Abstract
One of the most critical and challenging issues when developing wireless sensor networks (WSNs) is how to extend the network lifetime. Sensors are energy-constrained devices that require developing minimization techniques and mechanisms in order to exploit perfectly the energy and to prolong as long as possible the overall network lifetime. In this paper, we propose a limited energy consumption model for P2P wireless sensor networks, which takes a benefit of the Chord assets and adapts this last one so that it will be suitable for P2P WSNs. Chord in its basic form optimizes the path length by minimizing the number of hops, but it does not optimize the energy, since it was designed for wired networks. The key idea of our proposal is to optimize both the number of hops and the energy consumption to provide an energy-efficient routing scheme for P2P WSNs. The proposed enhanced Chord scheme makes a use of only Cluster-Heads (with the strongest level of energy) to construct the ring, which reduces the Chord topology while preserving the network connectivity. In the enhanced Chord scheme, Cluster-Heads are elected automatically and dynamically over the time, which helps to extend the network longevity. Simulation results show that the proposed scheme proves good performances in terms of hops number, alive nodes over the time and energy efficiency.
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Naik, P., Telkar, N., & Kotin, K. (2016). Survey on wireless sensor network with their remaining challenges. IJSRST, 2(6), 321–331. doi:15.11/IJSRST162658.
Yetgin, H., Cheung, K. T. K., El-Hajjar, M., & Hanzo, L. (2017). A survey of network lifetime maximization techniques. IEEE Communications Surveys & Tutorials. doi:10.1109/COMST.2017.2650979.
Amad, M., Aissani, D., Meddahi, A., Benkerrou, M., & Amghar, F. (2015). De Bruijn graph based solution for lookup acceleration and optimization in P2P networks. Journal of Wireless Personal Communications, 85(3), 1471–1486.
Cherbal, S., Boukerram, A., & Boubetra, A. (2016). A survey of DHT solutions in fixed and mobile networks. International Journal of Communication Networks and Distributed Systems, 17(1), 14–42.
Zuo, X., & Iamnitchi, A. (2016). A survey of socially aware peer-to-peer systems. ACM Computing Surveys (CSUR), 49(1), 1–28.
Meshkova, E., Riihijärvi, J., Petrova, M., & Mähönen, P. (2008). A survey on resource discovery mechanisms, peer-to-peer and service discovery frameworks. Computer Networks, 52(11), 2097–2128.
Stoica, I., Morris, R., Liben-Nowell, D., Karger, D., Dabek, F., & Balakrishnan, H. (2003). Chord: A scalable peer-to-peer lookup protocol for internet applications. IEEE/ACM Transactions on Networking, 11(1), 17–32.
Rashid, B., & Rehmani, M. H. (2016). Applications of wireless sensor networks for urban areas: A survey. Journal of Network and Computer Applications, 60, 192–219.
Sunita, M., Malik, J., & Mor, S. (2012). Comprehensive study of applications of wireless sensor network. International Journal of Advanced Research in Computer Science and Software Engineering, 2(11). ISSN 2277.
Boudries, A., Amad, M., & Siarry, P. (2016). Novel approach for replacement of a failure node in wireless sensor network. Journal of Telecommunication Systems. doi:10.1007/s11235-016-0236-5.
Xu, Y., Heidemann, J., & Estrin, D. (2001). Geography-informed energy conservation for ad hoc routing. In Proceedings of the 7th annual international conference on mobile computing and networking. ACM, pp. 70–84.
Schurgers, C., Tsiatsis, V., & Srivastava, M. B. (2002). STEM: Topology management for energy efficient sensor networks. In Aerospace conference proceedings, Vol, 3. IEEE, pp. 1099–1108.
Cerpa, A., & Estrin, D. (2004). ASCENT: Adaptive self-configuring sensor networks topologies. IEEE Transactions on Mobile Computing, 3(3), 272–285.
Lee, J. H. (2013). A traffic-aware energy efficient scheme for WSN employing an adaptable wakeup period. Wireless Personal Communications, 71(3), 1879–1914.
Xie, R., Liu, A., & Gao, J. (2016). A residual energy aware schedule scheme for WSNs employing adjustable awake/sleep duty cycle. Wireless Personal Communications, 90(4), 1859–1887.
Rodoplus, V., & Meng, T. H. (1999). Minimum energy mobile wireless networks. IEEE Journal on Selected Areas in Communications, 17(8), 1333–1344.
