SRG: Energy-Efficient Localized Routing to Bypass Void in Wireless Sensor Networks
Abstract The Shift Reverse Gradient (SRG) approach presents a void-size-independent hole bypassing scheme for wireless sensor networks. It does not require establishing any chain or hierarchical tree structure to ensure reliable delivery. The proposed Shift Reverse Gradient (SRG) offers an energy-efficient solution with minimal overhead and consumes minimum power. It has a communication overhead equivalent to greedy forwarding. We have shown through the simulation that SRG energy consumption is minimal and is not much affected by an increase in the void size like other existing void bypassing methods.
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Liu, W.-J. and Feng, K.-T., 2008. Greedy routing with anti-void traversal for wireless sensor networks. IEEE transactions on mobile computing, 8(7), 910–922. 10.1109/TMC.2008.162
Mostefaoui, A., Melkemi, M., and Boukerche, A., 2013. Localized routing approach to bypass holes in wireless sensor networks. IEEE transactions on computers, 63(12), 3053–3065. 10.1109/TC.2013.180
de Oliveira, H. A., Boukerche, A., Guidoni, D. L., Nakamura, E. F., Mini, R. A., and Loureiro, A. A., 2015. An enhanced location-free Greedy Forward algorithm with hole bypass capability in wireless sensor networks. Journal of Parallel and Distributed Computing, 77, 1–10. 10.1016/j.jpdc.2014.10.007
Rekik, M., Mitton, N., and Chtourou, Z., 2018. GRACO: a geographic greedy routing with an ACO based void handling technique. International Journal of Sensor Networks, 26(3), 145–161. 10.1504/IJSNET.2018.090148
Savvides, A. and Strivastava, M. B., 2003. Distributed fine-grained localization in ad-hoc networks. IEEE Transactions of Mobile Computing.
Toussaint, G. T., 1980. The relative neighbourhood graph of a finite planar set. Pattern recognition, 12(4), 261–268. 10.1016/0031-3203(80)90066-7
Yilmaz, O., Dagdeviren, O., and Erciyes, K., 2014. Localization-free and energy-efficient hole bypassing techniques for fault-tolerant sensor networks. Journal of network and computer applications, 40, 164–178. 10.1016/j.jnca.2013.09.002
Zhang, D. and Dong, E., 2015. A virtual coordinate-based bypassing void routing for wireless sensor networks. IEEE sensors journal, 15(7), 3853–3862. 10.1109/JSEN.2015.2398852
Arad, N. and Shavitt, Y., 2008. Minimizing recovery state in geographic ad hoc routing. IEEE Transactions on Mobile Computing, 8(2), 203–217. 10.1109/TMC.2008.86
Bahi, J. M., Makhoul, A., and Mostefaoui, A., 2008. Localization and coverage for high density sensor networks. Computer Communications, 31(4), 770–781. 10.1109/PERCOMW.2007.61
Boukerche, A., Turgut, B., Aydin, N., Ahmad, M. Z., Bölöni, L., and Turgut, D., 2011. Routing protocols in ad hoc networks: A survey. Computer networks, 55(13), 3032–3080. 10.1016/j.comnet.2011.05.010
Chen, S., Fan, G., and Cui, J.-H., 2006. Avoid’void’in geographic routing for data aggregation in sensor networks. International Journal of Ad Hoc and Ubiquitous Computing, 1(4), 169–178. 10.1504/IJAHUC.2006.010498
De Couto, D. S. and Morris, R., 2001. Location proxies and intermediate node forwarding for practical geographic forwarding.
