Energy Efficient Head Selection Based Routing Protocol For Wireless Sensor Networks

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Energy Efficient Head Selection Based Routing

Protocol For Wireless Sensor Networks

Abstract: In recent past few years, have seen a drastic improvement and development in the wireless sensor networks. This sensor networks are mainly dependent up on the optimal deployment of the sensor nodes and efficient data transfer architectures .in addition, the energy efficient clustering mechanism are used to route the data packets from the source to the destination.in the clustering algorithm, the entire network region is divided into zones. In this clustering technique, the node reachability and effective communication is achieved by using the proposed scheme.in this paper, we proposed as criteria based zone head selection algorithm for wireless sensor networks by considering the distinct parameters such as a network lifetime and residual energy. The metrics for zone head selection is based on the residual energy, distance between the nodes and elapsed time. The simulation results of the given proposed scheme are out performing better than the existing routing protocol. The result has been verified by the number of parameter is zone head selection and its impact is on the calculated in terms of networks stability and lifetime.

Index Terms: Wireless Sensor Networks, Clustering Algorithm, Network lifetime, Criteria based zone selection, Head selection and Residual energy.

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The wireless sensor networks are widely used in both attended and unattended environment such as smart phones, surveillance, health monitoring, disaster management, boarder surveillance etc. The wireless sensor is used to sense the physical environment changes in and collect information is transmitted from one sensor nodes to zone heads. The zone heads will aggregate the received data and transmit the information to the base station for further processing [1-2]. The wireless sensor networks will face various challenges such as an energy consumption, localization and data aggregation/battery power. The nodes are always battery powered it will consume energy and prolong network lifetime. For all these activities in the sensor nodes requires more energy compared to the sensing and aggregation [3]. Therefore, the energy efficient routing protocol is required to maintain network stability and lifetime. In this network, in order to maintain the network consumption, the clustering technique is used to adopt the nodes work together in a group. This group of nodes is called the clusters. In these clustering schemes, the clusters are based on the many criteria, such as the distance between the nodes and the energy consumption.

In this literature, there are many clustering techniques with probabilistic approaches has to be proposed to achieve the energy consumption. In this probabilistic approach, the cluster heads are based prior probability and to generate the random number selection scheme. The major drawback is that not to consider parameters such as energy level, position of the nodes in a clusters etc. The non-probabilistic approach the selection criteria is based on the residual energy, transmission power, distance etc. Due to the given randomize nature of

wireless sensor networks is having an open challenges and issue in large networks [4-5]. In this paper, we proposed a multi criteria bases zone head selection in wireless sensor networks. This technique is attempted to improve the lifetime of the networks and life span of the entire networks. The main contribution of this paper is that to develop such algorithm to select the most efficient zone heads to sense more data for making decision. In this routing protocol, the considered distinct parameters such as network lifetime, energy level, distance from the neighboring nodes, distance from the center zone and random number. For further analyzing, the zone head selection in this proposed technique, initially the one parameters is considered to extend the five parameters used. The rest of the paper is organized as section 2 is about the background, the proposed method is discussed in section 3, the simulation setup and result is explaining in section 4 and finally to paper is concluded in the section 5.

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This section explores the many existing energy efficient techniques proposed to address the energy efficiency, network stability, residual energy and network lifetime etc. In W. Heinzelman [6] proposed a low energy efficient adaptive clustering routing algorithm to address the above issues. This routing mechanism is a probabilistic approach which the cluster heads are selected based on the random number between 0 to 1. The main drawback of this algorithm is based on the random number and other parameters are not considered so the network performance is very poor. S. Lindsey etal., has introduced the power efficient information gathering routing protocol that forms chain of nodes using greedy algorithms [7]. The sensing nodes near to the base stations selected as leader to forward the collected data. This will improve the energy consumption. This will increase the transmission end to end delays due to long chain. The more amount of the energy is depleted because of the resulting in the network partitioning. In H. Farman, proposed an optimum cluster head selection algorithm [8] is proposed to maximize the network lifetime and to distribute evenly the entire nodes across the networks. This routing protocol is based on merge and split techniques. The whole network is divided into certain zones and the total number of nodes in each zone are identified. The node density is less than the threshold, so that the nodes are merged with the all the zone neighboring nodes. The major disadvantages of this routing protocol are to sudden ————————————————

