Hybrid Protocol to Improve Network Lifetime in Wireless Sensor Network

Transcription

1 Hybrid Protocol to Improve Network Lifetime in Wireless Sensor Network Sippy GZS PTU Campus, Bathinda (Punjab) Jyoti Saxena Professor, GZS PTU Campus, BTI Sukhjinder Singh Assistant Professor, GZS PTU Campus, BTI Abstract Energy efficiency is an important research issue in Wireless Sensor Networks (WSNs) to maximize network lifetime. Hence energy efficiency needs to be boosted in order to improve the network lifetime. Researchers suggested various protocols such as LEACH and I-LEACH etc. in order to meet above said requirements. However, LEACH fails for heterogeneous environment whereas I-LEACH results in improved network lifetime as compared to LEACH but not much efficient as compared to PEGASIS. So in order to further improve the performance of I-LEACH, a new hybrid protocol based on the chain-formation of PEGASIS has been developed and implemented using MATLAB platform in this paper. Experimental result showed that proposed protocol efficiently improves network lifetime over I-LEACH and PEGASIS with 250 and 101 rounds respectively at initial energy of 0.25J/Node over a network area of 100m x 100m. 1. Introduction The enhancement of technology in wireless communication has evoked much interest in WSNs Due to this growing up interest, tiny, low power, in expensive and multifunctional sensor nodes are being developed. Hundreds to thousands of sensing nodes are. densely deployed throughout a physical space to set up a WSN to observe numerous environmental parameter such as motion, pressure, humidity and temperature etc. The collaborative efforts of a vast number of sensor nodes has wide range of applications from s health, home and environment to military, space and commercial. After coming into light, WSNs have reformed the perspective on the collection and communication of data over wireless channel. Information about the environment is collected by sensor node, processed and transmitted to Base Station (BS). Much smaller number of sensor nodes may be equipped with the potential of data aggregation (process of combining distributed data into meaningful information) and data fusion (method in which different type of data from several sensors, are integrated to improve efficiency) which provide support to transmit partial processed data instead of fresh data. All sensor nodes are generally deployed randomly which creates an ad-hoc network. In a WSN, there are multi paths available to transmit the information from source to destination. Method of discovering out these paths is called as routing. Sensor nodes in WSNs are likely to be battery oriented and often it is difficult to recharge or change its battery make these nodes alive. So prolonging the network lifetime is desirable. One round is said to be completed when BS collects data from all nodes [12]. Routing protocols having low energy consumption [1, 10 and 14] is desirable in order to increase network lifetime. In addition, for limited channel bandwidth routing protocols has been put into practice to minimize bandwidth requirement. The most widely used hierarchical routing protocols such as LEACH, PEGASIS and I-LEACH etc. LEACH follows cluster formation concept. PEGASIS is near optimal chain-based protocol. I- LEACH was purposed to overcome shortcoming of LEACH and PEGASIS such as probability based CH 177

2 selection and uncertainty about CHs position in WSN. Hence, a new hybrid protocol is purposed that outperforms above said protocols. The implementation of a hybrid protocol to improve the network lifetime of WSNs is the main focus of this paper. The remainder of the paper is organized as follows: section-2 describes briefly, the related works and widely used routing protocols. The proposed technique and implementation is given in section-3. Section-4 provides the experimental setup and results obtained followed by conclusion and future scope of this paper in section Related Works The sensor nodes of WSN collect data from surrounding fields for onward transmission to BS. For the transmission, data packets need to follow some path and this is decided using routing protocol. Routing protocols [6] on the basis of network structure can be classified as flat based, location based and hierarchical based. In flat, each node typically plays the same role (homogeneous) so connection between the nodes is set for short distance communication. In Location based, sensor nodes are addressed by means of their locations. The distance between neighbouring nodes can be estimated on the basis of incoming signal strengths. In Hierarchical [2] based methods, higherenergy nodes may be used to process and send the information, while low-energy nodes may be used to perform the sensing in the proximity of the target. It deals with the creation of clusters and assigning special tasks to Cluster Heads (CHs). To minimise energy consumption and improving network lifetime, various hierarchical routing techniques proposed in literature such as LEACH [8], PEGASIS and I-LEACH etc. are briefly reviewed below: 2.1. LEACH W.R.Heinzelman [3], introduced a hierarchical clustering protocol for sensor networks, called Low Energy Adaptive Cluster Hierarchy. The purpose of this is to select a different set of CHs during each round. Each round in LEACH consists of a set-up phase and steady-state phase. Set-Up phase Set-Up phase further consists of two step discussed as follows: Cluster formation In this, neighboring nodes dynamically form cluster in distributed manner assuming all the nodes start with equal energy. Cluster Head Selection CH selection depends on decision made by the node by choosing a random number between 0 and 1. If the number is less than a threshold T(n), the node becomes a CH for the current round. The threshold is set as: (1) Where P is desired percentage of CHs, r is the current round; G is the set of nodes that have not been CHs in the last 1/P rounds. T(n) is the threshold probability value for candidate node n to become a CH at round r, n is node that choose a random number between 0 and 1. Using T(n), each node will be a CH at some point within 1/P rounds. Time Division Multiple Access (TDMA) is deployed for better management and scheduling. Steady-State Phase At the completion of each round, each node that is not a CH will select the nearest CH and joins that cluster to transmit data. The CHs combine and compress the data and forward it to the BS directly, thereby extending the life span of major nodes. After a certain period of time, network goes back to set-up phase and again starts a new round of CH selection. LEACH assumes that 5% of the total nodes play as CHs in every round PEGASIS An improvement over LEACH named as Power- Efficient Gathering in Sensor Information Systems (PEGASIS) has been proposed by S. Lindsey and C. S. Raghavendra [4]. This is chain-based protocol for extending the life span of network. In PEGASIS, every node communicates only with the adjoining neighbour by adjusting its power signal to be only heard by this adjoining neighbour. Every node uses signal strength to measure the distance to neighbourhood nodes in order to locate the closest nodes. In this chains of nodes are formed and during the formation of chain, care must be taken so that nodes already in chain should not be revisited and once a node die, then the chain is reconstructed by 178

