An Improved Energy Aware Hierarchical Routing Protocol in Wireless Sensor Networks

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(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 9, No. 11, November 2011

An Improved Energy Aware Hierarchical Routing
Protocol In Wireless Sensore Networks

Behzad Homayoufar Sayyed majid mazinani
Department of Technical and Engineering Department of Electrical Engineering
Mashhad Branch, Islamic Azad University Imam Reza University
Mashhad, Iran Mashhad-Iran
BehzadHomayounfar1@gmail.com Mazinani@ieee.org

Abstract—Reducing energy consumption and prolonging network achieved without carefully scheduling the energy utilization. So
lifetime is an important issue in wireless sensor networks. So this one of the very important factors that effect on sensor network
problem has to solve for sensor node energy while meeting the life time is sensor's energies, so the protocol running on
requirements of applications/users. Hierarchical network sensor networks must efficiently reduce the energy
structures have the advantage of providing scalable and resource consumption in order to prolong network lifetime [7]. Data
efficient solutions. In this paper to find an efficient way for saving gathering is a typical operation in many WSN applications, and
energy consumption, we propose an Improved Energy Aware data aggregation in a hierarchical manner is widely used for
Hierarchical Routing Protocol (IERP) that prolong the sensor prolonging network lifetime. Data aggregation can eliminate
network lifetime. IERP introduces a new clustering parameter
data redundancy and reduce the communication load.
for cluster head election, routing tree construction on cluster
Hierarchical mechanisms (especially clustering algorithms) are
heads for sending aggregated data to the base station. We use two
parameters to select cluster heads and construct routing tree on
helpful to reduce data latency and increase network scalability
cluster heads that includes distance from each node (others or [8]. IERP protocol introduce new formula for cluster head
base station) and residual energy of the nodes. We use a simple selection that can better handle homogeneous energy
but efficient approach, namely, intra-cluster coverage to cope circumstances than other clustering algorithms which IERP,
with the area coverage problem. Simulation results in the NS-2 first cluster the network then construct a spanning routing tree
platform demonstrate the longer network lifetime of the IERP over all of the cluster heads. IERP uses two parameters to
than the better-known clustering protocols, ERA and EAP. select heads on tree that includes distance from each node
(others and base station) and residual energy of the nodes. Only
the root node of this tree can communicate with the sink node
by single -hop communication. Because the energy consumed
Keywords-Hierachical; Clustring; Routing Tree; Lifetime for all communications in network can be computed by the free
Network; Residual Energy space model, the energy will be extremely saved and Network
lifetime is prolonged. The rest of this paper is organized as
I. INTRODUCTION follows: In the next section we introduce the related work, in
A typical WSN consists of a number of sensor devices that section 3 we will discuss the proposed algorithm, simulation
collaborate with each other to accomplish a common task (e.g. results and performance evaluation are given in section 4, the
environment monitoring, object tracking, etc.) and report the conclusion is presented in sections 5.
collected data through wireless interface to a sink node. The
areas of applications of WSNs vary from civil, healthcare and II. RELATED WORKS
environmental to military. Examples of applications include In hierarchical networks, nodes are separated to play
target tracking in battlefields[1], habitat monitoring[2],civil different roles, such as CHs and cluster members. The higher
structure monitoring [3], forest fire detection [4] and factory level nodes, cluster heads (CHs), Each CH collects data from
maintenance [5]. the cluster members within its cluster, aggregates the data, and
Wireless sensor networks (WSNs) become an invaluable then transmits the aggregated data to the sink. All of the
research area by providing a connection between the world of hierarchical routing protocols aim at selecting the best CH and
nature and that of computation by digitizing certain useful clustering the nodes into appropriate clusters in order to save
information. In wireless sensor networks, the sensor node energy. The hierarchical clustering protocol may execute
resources are limited in terms of processing capability, wireless reclustering and reselecting of CHs periodically in order to
bandwidth, battery power and storage space, which distribute the load uniformly among the whole network [10].
distinguishes wireless sensor networks from traditional ad hoc By the method of CH selection, the hierarchical routing
networks [6]. In most applications, each sensor node is usually protocols can be classified into two categories: random-
powered by a battery and expected to work for several months selected-CH protocol and well-selected- CH protocol. The
to one year without recharging. Such an expectation cannot be former randomly selects CHs and then rotates the CH task
among all nodes, while the latter carefully selects appropriate

