Modified Energy and Link Failure Recovery Routing Algorithm for Wireless Sensor Network
Wireless sensor network finds role in environmental monitoring, industrial applications, surveillance applications, health monitoring and other supervisory applications. Sensing devices form the basic operational unit of the network that is self-battery powered with limited life time. Sensor node spends its limited energy for transmission, reception, routing and sensing information. Frequent energy utilization for the above mentioned process leads to network lifetime degradation. To enhance energy efficiency and network lifetime, we propose a modified energy optimization and node recovery post failure method, Energy-Link Failure Recovery Routing (E-LFRR) algorithm. In our E-LFRR algorithm, two phases namely, Monitored Transmission phase and Replaced Transmission phase are devised to combat worst case link failure conditions. In Monitored Transmission phase, the Actuator Node monitors and identifies suitable nodes for shortest path transmission. The Replaced Transmission phase dispatches the energy draining node at early stage from the active link and replaces it with the new node that has sufficient energy. Simulation results illustrate that this combined methodology reduces overhead, energy consumption, delay and maintains considerable amount of alive nodes thereby enhancing the network performance.
[1] Alemdar, A., & Ibnkahla, M, “Wireless sensor networks: Applications and challenges”, 2007 9th International Symposium on Signal Processing and Its Applications, 2007.
[2] Qaisar, S. B., Ali, S., & Felemban, E. A., “Wireless Sensor Networks in Next Generation Communication Infrastructure: Vision and Challenges”, International Conference on Computational Science and Its Applications, Springer International Publishing, pp. 790-803, 2014.
[3] Chakraborty, A., Mitra, S. K., & Naskar, M. K., “Energy efficient routing in wireless sensor networks: A genetic approach”, CoRR abs/1105.2090, 2011.
[4] Zeng, W. Church, R. L., “Finding shortest paths on real road networks: the case for A*”. International Journal of Geographical Information Science. 23(4), 531–543, 2013. doi:10.1080/13658810801949850.
[5] Ghaffari, A., “An energy efficient routing protocol for wireless sensor networks using A-star algorithm”, Journal of applied research and technology,12(4), 815-822, 2014.
[6] Devi, C. Y., Shivaraj, B., Manjula, S. H., Venugopal, K. R., & Patnaik, L. M., “EESOR: Energy efficient selective opportunistic routing in wireless sensor networks” International Conference on Security in Computer Networks and Distributed Systems (pp. 16-31). Springer Berlin Heidelberg, 2014.
[7] Amiri, E., Keshavarz, H., Alizadeh, M., Zamani, M., & Khodadadi, T., “Energy efficient routing in wireless sensor networks based on fuzzy ant colony optimization”, International Journal of Distributed Sensor Networks, 2014.
[8] Sarma, H. K. D., Mall, R., & Kar, A, “E2R2: Energy-Efficient and Reliable Routing for Mobile Wireless Sensor Networks”, IEEE Systems Journal, vol. 10, no. 2, pp. 604-616, April 2015.
[9] Mishra, S., & Kaur, P. “Energy efficient neighbour selection for flat wireless sensor networks” arXiv preprint arXiv:1406.3550, 2014.
[10] Raj, D. A. A., & Sumathi, P, “Enhanced energy efficient multipath routing protocol for wireless sensor communication networks using cuckoo search algorithm”, Wireless Sensor Network, 6(04), 49, 2014.
[11] Abbasi, A. A., Younis, M. F., & Baroudi, U. A., “Recovering from a node failure in wireless sensor-actor networks with minimal topology changes”, IEEE Transactions on vehicular technology, 62(1), 256-271, 2013.
[12] Bakr, B. A., & Lilien, L. T, “Extending lifetime of wireless Sensor networks by management of spare nodes”, Procedia Computer Science, 34, pp. 493-498, 2014.
[13] Rao, M., & Singh, N., “Quality of service enhancement in MANETs with an efficient routing algorithm”, IEEE International Advance Computing Conference (IACC), 2014 pp. 381-384) IEEE, 2014.