3 bypassing that node. All nodes are homogenous and provided same amount of initial energy. Lifetime is maximized by increasing number of rounds. Data collection starts from the farthest node from the BS. In data collection cycle, each node receives a data packet and fuses that with its own data packet and then forwards it to other neighbouring node in network. This is called as token passing. A leader is selected from the chain formed on the basis of residual energy in every round and that leader collects data from the adjoining node to be transmitted to the BS.As an outcome, the average energy depleted by every node per round is reduced I-LEACH Naveen Kumar and Jasbir Kaur [5] proposed a new routing protocol named I-LEACH that outperformed LEACH by overcoming the limitations existing in its counterpart those are probability based CH selection and uncertainty about the location of CHs throughout the network. In LEACH also there is possibility that selected CHs may be concentrated in one part of network. Hence some nodes will not have any CHs in their neighborhood and as a result these nodes will have to transmit their data to far-distant CHs. In I-LEACH, first of all the probability based selection criteria for a CH was replaced with concept of residual energy and this energy is used for the selection of CH. The other limitation has been solved out by formation of clusters on the basis of x-axis coordinates of the nodes; it helped out in the uniform distribution [11] of the CHs i.e. CHs will not be selected at one portion of the network. This provision of co-ordinates based cluster-formation resulted in the reduction of energyconsumption in the WSN. LEACH completes 1077 rounds where as I-LEACH completes 1248 rounds when all nodes die over 100m 100m network area. As a results I-LEACH outperformed LEACH with 171 more rounds and 15% more energy efficient than LEACH at 1J/Node energy. But still it was not as much efficient as compared to PEGASIS because the number of dead nodes for a given number of rounds/runs [12] in this was significantly higher than PEGASIS that directly impact the network lifetime. using MATLAB platform. A wireless sensor network out of various possible models has been considered for the proposed protocol and it has following assumptions initially [7 and 9]. All sensor nodes in the network are static, homogeneous and with equal initial energy in starting. After first round, nodes will consider residual energy instead of initial energy and work as node heterogeneity. Each node periodically senses its nearby environment and would like to send its data to BS located at a fixed point. Distance is estimated from received signal strength. Data aggregation or data fusion is used to minimize redundancy in data assuming n packets of size k results in one packet of size k rather than n k size. Energy required for transmitting a message from A to B is same as energy required for transmitting message from B to A. So radio channel is symmetric. In this technique, the residual energy concept is used to select the CHs instead of probability based selection, so that non homogenous (heterogeneous) [13] sensor nodes can also perform well with this protocol and coordinates of the x-axis have been used to make sure that distribution of CHs is uniform. The diagrammatical representation to implement this protocol has been shown in figure 1. In residual energy concept, amount of energy for transmit electronics, amount of energy for receive electronics, amount of energy for transmit amplifier for k bits packet and amount of differential energy are calculated using first order radio energy model and calculated amount of energy is subtracted form initial energy. Depending upon the amount of energy left, node will become cluster head (CH). Each node is placed according to (x,y) coordinates. In this x- coordinates are taken at a fixed distance and y- coordinates are taken random to implement uniformity of nodes. 3. Proposed Technique To overcome the above said drawbacks, a new hybrid routing protocol has been developed and implemented 179

