This document discusses the energy conservation strategies in wireless sensor networks (WSNs) through a cluster-based broadcasting approach called 3B. It introduces a new algorithm that constructs a backbone using multipoint relaying (MPR) and optimizes broadcasting to minimize energy consumption compared to existing methods. The proposed system enhances network efficiency by allowing nodes to adjust their transmission based on remaining energy, resulting in prolonged network lifespan and reduced energy usage.

1. International Journal of Research in Engineering and Science (IJRES)
ISSN (Online): 2320-9364, ISSN (Print): 2320-9356
www.ijres.org Volume 2 Issue 2 ǁ Feb. 2014 ǁ PP.32-37
www.ijres.org 32 | Page
Energy Conservation in Wireless Sensor Networks Using Cluster-
Based Approach
M. Senthil Kumar1
, P.M. Vishnu Narayanan2
, S. Kalyani3
1
Assistant Professor, 2
PG Scholar, 3
Professor and Head
Department of ECE, Ranganathan Engineering College, Coimbatore, Tamil Nadu, India.
Abstract — In a wireless networking environment, the network is comprised of sensor nodes and backbones
are subsets of sensors or actuators that suffice for performing basic data communication operations. They are
applied for energy efficient broadcasting. In a broadcasting (also known as data dissemination) task, a message
is to be sent from one node, which could be a sink or an actuator, to all the sensors or all the actuators in the
network. The goal is to minimize the number of rebroadcasts while attempting to deliver messages to all
sensors or actuators. Neighbor detection and route discovery algorithms that consider a realistic physical layer
are described. An adaptive broadcasting protocol without parameters s ui t a b l e for delay tolerant networks is
further discussed. In existing solutions for minimal energy broadcasting problem, nodes can adjust their
transmission powers. Wireless Sensor Networks (WSNs) are sets of many sensors that gather data and
collaborate together. So, the procedures of broadcast or multicast are more important than traditional point-to-
point communication in computer network. This paper focuses on broadcasting in structured WSNs. In such a
kind, the procedure of network communications is easier than in unstructured WSNs. Thus, it will make an
overview of Multi Point Relay (MPR) to show its weakness. Then define a cluster-based architecture for WSNs
which is constructed using MPR. Next, provide a new broadcast algorithm based on the previous cluster
architecture called 3B (Backbone Based Broadcasting). By the end, an illustration of 3B shows that it
minimizes the energy consumption for accomplishing broadcast compared to MPR.
Keywords — Wireless Sensor Networks, Backbone Based Broadcasting, MPR.
I. INTRODUCTION
WSNs have attracted the attention of the research community during the last few years, due to their
low cost, their huge capabilities of collecting data and their various fields of applications i.e. health care,
surveillance, environment and military [1, 2]. The most important disadvantage of WSN is their limit in
energy, so many methods, algorithms and protocols were introduced and developed i n taking consideration
of this constraint. Since, WSNs are considered as ad-hoc networks with other characteristics, many algorithms
and methods of ad- hoc n e t wo r k s c o ul d be reused and reconfigured according to the WSN
specificity. Broadcasting is usually used in WSNs. So, many m e t h o d s a n d broadcasti ng he urist ics
were applied in unstructured WSNs, especially algorithms based on relaying like MPR [3] or RDS-MPR [4].
These methods decrease the consumed energy and avoid broadcast storm problem caused by flooding. For
structured WSNs, several cluster-based architectures have been proposed recently. They transform usual WSNs
to WSNs composed by a set of clusters connected by a backbone [16, 17]. To broadcast a packet of data over
cluster-based WSNs, the data will be first sent in the backbone, then in intra-clusters.
This paper combines the two types of broadcasting methods. Thus, it defines a new algorithm which is
executed in two stages: It begins with constructing the backbone using MPR. Then, it ends by using this
backbone to broadcast packets from sink node. The remainder of this paper is organized as follows: section 2
outlines the most known broadcasting methods and algorithms which have been proposed recently over
unstructured and structured WSNs. In section 3, make an overview of MPR heuristics proposed in [3], and
illustrate the weaknesses of this method in some kinds of WSNs. In section 4, defines a new cluster-based
architecture for WSNs and carry out an example of application of our new clustering heuristic over a sensor
networks. In addition, it provides a new broadcasting algorithm. The illustration of this new algorithm shows
that it minimizes the energy consumption to accomplish broadcasting compared to MPR.
II. RELATED WORK
The related work contains data aggregation and dissemination, clustering, broadcasting, routing and
energy efficiency of wireless sensor networks. Most existing studies use either active or passive measurements
for this purpose. Data aggregation in wireless sensor networks is employed to reduce the communication
overhead and prolong the network lifetime. However, an adversary may compromise some sensor nodes, and
use them to forge false values as the aggregation result. Previous secure data aggregation schemes have tackled
this problem from different angles. The goal of those algorithms is to ensure that the Base Station (BS)