[14] Naik, K. H., & Reddy, V. R., “Comparative Performance of PRO-AODV, DFRR, CPRR algorithm based on Link Failure Route Rectification problem in Mobile Sensor Network”, International Research Journal of Eng. and Technology, vol. 2, no. 9, pp. 2558-2564, 2015.
[15] Roy, A., & Sarma, N., “Performance Evaluation of Synchronous Energy Efficient MAC Protocols for Wireless Sensor Networks”, Procedia Technology, 6, pp-806-813, 2012.
[16] Rout, R. R., & Ghosh, S. K., “Enhancement of lifetime using duty cycle and network coding in wireless sensor networks”, IEEE Transactions on Wireless Communications, vol. 12 no. 2, 656-667, 2013.
[17] Gnanambigai, M. J., ME, D., & Umamaheswari, M.C, “Energy Optimization in Wireless Sensor Network Using Sleep Mode Transceiver”, Global Journal of Research in Engineering, vol. 11, no. 3, 2011.
[18] Hsueh, C. T., Wen, C. Y., & Ouyang, Y. C. , “A Secure Scheme Against Power Exhausting Attacks in Hierarchical Wireless Sensor Networks”, IEEE Sensors journal, vol. 15, no.6, 3590-3602, 2015.
[19] Maleki, M., Dantu, K., & Pedram, M., “Lifetime prediction routing in mobile ad hoc networks” 2003 IEEE Wireless Communications and Networking, 2003, vol. 2, pp. 1185-1190, 2003.
[20] Saraswat, J., & Bhattacharya, P. P., “Effect of duty cycle on energy consumption in wireless sensor networks”, International Journal of Computer Networks & Communications, 5(1), 125, 2013.
[21] Kim, H. W., & Kachroo, A, “Low Power Routing and Channel Allocation of Wireless Video Sensor Networks Using Wireless Link Utilization”, Ad Hoc & Sensor Wireless Networks, 30(1-2), 83-112, 2016.
[1] Alemdar, A., & Ibnkahla, M, “Wireless sensor networks: Applications and challenges”, 2007 9th International Symposium on Signal Processing and Its Applications, 2007.
[2] Qaisar, S. B., Ali, S., & Felemban, E. A., “Wireless Sensor Networks in Next Generation Communication Infrastructure: Vision and Challenges”, International Conference on Computational Science and Its Applications, Springer International Publishing, pp. 790-803, 2014.
[3] Chakraborty, A., Mitra, S. K., & Naskar, M. K., “Energy efficient routing in wireless sensor networks: A genetic approach”, CoRR abs/1105.2090, 2011.
[4] Zeng, W. Church, R. L., “Finding shortest paths on real road networks: the case for A*”. International Journal of Geographical Information Science. 23(4), 531–543, 2013. doi:10.1080/13658810801949850.
[5] Ghaffari, A., “An energy efficient routing protocol for wireless sensor networks using A-star algorithm”, Journal of applied research and technology,12(4), 815-822, 2014.
[6] Devi, C. Y., Shivaraj, B., Manjula, S. H., Venugopal, K. R., & Patnaik, L. M., “EESOR: Energy efficient selective opportunistic routing in wireless sensor networks” International Conference on Security in Computer Networks and Distributed Systems (pp. 16-31). Springer Berlin Heidelberg, 2014.
[7] Amiri, E., Keshavarz, H., Alizadeh, M., Zamani, M., & Khodadadi, T., “Energy efficient routing in wireless sensor networks based on fuzzy ant colony optimization”, International Journal of Distributed Sensor Networks, 2014.
[8] Sarma, H. K. D., Mall, R., & Kar, A, “E2R2: Energy-Efficient and Reliable Routing for Mobile Wireless Sensor Networks”, IEEE Systems Journal, vol. 10, no. 2, pp. 604-616, April 2015.
[9] Mishra, S., & Kaur, P. “Energy efficient neighbour selection for flat wireless sensor networks” arXiv preprint arXiv:1406.3550, 2014.
[10] Raj, D. A. A., & Sumathi, P, “Enhanced energy efficient multipath routing protocol for wireless sensor communication networks using cuckoo search algorithm”, Wireless Sensor Network, 6(04), 49, 2014.