4 Table 1:- Initialization parameters Parameters Values No. of Runs/Rounds, r 3500 No. of Nodes, NODES 100 Network Size, (L L) Base Station Location, (BSx, BSy) No. of bits each node is transmitting, k Initial energy of a node, E 100m 100m (50,300) J,.5J, 1J Figure 1:- Implementation of proposed hybrid protocol Also, the conceptual advantages of chain-formation from the PEGASIS have been added while designing this protocol. The details are given below with the help of pseudo code Radio Energy Model Path loss exponential, c 2 Electronics Energy for Transmitter and receiver, E elec Transmit Amplifier Energy, E amp Data Aggregation, E diff Minimum energy,e min 50 nj/bit 100 pj/bit/m 2 5nJ/bit/message Joule Number of clusters,n 5 Radio energy model is used to calculate overall energy consumed in by a node for transmission and reception. It can control their power to enhance the least power required to reach the anticipated recipients. The radios can also be turned off to avoid receiving undesired transmissions [3]. A energy loss (c = 2) is utilized due to channel transmission. The equations used to calculate transmission energy and receiving energy for a k-bit message and a distance d are shown as: Transmitting: E Tx (k, d) = E elec k + E amp k d c (5) Receiving: E Rx (k) = E elec k (6) The radio channel is taken symmetric and number of receives and transmissions ought to be as low as possible because reception of data is a highly energy consuming operation. In simulations, the packet length k of 2000 bits is considered Initialization Table 1 represents various parameters that are used in initialization Pseudo code Initially for first round, energy of all sensor nodes are assumed to be equal (homogeneous). Selection of CHs and leader on the basis of minimum distance from BS has been summarized using following steps: Step 1: 100 random nodes of equal energy are deployed in an area of 100m x 100m and BS is at (50, 300). Step 2: Formation of cluster is done on the basis of x- coordinates. 100 nodes are distributed equally to form 5 clusters, each cluster has 20 nodes (1 to 20 nodes in first cluster, 21 to 40 nodes in second cluster and so on). The code for nodes distribution in cluster is given below. for i=1:1:100 NodeX(1,i)=i; NodeY = rand(1,nodes); end Step 3: Cluster Heads in the first round are selected on the basis of shortest distance between a node and BS. The distance is calculated using eq. 2. This step will be repeated for each cluster to select CH. 180

5 d = (2) Step 4: Chain is formed in each cluster starting from farthest node, distance between two nodes is calculate using coordinates formula (ref eq. 2).Nodes with minimum w.r.t. its neighbourhood node, forms a chain. Step 5: Similarly the distance between selected CHs and BS is calculated using eq. 2, CH having minimum distance will be selected as Cluster leader that transmits data to BS. For second round onwards (up to r rounds/runs) the steps are summarized as: Step 6: Now with the help of first order radio model, dissipated energy is calculated and subtracted from initial energy to find residual energy and is calculated using eq. 3.Node with maximum residual energy is selected as CH. different initial energy of 0.25 Joule, 0.5 Joule and 1 Joule, scattered randomly with in network area. The BS is located at. Dissipated energy will be calculated using radio model. MATLAB is used for simulating of this protocol Results After the implementation of proposed protocol using MATLAB, results show that certainty about distribution of CHs is uniform and with residual energy, nodes can work for homogeneous as well as heterogeneous environment efficiently. Chain formation is also successfully implemented. Figure 2 represents Cluster Leader, CHs and dead nodes in each cluster of sensing field. (3) Step 7: Step 4 of first round will repeat. Step 8: Cluster Leader is selected with maximum (ref eq. 3) among already selected CHs. Step 9: After the completion of a round, each node is again calculated. If for of a node is less than E min ( minimum energy required by a node to be alive) then that node will declared dead node. E min has been calculated using eq. 4 E min = (4) Step 10: Step 6 to 9 will repeat itself until all rounds completed. In code, x- coordinate, y- coordinate, energy, CH, leader, alive node and dead node etc. are stored in different columns of matrices Finalization r(1) = No. of rounds when first node get dead r(2) = No. of rounds when 50 nodes get dead r(3) =No. of rounds when 100 nodes get dead Plot =No. of rounds v/s % of dead nodes Figure 2:- Representation of leader, cluster head and dead Nodes Simulations are run to determine the number of rounds of communication when 1%, 50% and 100% nodes die. The number of runs for different failure at initial energy 0.25J/Node is as under: Number of runs when 1node die: 436 Number of runs when 50 nodes die: 727 Number of runs when 100 nodes die: 792 The comparison of new hybrid protocol with LEACH, PEGASIS and I-LEACH is shown in Table 2 and Figure 3. Results represent that new hybrid protocol outperform I-LEACH with 250 and PEGASIS with 101 more rounds when 1% nodes died at lowest energy i.e. 0.25J/Node energy. 4. Experimental Setup & Results 4.1. Experimental Setup To evaluate the performance of hybrid protocol, simulation consists of 100 homogenous nodes with 181

