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International Journal of
Electronics JOURNAL OF ELECTRONICS AND INTERNATIONAL and Communication Engineering & Technology (IJECET), ISSN 0976 – 6464(Print), ISSN 0976 – 6472(Online), Volume 5, Issue 1, January (2014), © IAEME COMMUNICATION ENGINEERING & TECHNOLOGY (IJECET) ISSN 0976 – 6464(Print) ISSN 0976 – 6472(Online) Volume 5, Issue 1, January (2014), pp. 148-157 © IAEME: www.iaeme.com/ijecet.asp Journal Impact Factor (2013): 5.8896 (Calculated by GISI) www.jifactor.com IJECET ©IAEME S-LEACH: A SEQUENTIAL SELECTION APPROACH TO ELECT CLUSTER HEADS FOR LEACH PROTOCOL Ankit Thakkar1, Ketan Kotecha2 1 Assistant Professor, CSE Department, Institute of Technology, Nirma University, Ahmedabad - 382 481, Gujarat, India 2 Director, Institute of Technology, Nirma University, Ahmedabad - 382 481, Gujarat, India ABSTRACT Wireless Sensor Nodes are deployed in the hostile region to help the user by providing data to the user for the review purpose. These nodes are having limited power as they are battery operated. Hence, routing protocol used to deliver data to end users must be energy efficient to provide prolonged network lifetime. In this paper, we have proposed a decentralized clustering scheme based on sequential selection (S-LEACH) that maintains desired number of cluster heads during each round until the death of first node. Extensive simulations are carried out to compare our proposed protocol with three well known protocols - LEACH (Low Energy Adaptive Clustering Hierarchy), LDCHS (Low Energy Clustering Hierarchy with Deterministic Cluster Head Selection) and ALEACH (Advanced LEACH). Simulation results show that S-LEACH outperforms to the LEACH, LDCHS and ALEACH protocols. Key words: LEACH, Sequential Selection Approach, Energy Efficient Routing, Cluster Head Selection, Wireless Sensor Network 1. INTRODUCTION Energy efficiency is an important issue in Wireless Sensor Network (WSN), and steps taken to do effective communication by reducing number of transmissions affect the network lifetime. Low Energy Adaptive Clustering Hierarchy (Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000, January)) is one of the energy efficient adaptive clustering protocols and its primary goal is to save energy. It has also put foundation to enhance network lifetime with clustered based routing approach (Wang, A., Yang, D., & Sun, D. (2012)). Many cluster based approaches have been proposed to enhance network lifetime of a WSN which includes but not limited to EECS (Ye, M., Li, C., Chen, G., & Wu, J. (2005, April)), EEHC (Kumar, D., Aseri, T. C., & Patel, R. B. 148
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International Journal of
Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 – 6464(Print), ISSN 0976 – 6472(Online), Volume 5, Issue 1, January (2014), © IAEME (2009)), VLEACH (Yassein, M. B., A. Al-zou'bi, Khamayseh, Y., & Mardini, W. (2009)), CVLEACH (Thakkar, A., & Kotecha, K. (2012)), ALEACH (Ali, M. S., Dey, T., & Biswas, R. (2008, December)), WALEACH (Thakkar, A., & Kotecha, K. (2012)), WCVALEACH (Thakkar, A., & Kotecha, K. (2012)), EDACH (Kim, K. T., & Youn, H. Y. (2005, January)), REEH (Sehgal, L., & Choudhary, V. (2011)),TL-LEACH (Loscri, V., Morabito, G., & Marano, S. (2005, September)), LDCHS(Handy, M. J., Haase, M., & Timmermann, D. (2002)). In EECS (Ye, M., Li, C., Chen, G., & Wu, J. (2005, April)), author have achieved near uniform distribution of cluster heads through localized communication with minor overhead. In EEHC ((Kumar, D., Aseri, T. C., & Patel, R. B. (2009)), authors have used weighted probability to elect the cluster heads for heterogeneous WSN. CVLEACH (Thakkar, A., & Kotecha, K. (2012)) improves network lifetime by creating non-overlapping cluster regions by utilizing over hearing capacity of the nodes. ALEACH (Ali, M. S., Dey, T., & Biswas, R. (2008, December)) considers remaining energy of the nodes to elect cluster heads. WALEACH (Thakkar, A., & Kotecha, K. (2012)) improves ALEACH by assigning weight factor. In WCVALEACH (Thakkar, A., & Kotecha, K. (2012)), authors have combined the idea of weight factor with over hearing property of the nodes to prolong network lifetime. EDACH (Kim, K. T., & Youn, H. Y. (2005, January)), prolongs network lifetime by assigning more cluster heads in the region farther from the