[11] Abbasi, A. A., Younis, M. F., & Baroudi, U. A., “Recovering from a node failure in wireless sensor-actor networks with minimal topology changes”, IEEE Transactions on vehicular technology, 62(1), 256-271, 2013.
[12] Bakr, B. A., & Lilien, L. T, “Extending lifetime of wireless Sensor networks by management of spare nodes”, Procedia Computer Science, 34, pp. 493-498, 2014.
[13] Rao, M., & Singh, N., “Quality of service enhancement in MANETs with an efficient routing algorithm”, IEEE International Advance Computing Conference (IACC), 2014 pp. 381-384) IEEE, 2014.
[14] Naik, K. H., & Reddy, V. R., “Comparative Performance of PRO-AODV, DFRR, CPRR algorithm based on Link Failure Route Rectification problem in Mobile Sensor Network”, International Research Journal of Eng. and Technology, vol. 2, no. 9, pp. 2558-2564, 2015.
[15] Roy, A., & Sarma, N., “Performance Evaluation of Synchronous Energy Efficient MAC Protocols for Wireless Sensor Networks”, Procedia Technology, 6, pp-806-813, 2012.
[16] Rout, R. R., & Ghosh, S. K., “Enhancement of lifetime using duty cycle and network coding in wireless sensor networks”, IEEE Transactions on Wireless Communications, vol. 12 no. 2, 656-667, 2013.
[17] Gnanambigai, M. J., ME, D., & Umamaheswari, M.C, “Energy Optimization in Wireless Sensor Network Using Sleep Mode Transceiver”, Global Journal of Research in Engineering, vol. 11, no. 3, 2011.
[18] Hsueh, C. T., Wen, C. Y., & Ouyang, Y. C. , “A Secure Scheme Against Power Exhausting Attacks in Hierarchical Wireless Sensor Networks”, IEEE Sensors journal, vol. 15, no.6, 3590-3602, 2015.
[19] Maleki, M., Dantu, K., & Pedram, M., “Lifetime prediction routing in mobile ad hoc networks” 2003 IEEE Wireless Communications and Networking, 2003, vol. 2, pp. 1185-1190, 2003.
[20] Saraswat, J., & Bhattacharya, P. P., “Effect of duty cycle on energy consumption in wireless sensor networks”, International Journal of Computer Networks & Communications, 5(1), 125, 2013.
[21] Kim, H. W., & Kachroo, A, “Low Power Routing and Channel Allocation of Wireless Video Sensor Networks Using Wireless Link Utilization”, Ad Hoc & Sensor Wireless Networks, 30(1-2), 83-112, 2016.
@article{"International Journal of Electrical, Electronic and Communication Sciences:77432", author = "M. Jayekumar and V. Nagarajan", title = "Modified Energy and Link Failure Recovery Routing Algorithm for Wireless Sensor Network", abstract = "Wireless sensor network finds role in environmental monitoring, industrial applications, surveillance applications, health monitoring and other supervisory applications. Sensing devices form the basic operational unit of the network that is self-battery powered with limited life time. Sensor node spends its limited energy for transmission, reception, routing and sensing information. Frequent energy utilization for the above mentioned process leads to network lifetime degradation. To enhance energy efficiency and network lifetime, we propose a modified energy optimization and node recovery post failure method, Energy-Link Failure Recovery Routing (E-LFRR) algorithm. In our E-LFRR algorithm, two phases namely, Monitored Transmission phase and Replaced Transmission phase are devised to combat worst case link failure conditions. In Monitored Transmission phase, the Actuator Node monitors and identifies suitable nodes for shortest path transmission. The Replaced Transmission phase dispatches the energy draining node at early stage from the active link and replaces it with the new node that has sufficient energy. Simulation results illustrate that this combined methodology reduces overhead, energy consumption, delay and maintains considerable amount of alive nodes thereby enhancing the network performance.
", keywords = "Actuator node, energy efficient routing, energy hole, link failure recovery, link utilization, wireless sensor network.", volume = "11", number = "11", pages = "1172-7", }