6 No. Of Rounds Sippy et al, International Journal of Computer Science & Communication Networks,Vol 5(3), Table 2: The number of rounds until 1%, 50% and 100% nodes die for a 100m x 100m network for LEACH, I-LEACH, PEGAIS and Hybrid protocol at different initial energy Initial Energy Protocol 1% 50% 100% 0.25J/Node LEACH J/Node I-LEACH J/Node PEGASIS J/Node Hybrid J/Node LEACH J/Node I-LEACH J/Node PEGASIS J/Node Hybrid J/Node LEACH J/Node I-LEACH J/Node PEGASIS J/Node Hybrid Initial Energy 0.25 J/Node 1% 50% 100% Figure 3:- Comparison of different protocol for a 100m x 100m network with initial energy of 0.25J/Node 5. Conclusion & Future Scope Experimental results show that new hybrid protocol works even if the nodes have different initial energy, so it solves the issue of node heterogeneity. The uncertainty about the location of CHs has been resolved by the provision of x-coordinates based cluster formation. It also implements chain formation concept from PEGASIS. The node distribution in this is uniform as in I-LEACH. Therefore new hybrid protocol, improves the network lifespan over LEACH, PEGASIS and I-LEACH in terms of number of rounds/runs with respect to number of alive nodes. From future perspective, some of the parameters: different topologies, network area and no. of CHs in the protocols can be changed to verify the results. 6. References [1] Malka N.Halgamuge, Siddesware Mayura Guru and Andrew Jennings, Energy Efficient Cluster Formation in Wireless Sensor Networks, IEEE Tenth International Conference on Telecommunications, 2, 2003, pp [2] LaialiAlmazaydeh, EmanAbdelfattah, Manal Al- Bzoor, and Amer Al- Rahayfehanalyze, Performance Evaluation of Routing Protocols in Wireless Sensor Networks, International Journal of Computer Science and Information Technology, 2, 2010, pp [3] Wendi Rabiner Heinzelman, Anantha Chandrakasan, and Hari Balakrishnan, Energy-Efficient Communication Protocol for Wireless Microsensor Networks, Thirty-third Annual Hawaii International Conference on System Science, 2000, pp [4] Stephanie Lindsey and Cauligi S. Raghavendra, Power- Efficient Gathering in Sensor Information Systems, IEEE Aerospace Conference, 2002, pp [5] Naveen Kumar and Jasbir Kaur, Improved LEACH Protocol for Wireless Sensor Networks IEEE Seventh International Conference on Wireless Communications, Networking and Mobile Computing, 2011, pp [6] Jamal N.Al-Karaki and Ahmed E.Kamal, Routing Techniques WSN: A Survey, IEEE Wireless Communication, 2004, 11, pp [7] Fuzhe Zhao, You Xu, Ru Li and Wei Zhang, Improved Leach Communication Protocol for WSN, International Conference on Control Engineering and Communication Technology, 2012, pp [8] Raed M. Bani Hani and Abdalraheem A. Ijjeh, A Survey on LEACH-Based Energy Aware Protocols for WSN, Journal of Communications, 2013, 8, pp [9] Kyung Tae Kim, Han Ku Yoo, Byung Ha Son, and Hee Yong Youn, An Energy Efficient Clustering Scheme for Self-Organizing Distributed Wireless Sensor Networks, IEEE Tenth International Conference on Computer and Information Technology, 2010, pp [10] Kanojia Sindhuben Babulal and Rajiv Ranjan Tewari, Cross layer Energy Efficient Routing (XLE2R) for Prolonging Lifetime of Wireless Sensor Networks, IEEE International Conference on Computer and Communication Technology, 2010, pp [11] Prof. K. Manikandan and Dr. T. Purusothaman, An Efficient Routing Protocol Design for Distributed Wireless Sensor Networks, International Journal of Computer Application, 2010, 10(4), pp [12] Keyhan Khamforoosh and Hana Khamforoush, A New Routing Algorithm for Energy Reduction in Wireless Sensor 182

7 Networks, IEEE Second International Conference on Computer Science and Information Technology, 2009, pp [13] Li Qing, Qingxin Zhu, and Mingwen Wang, Design of a Distributed Energy-Efficient Clustering Algorithm for Heterogeneous Wireless Sensor Networks, Computer Communication, 2006, pp [14] Mohamed Younis, Moustafa Youssef and Khaled Arisha, Energy-Aware Routing in Cluster-Based Sensor Networks, IEEE Tenth International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunications System, 2002, pp