28 http://sites.google.com/site/ijcsis/
ISSN 1947-5500
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 9, No. 11, November 2011
CHs and then gathers nodes under the CHs based on the  The energy of sensor nodes cannot be recharged.
network status [9] and [10]. Energy Residue Aware (ERA)
clustering algorithm is one of energy-aware hierarchical  Sensor nodes are location-aware, i.e. a sensor node can
approaches. It is also improved from LEACH by including the get its location information through other mechanism
communication cost into the clustering. The communication such as GPS or position algorithms.
cost includes residual energy, communication energy from the
CH to the sink and communication energy from the cluster B. Set-up phase
members to the CH. ERA uses the same CH selection scheme At the beginning of each round, each node first estimates its
as LEACH but provides an improved scheme to help non-CH residual energy (Enode-res)j and broadcasts the CH-E_Msg
nodes choose a better CH to join by calculating the clustering within radio range r which contains residual energy and
cost and finding CH according to maximum residual energy distance to base station. Each node receives the CH-E _Msg
[11]. from all neighbours in its cluster range and updates the
In HEED, author introduces a variable known as cluster neighbourhood table, also compute CH-E (cluster head
radius which defines the transmission power to be used for election) using (1).
intra-cluster broadcast [12]. The initial probability for each ( E node  res ) j
node to become a tentative cluster head depends on its residual CH  E 

energy, and final heads are selected according to the intra- dis ( j ) 2
(1  ( ))
cluster communication cost. HEED terminates within a 100
constant number of iterations, and achieves fairly uniform
distribution of cluster heads across the network. In
EAP(Energy-Aware Routing Protocol), a node with a high ratio (ENODE-RES)J can be derived as below:
of residual energy to the average residual energy of all the
neighbour nodes in its cluster range will have a large ( Enode res ) j  Max{( Enode rem ) j  ( EtoOther ) ji } (2)
probability to become the cluster head. This can better handle
heterogeneous energy circumstances than existing clustering j  N ,i  S o
algorithms which elect the cluster head only based on a node’s
own residual energy. After the cluster formation phase, EAP Where, N is the set of nodes , SO is set of other nodes
constructs a spanning tree over the set of cluster heads [13]. within radio range r and (Enode-rem)j indicates the residual
Only the root node of this tree can communicate with the sink energy of node j in the current round as well as (EtoOther)ji
node by single-hop communication. Because the energy indicates the communication energy from node j to other
consumed for all communications in the network can be nodes i within radio range r. Eventually, each node chooses
computed by the free space model, the energy will be (Enode-res) according to maximum residual energy .
extremely saved and thus leading to sensor network longevity
[14]. Value of parameter dis(j) is computed as follow :
l
dis( j )  ( (| Ddb ( j )  Ddb (i) |)  t p  k ) (3)
III. THE PROPOSED ALGORITHM
i 1
In IERP , the role of the cluster head must be rotated among
all sensor nodes. Therefore, the operation of IERP is divided D db is node distance to base station. We assume that
into rounds. Each round begins with a set-up phase while number of bits , k=1 , Transmission power , tp =1.
clusters are organized and then in the steady-state phase the
routing tree is constructed as well as aggregated data are sent to In this protocol , If node s CH-E is the largest value within
the sink node. radio range r , it will set its state as head and node which has
the second largest value of CH-E is selected as the back up
In IERP protocol, each node needs to maintain a cluster head for the next round. Because , the probability that
neighbourhood table to store the information about its this node will be selected as cluster head in the next round is
neighbours that including residual energy and distance to sink. high. So minimizing communication energy , calculations of
CHs for half of rounds and reduction of energy Consumption
A. Network Model for each round can help to prolong the network lifetime.
This paper assumes that N sensor nodes are randomly
scattered in a two-dimensional square field A and the sensor C. Construction of Routing Tree
network has the following properties: There are several ways that can construct aggregation
tree[16]. All tree algorithms have the same structure but have
 This network is a static densely deployed network. It different metrics and cost measures. In this paper we use two
means a large number of sensor nodes are densely parameters to select root node on tree which is distance from
deployed in a two-dimensional geographic space, each node (others or base station) and residual energy of the
forming a network and these nodes do not move any nodes. Only the root node of this tree can communicate with
more after deployment. the sink node by single -hop communication. In IERP , After
 There is only one base station, which is deployed at a clustering, cluster heads broadcast within a radio range R a
fixed place outside A. message contains node residual energy and its distance to base