BS. REEH ((Sehgal, L., & Choudhary, V. (2011)), is designed and validated for heterogeneous wireless sensor network in which residual energy of the node is considered to elect the cluster head. TL-LEACH (Loscri, V., Morabito, G., & Marano, S. (2005, September)), improves network lifetime by reducing data transmission distance by creating two levels of cluster heads. LDCHS (Handy, M. J., Haase, M., & Timmermann, D. (2002)) improves stochastic approach of LEACH to elect cluster head by introducing deterministic component. The protocols discussed above are energy efficient clustering protocols. They are either based on LEACH protocol or designed separately. LEACH protocol gives optimal performance when 5% of the total nodes are elected as cluster heads during each round (Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000, January)). However, LEACH does not ensure that desired numbers of cluster heads are maintained during each round. The same is also applicable to LDCHS and ALEACH protocols as they are based on LEACH protocol. In this paper, we have proposed a new sequential selection approach (S-LEACH) to maintain desired number of cluster heads during each round to improve network lifetime. Rest of the paper is organized as follows: LEACH, LDCHS and ALEACH are described in Section 2; System and Energy model are given in Section 3; S-LEACH is discussed in Section 4; Simulation Strategy and Result Discussion are presented in Section 5 and Concluding remarks are given in Section 6. 2. LEACH, ALEACH and LDCHS In LEACH (Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000, January)), authors have proposed energy efficient cluster based routing scheme, in which role of cluster head (CH) is rotated between nodes to achieve uniform energy depletion through load balancing. Each sensor node elects itself as a CH with certain probability. This status is informed by the CH nodes to the other nodes in the network. After getting status message from the CH nodes, non-CH nodes select one of the CHs as its own cluster head for which minimum energy is required for communication. CH nodes receive data from the non-CH nodes, fuse it and send to the Base Station (BS). At the commencement of the each round, a node selects a random number which is uniformly distributed pseudo random number between 0 and 1. If random number is less than threshold value T(n) which is given by equation 1, then node elects itself as a CH for the current 149
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International Journal of
Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 – 6464(Print), ISSN 0976 – 6472(Online), Volume 5, Issue 1, January (2014), © IAEME round. LEACH ensures that each node becomes CH only once every 1/p rounds, where p is the desired percentage of cluster heads known a priori to the algorithm. (1) In ALEACH (Ali, M. S., Dey, T., & Biswas, R. (2008, December)), authors have modified threshold value T(n) which is given by Equation 2. ALEACH also works in rounds as LEACH. Each round begins with Cluster Setup phase. During cluster setup phase, a node selects a random number between 0 and 1. If selected random number is less than threshold value T(n), then the node declares itself as a cluster head where T(n) is given by equation 2. (2) where Gp and CSp is given by equations 3 and 4 respectively. Gp and CSp refer to general probability and current state probability. (3) where k/N refers to the desired percentage of cluster heads during each round and Ecurrent and Emax is remaining energy and maximum energy of a node respectively. (4) In LDCHS (Handy, M. J., Haase, M., & Timmermann, D. (2002)), authors have modified threshold T(n) given in Equation 1 to elect cluster head by considering ratio of node’s current energy with respect to initial energy and it is given by Equation 5. (5) LEACH, ALEACH and LDCHS use stochastic approach to select cluster heads with certain probability. LDCHS and ALEACH improve LEACH protocol by considering current energy of the nodes to elect cluster heads. However, there is a huge variation into the number of cluster heads elected and desired number of cluster heads required during each round that results into un-even energy depletion of the network. Number of cluster heads during each round for LEACH, LDCHS and ALEACH is presented at the end of the paper. 150