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does not accept any forged aggregation results. But none of them have tried to detect the nodes that inject into
the network bogus aggregation results. Moreover, most of them usually have a communication overhead that is
(at best) logarithmic per node. In this paper, Y. Xiang et al. (ICA3PP 2011, Part I, LNCS 7016, pp. 2–13,
2011) proposed a secure and energy-efficient data aggregation scheme that can detect the malicious nodes with
a constant per node communication overhead. In their solution, all aggregation results are signed with the
private keys of the aggregators so that they cannot be altered by others [18]. Nodes on each link additionally
use their pair wise shared key for secure communications. Each node receives the aggregation results from its
parent (sent by the parent of its parent) and its siblings (via its parent node), and verifies the aggregation result of
the parent node. Theoretical analysis on energy consumption and communication overhead accords with our
comparison based simulation study over random data aggregation trees.
Central to the cluster based routing protocols is the cluster head (CH) selection procedure that allows
even distribution of energy consumption among the sensors, and therefore prolonging the lifespan of a sensor
network. Sang H. Kang Thinh Nguyen (2012 IEEE) proposed a distributed CH selection algorithm that takes
into account the distances from sensors to a base station that optimally balances the energy consumption
among the sensors. NS-2 simulations show that their proposed scheme out performs existing algorithms in terms
of the average node lifespan and the time to first node death. [20]
Flooding is an elementary tool for information dissemination in a wide range of network scenarios,
such as link state advertisements in wireless multi- hop networks and query propagation in peer-to-peer
networks. Using random graph models, Sergio Crisostomo et.al (IEEE International Conference on Circuits
and Systems for Communications, Shanghai, China, May 2008.) had compared two competing flooding
techniques: multipoint relays and network coding [19]. Their analytical model shows that in case of network
coding, the number of transmissions per source message is asymptotically independent of the number of nodes.
Simulation results yield further insights on the impact of topology on the performance of each flooding
technique, more specifically on the required number of transmissions and the resulting end-to-end delay.
Reuven Cohen and Boris Kapchits (IEEE/ACM Transactions on Networking, Vol. 19, no.1, February
2011) had explained that, in most sensor networks the nodes are static. Nevertheless, node connectivity is
subject to changes because of disruptions in wireless communication, transmission power changes, or loss of
synchronization between neighboring nodes [21]. Hence, even after a sensor is aware of its immediate
neighbors, it must continuously maintain its view, a process called continuous neighbor discovery. In that work
they distinguish between neighbor discovery during sensor network initialization and continuous neighbor
discovery. They focus on the latter and view it as a joint task of all the nodes in every connected segment.
Each sensor employs a simple protocol in a coordinate effort to reduce power consumption without increasing
the time required to detect hidden sensors.
D. Sivaganesan and Dr. R. Venkatesan (International Journal of Ad hoc, Sensor & Ubiquitous
Computing ( IJASUC ) Vol.1, No.2, June 2010) describes that broadcasting is a fundamental service in
Mobile Ad hoc Networks (MANETs). Cluster based approach are proposed in literature to reduce the network
collision, to reduce delay of packet transmission, to reduce the energy consumption and improves the
throughput [22]. They proposed a cluster- based infrastructure is proposed for broadcasting in MANETs. The
backbone of the network takes advantage of the cluster structure and only requires cluster- heads and some
selected gateways to forward the broadcast packet. Each cluster head selects some gateways to forward the
packet when it sends the packet to all the cluster heads in its coverage set. Cluster structures have been
simulated using mobile simulator Glomosim 2.03, which gives better performance to reduce the network
collision, to reduce delay of packet transmission, to reduce the energy consumption and improves the
throughput.
Hassan Raei et al. (Scientific Research and Essays Vol. 6(10), pp. 2154-2163,18 May,2011) had
examined an important characteristic that distinguishes wireless sensor networks (WSNs) from other
distributed systems is their need for energy efficiency because sensors have finite energy reserve. Since there
is no fixed infrastructure or centralized management in WSN, a connected dominating set (CDS) has been
proposed as a virtual backbone. The CDS plays a major role in routing, broadcasting, coverage and activity
scheduling. To reduce the traffic during communication and prolong network lifetime, it is desirable to
construct a minimum CDS (MCDS) [23]. The MCDS problem has been studied intensively in unit disk graph
(UDG), in which the nodes have the same transmission range. They had developed a new timer based energy-
aware distributed algorithm for MCDS problem in disk graph with bidirectional links (DGB), in which nodes
have different transmission ranges, is introduced which has outstanding time and message complexity of
O(n) and constant approximation ratio. Theoretical analysis and simulation results are also presented to verify
their approach’s efficiency.