 Mr. Baranidharan V is currently working as an Assistant professor in Department of Electronics and Communication Engineering, Bannari Amman Institute of Technology, Sathy, India. His areas of interest are Wireless Communication and Networks, Wireless Body Area Networks & Image processing. E-mail: [email protected]

 Mr. Sathishkumar K is working as an Assistant professor in Department of Electronics and Communication Engineering, Bannari Amman Institute of Technology, Sathy, India. His area of interest is RF Systems design and Optical networks. E-mail ID: [email protected]

depletion of the energy at earlier stage. The H. Farman [9] also proposed a new routing protocol to overcome this energy depletion issue. In this routing protocol the zone heads are selected based on the non-probabilistic way by using various three parameters. To minimize the node residual energy, the author considers these three parameter is selector of cluster/zone heads. The Author in [10] is proposed an energy based cluster head selection of unequal clustering algorithms. The proposed method addresses the problem of energy consumptions and to maintain the unequal clustering. This initially selects, a dummy cluster head based on energy, Random number, energy based on the sinks are used to collect the data from the al other nodes. The major issue is that the network overhead occurs by using sinks [11-12].

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In this proposed works, a multi-criteria based improved zone head selection routing protocols is developed. In all other exiting routing protocols, the zone head selection is based on the three distinct parameters energy levels, zone-node distances, and zone-center distance.

Fig.1.Random Deployment of sensor nodes

Fig.2.Zone formation and identifying the total number of nodes in the region

Fig.3.Merging and splitting of sensor nodes based on their node density

This proposed research work improves the network stability and overall network lifetime by considering the five various distinct parameters for zone head selections. This entire process for the head selection is classified into two phase. They are, Topology Construction and Zone Head Selection.

Topology Construction

In the modified routing protocol, the entire networks are divided into a various M x M dimensional grids; the each girds are represented as zones. The entire sensor nodes (N) are deployed over the entire regions randomly. Here, the field area is given as the product of field-height and field-width. Each and every zone is having zones ID number, which are generated randomly. All the nodes are considered as static nodes. The nodes are not able to change their positions. We assuming that all the base station and sensor nodes are having some basics knowledge about the zone ID, energy levels and this coordinates (X, Y, Z positions). On the basis of the coordinates system, the high and low density zones are identified first, if the number of the nodes in a zone is less than the selected threshold value than the nodes in the nodes is merged with the neighboring zone. In case if the number of nodes will exceed than the upper threshold value, automatically the zone is splitted into two regions equally.

W (N) = [(Di x distance) + (Sigma + density)] – (1) Where, Di is the distance between the sensor nodes and clusters, W (N) is the weight of an each and every sensor node, Sigma is the randomly generated number and Density is also considered to calculate the Weight. If the topology was constructed, then the base station will determine zone head from all the neighboring nodes. The zone heads are always responsible for the data gathering from all the nodes.

Zone Head Election and Selection

The network performance is depending upon the election and correct selection of the zone head in WSN. The networks instability and lowering network lifetime will be based upon the selection of proper zone heads. The zone heads are the responsible for the data gathering, aggregating and forwarding to the selected monitoring system. There are five mainly distinct parameters are used. They are,

(i) Nodes Residual energy

(ii) Distance between the neighboring nodes with the zone (iii) Distance from the zone center

3741 The aggregated values of these five parameters will be

calculated based on it analytical network process (ANP). In the general the sum of all the four weights are always equal to 1. After scaling of the entire networks based on the pairwise comparison of the criteria and the alternative method is calculated .In case the consistency ratio is less than 0.1 then the comparison made is always consistent.