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Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 – 6464(Print), ISSN 0976 – 6472(Online), Volume 5, Issue 1, January (2014), © IAEME 3. PREREQUISITE 3.1 System Model In this paper, we have considered a sensor network of N nodes that are uniformly distributed in the region of MxM m2. Following assumptions are made about the sensor nodes and underlying network (Chen, G., Li, C., Ye, M., & Wu, J. (2009)). 1. Base Station (BS) is located in the center of the node deployment area and it is having infinite amount of energy. 2. BS and sensor nodes are stationery once they are deployed in the Region of Interest (ROI). 3. All sensor nodes are homogeneous and are assigned unique identifier. 4. All sensor nodes are having limited amount of energy. 5. All sensor nodes are capable of transmitting with different power levels depending upon the distance from the desired recipient. 6. Communication links are symmetric. 7. Cluster Head always receive highly correlated data from the member nodes. Thus, data aggregation is possible. 8. Round (r) is known to each and every node. 3.2 Energy Model We have considered first order of radio model as given in (Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000, January), Chen, G., Li, C., Ye, M., & Wu, J. (2009)) for communication energy expenditure. We have used free space model (d2 power loss) and multipath fading model (d4 power loss) where d is the distance between the transmitting and receiving nodes. The energy expenditure to transmit l-bit data packet over distance d is given by equation 6. (6) The electronics energy, Eelec, depends on factors such as the digital coding, and modulation, whereas the amplifier energy, l fsd2 or l fsd4, depends on the transmission distance and the acceptable bit-error rate (Chen, G., Li, C., Ye, M., & Wu, J. (2009)). To receive this message, the radio expends energy as given by equation 7. We have also assumed that a cluster head consumes EDA (nJ/bit/message) amount of energy for data aggregation. (7) 4. PROPOSED APPROACH Like LEACH, our proposed approach also works in rounds. Round is the duration for which a particular node works as a CH. Round consists of two phases. (a) Cluster Head election phase and (b) Steady State Phase. Both of these phases are described in the following subsections. 151
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International Journal of
Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 – 6464(Print), ISSN 0976 – 6472(Online), Volume 5, Issue 1, January (2014), © IAEME 4.1 Cluster Head Election Phase A node elects itself as a CH, if its node identifier (id) is within the set of node identifiers that should be a cluster head during a particular round; otherwise it works as a member node (non-CH node) for the current round i.e. if total nodes are 100 and desired percentage of cluster heads are set to 5% of the total nodes then first five nodes are elected as CHs during first round, nodes with the ids 6 to 10 would be elected as the cluster heads during second round; and so on. This process continues until all nodes become cluster heads. When all the nodes become cluster heads then the process repeats with nodes with ids 1 to 5 as the CHs. This process ensures that each node becomes a cluster head exactly once during 1/p rounds where p is the desired percentage of cluster heads. This proposed approach also ensures that desired percentage of cluster heads should be maintained until the death of first node. Once nodes are aware that they are elected as CHs during a particular round, they inform their status to the non-CH nodes within the network. Non-CH node associates with the one of the CH nodes for which minimum communication energy expenditure is required; and sends a join message to the selected CH. After getting join messages from the Non-CH nodes, CH nodes prepares TDMA schedule and inform to the member nodes of their own cluster. 