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http://dx.doi.org/10.3837/tiis.2018.10.007

A Rendezvous Node Selection and Routing Algorithm for Mobile Wireless Sensor Network  

Hu, Yifan (Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences))
Zheng, Yi (Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences))
Wu, Xiaoming (Qilu University of Technology (Shandong Academy of Sciences), Shandong Computer Science Center (National Supercomputer Center in Jinan), Shandong Provincial Key Laboratory of Computer Networks)
Liu, Hailin (Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences))
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.12, no.10, 2018 , pp. 4738-4753 More about this Journal
Abstract
Efficient rendezvous node selection and routing algorithm (RNSRA) for wireless sensor networks with mobile sink that visits rendezvous node to gather data from sensor nodes is proposed. In order to plan an optimal moving tour for mobile sink and avoid energy hole problem, we develop the RNSRA to find optimal rendezvous nodes (RN) for the mobile sink to visit. The RNSRA can select the set of RNs to act as store points for the mobile sink, and search for the optimal multi-hop path between source nodes and rendezvous node, so that the rendezvous node could gather information from sensor nodes periodically. Fitness function with several factors is calculated to find suitable RNs from sensor nodes, and the artificial bee colony optimization algorithm (ABC) is used to optimize the selection of optimal multi-hop path, in order to forward data to the nearest RN. Therefore the energy consumption of sensor nodes is minimized and balanced. Our method is validated by extensive simulations and illustrates the novel capability for maintaining the network robustness against sink moving problem, the results show that the RNSRA could reduce energy consumption by 6% and increase network lifetime by 5% as comparing with several existing algorithms.
Keywords
Wireless sensor network; mobile sink; tour plan; rendezvous node; artificial bee colony;
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Times Cited By KSCI : 2  (Citation Analysis)
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1 K. Saleem, A. Derhab, J. Al-Muhtadi, M. A. Orgun, "Analyzing ant colony optimization based routing protocol against the hole problem for enhancing user's connectivity experience," Computers in Human Behavior, vol. 51, pp. 1340-1350, 2015.   DOI
2 B. Zhang, Y. Wang, H. Wang, X. Guan, Z. Zhuang, "Tracking a duty-cycled autonomous underwater vehicle by underwater wireless sensor networks," IEEE Access, vol. 5, pp.18016-18032, 2017.   DOI
3 Y. F. Hu, Y. S. Ding, K. R. Hao, H. Han, "An endocrine cooperative particle swarm optimization algorithm for routing recovery problem of wireless sensor networks with multiple mobile sinks, " Information Sciences, vol. 300, pp. 100-113, 2015.   DOI
4 C. Tunca, S. Isik, M. Y. Donmez, and C. Ersoy, "Distributed mobile sink routing for wireless sensor networks: A survey," IEEE Communications Surveys & Tutorials, vol. 16, no. 2, pp. 877-897, 2014.   DOI
5 Y. S. Jiang, W. R. Shi, X. G. Wang and H. B. Li, "A distributed routing for wireless sensor networks with mobile sink based on the greedy embedding," Ad Hoc Networks, vol. 20, pp. 150-162, 2014.   DOI
6 W. Cai, M. Zhang, "3D Dubins curves based path programming for mobile sink in underwater sensor networks," Electronics Letters, 53(1) :48-50, 2016.   DOI
7 M. Abo-Zahhad, S. M. Ahmed, N. Sabor, and S. Sasaki, "Mobile sink-based adaptive immune energy efficient clustering protocol for improving the lifetime and stability period of wireless sensor networks," IEEE Sensors Journal, vol. 15, no. 8, pp. 4576-4586, 2015.   DOI
8 J. Y. Chang, T. H. Shen, "An efficient tree-based power saving scheme for wireless sensor networks with mobile sink," IEEE Sensors Journal, vol. 16, no. 20, pp. 7545-7557, 2016.   DOI
9 H. Salarian, C. Kwan-Wu; F. Naghdy, "An energy-efficient mobile-sink path selection strategy for wireless sensor networks," IEEE Trans. Vehicular Technology, vol. 63, no. 5, pp. 2407-2419, 2014.   DOI
10 S. Mottaghi, M. R. Zahabi, "Optimizing LEACH clustering algorithm with mobile sink and rendezvous nodes," AEU - International Journal of Electronics and Communications, vol. 69, no. 2, pp. 507-514, 2015.   DOI
11 B. Suh and S. Berber, "Rendezvous points and routing path-selection strategies for wireless sensor networks with mobile sink," Electronics Letters, vol. 52, no. 2, pp. 167-169, 2016.   DOI
12 R. S. Chang, S. H. Wang, S. L. Tsai, W. P. Yang, "Planning rendezvous using the Halin graph in wireless sensor networks," Wireless Sensor Systems, IET, vol. 2, no. 3, pp. 222-229, 2012.   DOI
13 E. Lim, B. Kim and H. Min, "An energy efficient rendezvous node selection approach," in Proc. of 2017 International Conference on Information Networking (ICOIN), pp. 423-425, 2017.
14 A. Sharifkhani, N. C. Beaulieu, "A mobile-sink-based packet transmission scheduling algorithm for dense wireless sensor networks," IEEE Trans. Vehicular Technology, vol. 58, no. 5, pp. 2509-2518, 2009.   DOI
15 R. Sugihara and R. Gupta, "Improving the data delivery latency in sensor networks with controlled mobility," Distributed Computing in Sensor Systems, pp. 386-399, 2008.
16 G. L. Xing, T. Wang, Z. H. Xie, and W. J. Jia, "Rendezvous planning in wireless sensor networks with mobile elements," IEEE Trans. Mobile Computing, vol. 7, no. 12, pp. 1430-1443, Dec. 2008.   DOI
17 Y. Z. Wu, T. Weise, R. Chiong, "Local search for the Traveling Salesman Problem: A comparative study," in Proc. of 2015 IEEE 14th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC2015), pp. 213 - 220, July, 2015.
18 M. Z. Abbas, K. A. Bakar, M. Ayaz, "Hop-by-hop dynamic addressing based routing protocol for monitoring of long range underwater pipeline," KSII Transactions on Internet and Information Systems, vol. 11, no. 2, pp. 731-763, Feb. 2017.   DOI
19 J. Aparicio, J. J. Echevarria, J. Legarda, "A software defined networking approach to improve the energy efficiency of mobile wireless sensor networks," KSII Transactions on Internet and Information Systems, vol. 11, no. 6, pp. 2848-2869, June, 2017.   DOI