Li, L., & Halpern, J. Y. (2004). A minimum-energy path-preserving topology-control algorithm. IEEE Transactions on Wireless Communications, 3(3), 910–921.
Narayanaswamy, S., Kawadia, V., Sreenivas, R. S., & Kumar, P. (2002). Power control in ad-hoc networks: Theory, architecture, algorithm and implementation of the COMPOW protocol. In European wireless conference, Vol. 202, pp. 156–162.
Ahmed, G., & Khan, N. M. (2017). Adaptive power-control based energy-efficient routing in wireless sensor networks. Wireless Personal Communications, 94(3), 1297–1329. doi:10.1007/s11277-016-3683-0.
Du, D. Z., & Pardalos, P. M. (Eds.). (2013). Handbook of combinatorial optimization: Supplement (Vol. 1). Springer US. doi:10.1007/978-1-4757-3023-4.
Wu, J., Dai, F., Gao, M., & Stojmenovic, I. (2002). On calculating power-aware connected dominating sets for efficient routing in ad hoc wireless networks. Journal of Communications and Networks, 4(1), 59–70.
Yuanyuan, Z., Jia, X., & Yanxiang, H. (2006). Energy efficient distributed connected dominating sets construction in wireless sensor networks. In Proceedings of the 2006 international conference on Wireless communications and mobile computing. ACM, pp. 797–802.
Labrador, M. A., & Wightman, P. M. (2009). Topology control in wireless sensor networks: With a companion simulation tool for teaching and research. Springer Netherlands. doi:10.1007/978-1-4020-9585-6.
Bao, L., & Garcia-Luna-Aceves, J. J. (2003). Topology management in ad hoc networks. In Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing. ACM, USA, pp. 129–140.
Shanavas, J., & Simi, S. (2014). An energy efficient topology control scheme with connectivity learning in wireless networks. In International conference on advances in computing, communications and informatics, (ICACCI). IEEE, pp. 1770–1774.
Thenmozhi, E., & Audithan, S. (2016). Energy efficient cluster head selection and data convening in wireless sensor networks. Indian Journal of Science and Technology, 9(15). doi:10.17485/ijst/2016/v9i15/77749.
Alippi, C., Anastasi, G., Francesco, M. D., & Roveri, M. (2010). An adaptive sampling algorithm for effective energy management in wireless sensor networks with energy-hungry sensors. IEEE Transactions on Instrumentation and Measurement, 59(2), 335–344.
Fateh, B., & Govindarasu, M. (2013). Energy minimization by exploiting data redundancy in real-time wireless sensor networks. Ad Hoc Networks, 11(6), 1715–1731.
Sudevalayam, S., & Kulkarni, P. (2011). Energy harvesting sensor nodes: Survey and implications. IEEE Communications Surveys & Tutorials, 13(3), 443–461.
Chen, B., Jamieson, K., Balakrishnan, H., & Morris, R. (2002). Span: An energy-efficient coordination algorithm for topology maintenance in ad hoc wireless networks. Wireless Networks, 8(5), 481–494.
Kawadia, V., & Kumar, P. R. (2003). Power control and clustering in ad hoc networks. In INFOCOM 2003. Twenty-second annual joint conference of the IEEE computer and communications, IEEE Societies, Vol. 1, pp. 459–469.
Akkari, W., Bouhdid, B., & Belghith, A. (2015). LEATCH: Low energy adaptive tier clustering hierarchy. Procedia Computer Science, 52, 365–372.
Fersi, G., Louati, W., & Jemaa, M. B. (2013). Distributed Hash table-based routing and data management in wireless sensor networks: A survey. Wireless Networks, 19(2), 219–236.
Busnel, Y. (2008). SOLIST : Structure multi-couche pair-à-pair à faible consommation pour les rśeaux de capteurs sans-fil. In Proceedings, Conférence Francophone sur les Systèmes d’Exploitation-6‘eme édition, (CFSE’6), Suisse.
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Cheklat, L., Amad, M. & Boukerram, A. A Limited Energy Consumption Model for P2P Wireless Sensor Networks. Wireless Pers Commun 96, 6299–6324 (2017). https://doi.org/10.1007/s11277-017-4478-7
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DOI: https://doi.org/10.1007/s11277-017-4478-7