4.2. Steady State Phase During the steady state phase, all non-CH nodes turn off their radio to save their energy, except the time slot for which they have to transmit data to CH. CHs perform data aggregation and send aggregated data to BS after receiving data from the member nodes. This data aggregation approach helps to save energy of the CH because less number of bits transmitted by CHs. At the end of Steady State phase a new round begins with CH election phase. There is a high energy drains for the cluster heads because they have to do CH announcement to the other nodes, reception of CH Join message, TDMA schedule announcement to the nodes who have sent CH Join messages, data reception from the member nodes and finally data transmission to BS after performing data aggregation. Thus, to enhance the network life time, role of the CH is rotated between all active nodes of the network. Thus, set of nodes xj who are the cluster head for the round j is different than the set of nodes xj-1 who had been cluster head for the previous round. 5. SIMULATION STRATEGY AND RESULT DISCUSSION We have simulated our proposed approach – S-LEACH and compared it with the LEACH, ALEACH and LDCHS protocols for a random network of 50 nodes, 100 nodes and 200 nodes uniformly deployed in a region of 100m x 100m with initial energy 0.25J/node, 0.5J/node and 0.75J/node. Simulation parameters used for the verification of the proposed approach is given in the Table 1. Table 1. Simulation Parameters Parameter Name Value Simulation Area 100m x 100m Total Nodes (1) 50 (2) 100 and (3) 200 Cluster Heads (in %) 5 Initial Energy (J/Node) (1) 0.25 (2) 0.5 (3) 0.75 Transmitter Electronics and Receiver 50 nJ/bit Electronics Transmit Amplifier 100 pJ/bit/m2 Energy for Data Aggregation 5nJ/bit/message Message Size 4000-bit 152
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International Journal of
Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 – 6464(Print), ISSN 0976 – 6472(Online), Volume 5, Issue 1, January (2014), © IAEME Figure 1. Death of Nodes and number of Cluster Heads for a network of 50 nodes with initial energy 0.25J/Node Figure 2. Number of Cluster Heads for S-LEACH algorithm for a network of 50 nodes with initial energy 0.25J/Node Figure 3. Number of Cluster Heads for ALEACH algorithm for a network of 50 nodes with initial energy 0.25J/Node Figure 4. Number of Cluster Heads for LEACH algorithm for a network of 50 nodes with initial energy 0.25J/Node Figure 5. Number of Cluster Heads for LDCHS algorithm for a network of 50 nodes with initial energy 0.25J/Node 153
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International Journal of
Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 – 6464(Print), ISSN 0976 – 6472(Online), Volume 5, Issue 1, January (2014), © IAEME Figure 6. Death of Nodes and number of Cluster Heads for a network of 50 nodes with initial energy 0.5J/Node Figure 7. Death of Nodes and number of Cluster Heads for a network of 50 nodes with initial energy 0.75J/Node Figure 8. Death of Nodes and number of Cluster Heads for a network of 100 nodes with initial energy 0.25J/Node 154
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International Journal of
Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 – 6464(Print), ISSN 0976 – 6472(Online), Volume 5, Issue 1, January (2014), © IAEME Figure 9. Death of Nodes and number of Cluster Heads for a network of 100 nodes with initial energy 0.5J/Node Figure 10. Death of Nodes and number of Cluster Heads for a network of 100 nodes with initial energy 0.75J/Node Figure 11. Death of Nodes and number of Cluster Heads for a network of 200 nodes with initial energy 0.25J/Node 155
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International Journal of
Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 – 6464(Print), ISSN 0976 – 6472(Online), Volume 5, Issue 1, January (2014), © IAEME Figure 12. Death of Nodes and number of Cluster Heads for a network of 200 nodes with initial energy 0.5J/Node Figure 13. Death of Nodes and number of Cluster Heads for a network of 200 nodes with initial energy 0.75J/Node We have shown death of nodes and number of cluster heads during each round in Figures 113 for a network of 50, 100 and 200 nodes with initial energy 0.25, 0.5 and 0.75 J/node. Simulation results show that First Node Dies (FND) is poor for the proposed approach compared to LEACH, LDCHS and ALEACH protocols. However, our proposed approach improves overall network lifetime. Also, number of cluster heads for S-LEACH, ALEACH, LEACH and LDCHS is shown separately in Figures 2-5 respectively and their comparative result is shown in Figure 1. S-LEACH maintains desired percentage of cluster heads during each round until the death of first node and same can be verified from Figure 2. This is the reason why S-LEACH outperforms to LEACH, LDCHS and ALEACH protocols 6. CONCLUSION In this paper, we have proposed S-LEACH protocol, which is distributed in nature, sustain with the node density and provides improved network lifetime compared to LEACH, LDCHS and ALEACH protocols. In S-LEACH, we have used sequential selection approach to maintain desired percentage of cluster heads during each round until the death of first node. Our protocol enhances overall network lifetime compared to LEACH, LDCHS and ALEACH but First Node Dies (FND) is not as good as LEACH, LDCHS and ALEACH. 156