29 http://sites.google.com/site/ijcsis/
ISSN 1947-5500
(IJCSIS) International Journal of Computer Science and Information Security,
Vol. 9, No. 11, November 2011
station. The cluster head computes RN (root node) by Using Where, Pcover is the coverage expectation of sensing field,
(4): and r is sensing radius, R is cluster radius and m' is the number
of active nodes. Use of intra-cluster coverage has two
( ECH  res ) j advantages. The first is to reduce energy consumption in each
RN  l l (4) round by turning redundant nodes’ radio off so that network
(E )
( CH res i )   dis(ij ) 2
 D (i) i1 lifetime is prolonged. The second is to reduce TDMA schedule
i 1 CH  db overhead. In this case we can coverage whole of network by
active nodes and other member nodes are turned off, as a result,
Where, (ECH-res) is obtained as follow: energy consumption in intra cluster nodes remarkably reduced
and network lifetime is extended [15].
( ECH res ) j  ( ECH rem ) j  ( ECH BS ) j (5) CH
NonCH
j  SC r
R
SINK
SC is set of cluster heads in radio range R , (ECH-res)j
indicates the residual energy of the cluster head , (DCH-db)
indicates cluster head distance to base station and dis(ij)
determines distance between cluster heads in radio range R.
Each cluster head node compute this RN and broadcasts it
to other cluster head nodes within its radio range R . If the other
cluster head node has smaller RN , it selects the node that has
the largest RN as its parents and sends a message to notify the
parent node. Finally, after a specified time, a routing tree will
be constructed, whose root node has the largest RN among all
cluster heads. Example of network topology is shown in Fig. 1.

TABLE I. SIMULATION P ARAMETERS

Parameters Value
Network Filed (0,0)~(100,100)
Number of nodes 100~500 Figure 1. Example of Network Topology
Cluster radius R 30 m
Sensing radius r 10 m
Sink position (50,200)
IV. PERFORMANCE EVALUATION
Initial energy 3J We used NS-2 to implement and simulate our protocol and
Data packet size 600 Bytes compare it with the ERA and EAP protocols. Every simulation
Broadcast packet size 30 Bytes result shown below is the average of 100 independent
Ethreshold 0.01 J
Eelec 50 nJ/bit
experiments where each experiment uses a different randomly-
Efs 10 nJ/bit/m2 generated uniform topology of sensor nodes. The parameters
Threshold distance 80m used in simulations are listed in Table 1.
Data Cycles per 5
round(L) A. Network Lifetime

D. Intra-Cluster Coverage
Coverage is one of the most important issues in WSNs and
it has been studied extensively in recent years [17]. Coverage
mechanism is to choose a subset of active nodes to maintain the
coverage expectation. We introduce into clusters the notion of
intra-cluster coverage which selects some active nodes within
clusters while maintaining coverage expectation of the cluster.
Utilizing the idea proposed in our research, cluster head
randomly chooses m' nodes according to (6) :
2i m  i
m
ri  r2 
p cov er  C   m 1  2 
 R  (6)
i k R   Figure 2. Network Lifetime

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Vol. 9, No. 11, November 2011
Fig.2 shows the network lifetime between ERA, EAP, and extremely reduce energy consumption in CHs, as shown in
IERP protocols with the number of nodes from 100 to 500. As Fig.4 for 10 rounds.
seen in figure, number of rounds is significantly extended due
to the reasons .First Cluster head roles are rotated, so energy D. Time of the Nodes dead
consumption among cluster members is balanced. Second, Fig.5 shows an influence of network topology. we change
constructing routing tree on cluster heads to send aggregated the number of nodes from 100 to 500 and observe the time of
data to the base station as multi-hop that can extremely reduces the nodes dead. In ERA and EAP each node has to spend more
energy consumption in Cluster heads. energy to communicate with other nodes and manage the
cluster so the network lifetime decreases with the scale of
B. Network Lifetime Versus Base station position network while IERP is improved on average time of 100%
As you know in ERA cluster heads, directly communicate nodes dead when the number of nodes is changed from 100 to
with the sink node, the energy consumption for each cluster 500.Because, each node has the lower energy consumption.
head is different because the distance between each node and
the sink node is different. As a result, energy consumption
farthest CHs to the BS more than nearest CHs. So, their energy
significantly reduced and nodes die soon. In IERP and EAP
protocols, there is only a single node to communicate with the
sink node, Fig.3 shows, the network lifetime of three protocols,
by changing base station position.

Figure 5. Time of the 100% nodes dead

V. CONCLUSION
In this paper, to maximize the network lifetime we used
hierarchical mechanism with new factors for selecting cluster
heads and root node on the tree. Also we introduced new
Figure 3. Network Lifetime vs. BS Position coverage schema for energy saving in member sensors, which
can save extremely energy in sensors. According Simulation
C. Average Energy Consumption in Cluster Heads results, IERP has improved the network lifetime by reducing
energy consumption on cluster heads and other sensor nodes,
when compared to other protocols.

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