. This makes the node
with more residual energy and has high polymerization degree in the network
has greater probability to become cluster heads. In the stable working stage, it
reduces the adverse effect on the energy consumption of the cluster head,
resulting from the non-uniform distribution of nodes in network and avoids the
direct communication between the base station and the cluster head, which may
has low energy and far away from base station. The results of simulation
indicate that the improved algorithm effectively balances the energy
consumption, prolongs 31% of the lifetime, reduces 40% of the energy
consumption and has a better performance than the original LEACH protocol.

16. REFERENCES:
[1] Hierarchical Cluster-based Routing in Wireless Sensor Networks Sajid
Hussain and Abdul W. Matin Jodrey School of Computer Science, Acadia
University Wolfville, Nova Scotia, Canada{Sajid.Hussain,
073720m}@acadiau.ca
[2] An Enhanced Cluster Based Routing Algorithm for Wireless Sensor
Networks Uk-Pyo Han*, Sang-Eon Park**, Seung-Nam Kim*, Young-Jun
Chung* * Computer Science Department, Kangwon National University,
Chunchon, Korea **Computer Science Department, California State
Polytechnic University, Pomona, USA {mania2k, colors95,
ychung}@mail.kangwon.ac.kr, sangeonpark@csupomona.edu
[3] Delay Tolerant Cluster Based Routing For Wireless Sensor Networks
Saranya. N1 and Mr. S.V. Manisekaran2 M. Tech -IT , Anna University of
Technology, Coimbatore, saranit45@gmail.com Assistant Professor-IT, Anna
University of Technology, Coimbatore, svmanisekaran@yahoo.co.in
[4] JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 26,
2159-2171 (2010)
2159 An Energy-Aware, Cluster-Based Routing Algorithm for Wireless Sensor
Networks
JYH-HUEI CHANG Department of Computer Science National Chiao Tung
University Hsinchu, 300 Taiwan