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International Journal of
Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 – 6464(Print), ISSN 0976 – 6472(Online), Volume 5, Issue 1, January (2014), © IAEME REFERENCES 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000, January). Energy-efficient communication protocol for wireless microsensor networks. InSystem Sciences, 2000. Proceedings of the 33rd Annual Hawaii International Conference on (pp. 10-pp). IEEE. Wang, A., Yang, D., & Sun, D. (2012). A clustering algorithm based on energy information and cluster heads expectation for wireless sensor networks. Computers & Electrical Engineering, 38(3), 662-671. Ye, M., Li, C., Chen, G., & Wu, J. (2005, April). EECS: an energy efficient clustering scheme in wireless sensor networks. In Performance, Computing, and Communications Conference, 2005. IPCCC 2005. 24th IEEE International (pp. 535-540). IEEE. Kumar, D., Aseri, T. C., & Patel, R. B. (2009). EEHC: Energy efficient heterogeneous clustered scheme for wireless sensor networks. Computer Communications, 32(4), 662-667. Yassein, M. B., A. Al-zou'bi, Khamayseh, Y., & Mardini, W. (2009). Improvement on LEACH Protocol of Wireless Sensor Network (VLEACH).JDCTA, 3(2), 132-136. Thakkar, A., & Kotecha, K. (2012). CVLEACH: Coverage based energy efficient LEACH Algorithm. International Journal of Computer Science and Network (IJCSN) Volume, 1. Ali, M. S., Dey, T., & Biswas, R. (2008, December). ALEACH: Advanced LEACH routing protocol for wireless microsensor networks. In Electrical and Computer Engineering, 2008. ICECE 2008. International Conference on (pp. 909-914). IEEE. Thakkar, A., & Kotecha, K. (2012). Computer Science & Information Technology (CS & IT). WALEACH: Weight Based Energy Efficient Advanced LEACH Algorithm, 2 (4), 117130. Thakkar, A., & Kotecha, K. (2012). WCVALEACH: Weight and Coverage Based Energy Efficient Advanced LEACH Algorithm. Computer Science & Engineering, 2(6). Kim, K. T., & Youn, H. Y. (2005, January). Energy-driven adaptive clustering hierarchy (EDACH) for wireless sensor networks. In Embedded and Ubiquitous Computing–EUC 2005 Workshops (pp. 1098-1107). Springer Berlin Heidelberg. Sehgal, L., & Choudhary, V. (2011). REEH: Residual Energy Efficient Heterogeneous Clustered Hierarchy Protocol for Wireless Sensor Networks. International Journal of Scientific & Engineering Research, 2(12), 1-5. Loscri, V., Morabito, G., & Marano, S. (2005, September). A two-level hierarchy for lowenergy adaptive clustering hierarchy (TL-LEACH). In IEEE Vehicular Technology Conference (Vol. 62, No. 3, p. 1809). IEEE; 1999. Handy, M. J., Haase, M., & Timmermann, D. (2002). Low energy adaptive clustering hierarchy with deterministic cluster-head selection. In Mobile and Wireless Communications Network, 2002. 4th International Workshop on (pp. 368-372). IEEE. Chen, G., Li, C., Ye, M., & Wu, J. (2009). An unequal cluster-based routing protocol in wireless sensor networks. Wireless Networks, 15(2), 193-207. Rashid M. Awadi, Rawya Y. Rizk, Mohamed I. Habib and Amira A. M. Elsonbaty, “An Efficient Cluster Head Selection Scheme for Dynamic Sleep Time in Wireless Sensor Network”, International Journal of Electronics and Communication Engineering & Technology (IJECET), Volume 4, Issue 6, 2013, pp. 1 - 13, ISSN Print: 0976- 6464, ISSN Online: 0976 –6472. Ankit Thakkar and Ketan Kotecha, “A New Enhanced Leach Routing Protocol for Wireless Sensor Network Based on Gaussian Distribution of Random Numbers”, International Journal of Advanced Research in Engineering & Technology (IJARET), Volume 4, Issue 7, 2013, pp. 207 - 215, ISSN Print: 0976-6480, ISSN Online: 0976-6499. 157
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