ASi = (W1 ∗ RELi) + (W2 ∗ 1/ADVi) + (W3 ∗ PRTZH ) + (W4 ∗ MNode) – (2) Where, ASi is the comparison ratio based on the weights, W1, W2, W3 and W4 are the weights in the network model, PRTZH is the priority of the zone head and MNode is the maximum distance between the nodes and RELi is the residual energy of the all nodes after the simulation. The distance parameter will also be considered as an important parameter to know the distance between the neighbouring nodes and the centring nodes. The minimum value of ADC is also calculated. The distance between the nodes is given as,

Dist (I, j) = √( )( ) ( )( ) -- (3)

The distance between the center of Zone Head and the all the sensor nodes are given as,

Dist_Cr (i,j) = √( )( ) ( )( ) – (4)

Where, α and β are the weights assigned to distance between the sensor nodes and distance between the center (Zone Head) and the sensor nodes according to the importance. It is derived from TZH parameter as shown in the above equation, which represents the number of times a node has been zone head. Initially it will be same for all nodes, as in the first round no node has been nominated as ZH. However, in the reselection process, node that has been ZH once will have less priority and so on. Moreover, high value of TZH will minimize the chances to be ZH to avoid poor node selection that can affect the network stability and overall network lifespan.

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The proposed method is compared and evaluated with the related existing energy efficient routing protocols in the terms of the network stability and overall network stability and overall network lifetime. The network stability means when the first node lies in the networks. The overall network lifetime is given as the stage when all the nodes die. The proposed modified the multi-colored is adopt to select the most optimum node as an zone head. The existing routing protocol such as leach is compared with the routing protocol. The results are shows that this proposed method will be having a better or outperform than the existing routing protocol.

Simulation Setup

In the wireless sensor networks model, consider an N number of static nodes. These nodes are deployed randomly over the entire region. The entire deployment region is divided into various M x M regions. The stability of the entire network is measured in terms of number of rounds (random). Before the simulation, some few assumptions are made such as energy and position of all, the sensor nodes are known all other nodes. The numbers of rounds are considered based on network stability period. The parameters are given as simulation is given in this following table,

Table.1. Simulation Parameters

PARAMETERS DESCRIPTION Area 1000x1000 M Total Number of Nodes 100

Node density(N) 100 Energy(Joules) 2.0 Packet Size(Bits) 2000 Grid Dimension(m) 40 m Amp(pj/bit) 50J

W1 0.4

W2 0.36

W3 0.14

Network stability

The proposed routing method is compared with respect to network stability to analyse how long time it takes requires to first node die within the entire network. To maintain the stability of the network, the different energy levels are considered. The given figure shows that the proposed routing protocol takes more number of rounds to first node to die in compared with existing protocols.

Fig.4. Comparison of Residual Energy versus Number of Rounds

In the existing method, the nodes will directly send the data to monitoring system. So they result in depletion of more energy. While the existing protocols will not consider energy level into a account of cluster selection. So it takes a very less number of rounds to die. The proposed method out performs better than the number of rounds and it will maximize the stability period. This outperformance of this routing protocol is based on the criteria for the selection of zone heads based on multi criteria’s.

Network Lifetime

one chain leader node is responsible to formation of chain, resulting in more energy consumption.

Fig.5. Overall network lifetime w.r.t initial energy at 0.5 J).

Fig.6. Overall network lifetime w.r.t initial energy at E = 1J

Fig.7. Overall network lifetime w.r.t initial energy at 1.5 J

When the existing routing protocol consider the most of the parameters, that is based on merge and split strategy by using the merging factors. In the existing routing protocol, the merged node and number of times the node has been cluster head not considered they two parameters as well as they minimized the chance of fuel node that is merged from other zone and lowers priority of a nods from other zone and lowest priority of a node that has been selected, zone head which results in number of rounds.

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In this paper, an improved Energy Efficient Head selection based Routing protocol scheme for selection the Zone Head Selection and Re-selection for Wireless Sensor Networks with 100 nodes at random deployment. The work is mainly focused on works was at two important parameters. First, the zone head selection problem was solved by the set of five parameters such as Residual energy, Distance between the sensor nodes, Distance between the center and sensor nodes, Threshold energy level and Maximum nodes available. The Zone head selection is based on the set of best among the five parameters and its impact is considered as a multi-criteria decision probability. Secondly, the simulation of the proposed method was performed and the results are obtained is compared with existing routing protocols. It was shown that the proposed scheme is having an improved ZH selection and re-selection, good network stability and improved overall network lifetime at different energy levels. In future, the current work is extended to ZH selection and re-selection for the nodes at mobile and frequency of change their position based on some realistic mobility models.

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