Gabriel, K. R. and Sokal, R. R., 1969. A new statistical approach to geographic variation analysis. Systematic zoology, 18(3), 259–278. 10.2307/2412323
He, T., Stankovic, J. A., Abdelzaher, T. F., and Lu, C., 2005. A spatiotemporal communication protocol for wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 16(10), 995–1006. 10.1109/TPDS.2005.116
Hou, J. and Zhang, Y., 2018. Mobile-service based approach for topology control of wireless sensor networks. Wireless Personal Communications, 102(2), 1839–1851. 10.1109/TPDS.2005.116
Hu, X., Ma, L., Ding, Y., Xu, J., Li, Y., and Ma, S., 2019. Fuzzy logic-based geographic routing protocol for dynamic wireless sensor networks. Sensors, 19(1), 196. 10.3390/s19010196
Huang, H., Yin, H., Min, G., Zhang, J., Wu, Y., and Zhang, X., 2017. Energy-aware dual-path geographic routing to bypass routing holes in wireless sensor networks. IEEE Transactions on Mobile Computing, 17(6), 1339–1352. 10.1109/TMC.2017.2771424
Jiang, Z., Ma, J., Lou, W., and Wu, J., 2008. An information model for geographic greedy forwarding in wireless ad-hoc sensor networks. In IEEE INFOCOM 2008-The 27th Conference on Computer Communications, pages 825–833. IEEE. 10.1109/INFOCOM.2008.134
Joshi, G. P. and Kim, S. W., 2009. A distributed geo-routing algorithm for wireless sensor networks. Sensors, 9(6), 4083–4103. 10.3390/s90604083
Karp, B. and Kung, H.-T., 2000. GPSR: Greedy perimeter stateless routing for wireless networks. In Proceedings of the 6th annual international conference on Mobile computing and networking, pages 243–254. 10.1145/345910.345953
Kim, S., Kim, C., Cho, H., Yim, Y., and Kim, S.-H., 2016. Void avoidance scheme for real-time data dissemination in irregular wireless sensor networks. In 2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA), pages 438–443. IEEE. 10.1109/AINA.2016.59
Kuhn, F., Wattenhofer, R., and Zollinger, A., 2008. An algorithmic approach to geographic routing in ad hoc and sensor networks. IEEE/ACM Transactions On Networking, 16(1), 51–62. 10.1109/TNET.2007.900372
Le Nguyen, P., Nguyen, N. H., Dinh, T. A. N., Le, K., Nguyen, T. H., and Nguyen, K., 2021. QIH: An Efficient Q-Learning Inspired Hole-Bypassing Routing Protocol for WSNs. IEEE Access, 9:123414–123429. 10.1109/ACCESS.2021.3108156
Lima, M. M., Oliveira, H. A., Guidoni, D. L., and Loureiro, A. A., 2017. Geographic routing and hole bypass using long range sinks for wireless sensor networks. Ad Hoc Networks, 67, 1–10. 10.1016/j.adhoc.2017.08.010
Liu, W.-J. and Feng, K.-T., 2008. Greedy routing with anti-void traversal for wireless sensor networks. IEEE transactions on mobile computing, 8(7), 910–922. 10.1109/TMC.2008.162
Mostefaoui, A., Melkemi, M., and Boukerche, A., 2013. Localized routing approach to bypass holes in wireless sensor networks. IEEE transactions on computers, 63(12), 3053–3065. 10.1109/TC.2013.180
de Oliveira, H. A., Boukerche, A., Guidoni, D. L., Nakamura, E. F., Mini, R. A., and Loureiro, A. A., 2015. An enhanced location-free Greedy Forward algorithm with hole bypass capability in wireless sensor networks. Journal of Parallel and Distributed Computing, 77, 1–10. 10.1016/j.jpdc.2014.10.007
Rekik, M., Mitton, N., and Chtourou, Z., 2018. GRACO: a geographic greedy routing with an ACO based void handling technique. International Journal of Sensor Networks, 26(3), 145–161. 10.1504/IJSNET.2018.090148
Savvides, A. and Strivastava, M. B., 2003. Distributed fine-grained localization in ad-hoc networks. IEEE Transactions of Mobile Computing.
Toussaint, G. T., 1980. The relative neighbourhood graph of a finite planar set. Pattern recognition, 12(4), 261–268. 10.1016/0031-3203(80)90066-7
Yilmaz, O., Dagdeviren, O., and Erciyes, K., 2014. Localization-free and energy-efficient hole bypassing techniques for fault-tolerant sensor networks. Journal of network and computer applications, 40, 164–178. 10.1016/j.jnca.2013.09.002
Zhang, D. and Dong, E., 2015. A virtual coordinate-based bypassing void routing for wireless sensor networks. IEEE sensors journal, 15(7), 3853–3862. 10.1109/JSEN.2015.2398852
Singh, S., Singh, S., & Prakash, J. (2023). SRG: Energy-Efficient Localized Routing to Bypass Void in Wireless Sensor Networks. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 12(1), e30865. https://doi.org/10.14201/adcaij.30865
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