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III. DESIGN OF 3B SYSTEM
The 3B system combines two types of broadcasting methods. Here defines a new algorithm which is
executed in two stages: It begins with constructing the backbone using MPR. Then, it ends by using this
backbone to broadcast packets from sink node. The illustration of this new algorithm show that it minimizes
the energy consumption to accomplish broadcasting compared to MPR.
Advantage of Proposed System
a. The 3B architecture helps to carry out broadcast and multicast protocols with low complexity.
b. It minimizes the energy consumption to accomplish the broadcasting compared to MPR.
c. Also it reduces the no. of nodes in the field of coverage.
d. The algorithm wakes up or put the nodes into sleeping mode, through predicting the moving track of the
target and it reduces the network energy consumption.
e. In cluster based broadcasting, clusters are linked each other by gateways and every cluster has a special
cluster head.
f. The back bone in such network is composed of root, cluster head, and gateways.
(Fig. 1) Design of 3B System
A. Node Generation
This module is used to create the node information. In a network, a node is a connection point that
is attached to a network, and is capable of sending, receiving, or forwarding information over a
communications channel. In general, a node has programmed or engineered capability, to recognize and process
or forward transmissions to other nodes, Power Monitor – function, that checks remaining energy, runs in
background using a thread. Check If Sink –function, that initiates Cluster algorithm when the node becomes
the sink.
(Fig. 2) A basic MPR Network

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B. Cluster Construction
The cluster architecture construction is based on MPR. The sink node is called root. Every node
chosen as a relay node by MPR will be a cluster head. Next, the rest of nodes will be leaves. If a leaf is
connected to more than one cluster head it will choose the cluster head with maximum remaining energy to be
linked and cut others links. Bellow the algorithm is defined. CC constructs Gc (Vc Ec) according to G (V, E).
Clusters a re linked to each other by special nodes called getaways, a nd e ver y cluster ha s a s p e c i a l
no de called cluster head. In such network, we have found a node called root which is the sink node in most
cases or the first sender node of the packet of data to be broadcasted. The backbone in such network is composed
by root, cluster head, and getaways.
(Fig. 3) The Network of (Fig. 1) after applying MPR Table Symbols and Notations
Algorithm 1: CC: Cluster-Construction
1: id (sink) <- root
2 Vc <- Vc U {root}
3:Vc <- Vc U MPR (G)
4: for all node n in Vc {sink} do
5: id (n) <- ch
6: End for all
7: Temp <- Ø
8: for all node n in GGc and ch in Gc do
9: If (n, ch) G then
10: Temp <- Temp U {ch}
11: End if
12: Choose ch in Temp having the maximum remaining energy
13: id (n) <- leaf
14: Ec <- Ec U (n, ch)
15: Temp <- Ø
16: End for all.
C. Back Bone based Broadcasting
Collect Data – This function collects data from the Black node once cluster formation is over.
Draw Route +Tree Draw– The two functions act together to retrieve useful information from the data
packet. Nodes participating, along with their ID, Color and energy levels are displayed as a list. A tree
representation is shown with Green nodes connecting to the Black node.
Send Data – Broadcast sensed data along with other details. (NodeID+Color+Energy+Seq.number)
Receive Data – Receiver, non-active only if node’s Color is change.
The broadcasting algorithm proposed is based on the previous cluster architecture. In fact, a packet
sent from the root will reach all nodes in the network by the backbone which is consists of root and cluster
heads.
Algorithm 2: 3B: Backbone-Based Broadcasting
1: Applying CC to G.
2: The backbone is consists of root and cluster heads induced by CC.
3: Broadcast the packet form the root over the backbone.

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(Fig. 4) The network after applying the clustering architecture and 3B
IV. CONCLUSION
The aim of the paper is to create a sensor network scenario using Wi-Fi enabled devices that will
work in an energy-efficient manner, to transmit some useful data. In this project, a new broadcast heuristic is
provided. This method is an improvement of MPR broadcasting in term of energy. In fact, it uses relay-based
broadcast to select a backbone in the network. After, it eliminates the links between nodes able to be the source
of losing energy. 3B makes an important amelioration of MPR in term of decreasing total consumed energy to
accomplish broadcasting all over the network. Thus, 3B increases the network lifetime which is a critical
criterion for WSNs. The proposed algorithm selects the backbone members based on the remaining energy.
The nodes with higher remaining energy (means longer lifetime) will be selected as the cluster head. The
proposed algorithm operates only based on the local information of each node; the algorithm combines with the
countdown mechanism to avoid the discovering phase.
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AUTHOR DETAILS
M. Senthil Kumar was born in Ramanathapuram District, Tamil Nadu, India in 1982. He
obtained his B.Sc., M.Sc. and M.Tech. degrees in Electronics in the years 2002, 2004 and
2006 respectively. He has more than 7 years of teaching experience. He has presented more
than 30 research papers in various national and international conferences. He has also
published more than 10 research papers in reputed international journals. He has guided
several UG and PG students for their project work. His area of interest is Energy
Conservation and Optimization Techniques in Wireless Sensor Networks. Currently, he is
with Ranganathan Engineering College, Coimbatore, India, as Assistant Professor in the
Department of Electronics and Communication Engineering.
P.M. Vishnu Narayanan is currently pursuing M.E. in VLSI Design at Ranganathan
Engineering College, Coimbatore, India. He has a total experience of 2 years as Control
Room Operator (Kerala State Electricity Board). His research interests include the area of
Low Power and Testing of VLSI Design.
Prof. S. Kalyani is presently working as Professor and Head of the Department of
Electronics and Communication Engineering in Ranganathan Engineering College,
Coimbatore, India. She has more than 25 years of teaching experience in various
institutions. She has published more than 15 research papers in reputed international
journals. Her area of interests includes testing of VLSI Design.