An Improved Energy Aware Hierarchical Routing Protocol in Wireless Sensor Networks

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An Improved Energy Aware Hierarchical Routing Protocol in Wireless Sensor Networks Powered By Docstoc
					                                                                  (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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                                                                                                       ISSN 1947-5500
                                                              (IJCSIS) International Journal of Computer Science and Information Security,
                                                                                                            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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                                                                                                                       Vol. 9, No. 11, November 2011
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