Abstract
For wireless sensor networks, unbalanced task load will decrease the lifetime of network. In this paper, we investigate how to schedule the sensor nodes to sleep or wakeup according to the dynamically changing task load. We first demonstrate that for a sensor network with uniform node distribution and constant data reporting, balancing the task load of the whole network cannot be realized. Then we define the concept of state transition and design a state transition model for sensor nodes. By introducing Markov chain, we further propose a task prediction method to predict the local task load in the next time period. Finally, we propose an energy-efficiency node scheduling algorithm based on game theory (ENSG) for WSNs. To obtain better performance, the residual energy of sensor nodes and local task load are both considered into the payoff function of our game. Our simulation results show that ENSG can guarantee the real-time task completion and prolong the lifetime of network.









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References
Chen M, Yang L T, Kwon T, Zhou L, Jo M (2011) Itinerary planning for energy-efficient agent communication in wireless sensor networks. IEEE Trans Veh Technol 60:3290–3299
Yu G, Cheng L, Niu J, He T, Du D H-C (2014) Achieving asymmetric sensing coverage for duty cycled wireless sensor networks. IEEE Trans Parallel Distrib Syst 25(12):3076–3087
Tang S, Yuan J (2013) DAMson: on distributed sensing scheduling to achieve high quality of monitoring. In the 32nd IEEE international conference on computer communications. Turin, Italy
XiaoHua X, Wan PJ, Tang SJ (2012) Efficient scheduling for periodic aggregation queries in multihop sensor networks. IEEE/ACM Trans Netw 20:690–698
Chen M, Mao S, Liu Y (2014) Big data: a survey. ACM/Springer Mob Netw Appl 19:171–209
Chen M, Mao S, Zhang Y, Leung VCM (2014) Big data: related technologies, challenges and future prospects. In: SpringerBriefs in computer science. Springer. ISBN 978-3-319-06245-7
Shrivastava P, Pokle SB (2014) An energy efficient scheduling strategy for data collection in wireless sensor networks. ICESC 2014:170–173
Chen M, Cai W, Gonzalez S, Leung VCM (2010) Balanced itinerary planning for multiple mobile agents in wireless sensor networks. In: Ad hoc networks: second international conference. Victoria, BC, Canada
Howrah GN, Banerjee I, Samanta T (2014) Energy efficient coverage of static sensor nodes deciding on mobile sink movements using game theory. In: Applications and innovations in mobile computing. Kolkata, India
Chen M, Leung VCM, Mao S, Kwon T (2009) Receiver-oriented load-balancing and reliable routing in in wireless sensor networks. Wireless Commun Mob Comput 9:405–416
Tang L, Sun Y, Gurewitz O, Johnson DB (2011) PW-MAC: an energy-efficient predictive-wakeup MAC protocol for wireless sensor networks. In: The 30th IEEE international conference on computer communications. Shanghai, China
Chen M, Leung VCM, Mao S, Li M (2008) Cross-layer and path priority scheduling based real-time video communications over wireless sensor networks. In: IEEE 67th vehicular technology conference-spring. Marina Bay
Carle J, Simplot-Ryl D (2004) Energy-efficient area monitoring for sensor networks. IEEE Comput 37 (2):40–46
Abrams Z, Goel A, Plotkin S (2004) Set k-cover algorithms for energy efficient monitoring in wireless sensor networks. In: The 3rd conference on information processing in sensor networks. Berkeley, CA, USA
Ma J, Lou W, Li X-Y (2014) Contiguous link scheduling for data aggregation in wireless sensor networks. IEEE Trans Parallel Distrib Syst 25:1691–1701
Li J, Chen J, He S, He T (2011) On energy-efficient trap coverage in wireless sensor networks. In: Proceedings of IEEE real-time systems symposium. Vienna, Austria
He S, Chen J, Li X, Shen X (2012) Leveraging prediction to improve the coverage of wireless sensor networks. IEEE Trans Parallel Distrib Syst 23:701–712
Cao Q, Abdelzaher T, He T, Stankovic J (2005) Towards optimal sleep scheduling in sensor networks for rare-event detection. In: The fourth international symposium on information processing in sensor networks. Los Angeles, California, USA
Liu C, Wu K, Xiao Y, Sun B (2006) Random coverage with guaranteed connectivity: joint scheduling for wireless sensor networks. IEEE Trans Parallel Distrib Syst 17:562–575
Kasbekar G S, Bejerano Y, Sarkar S (2011) Lifetime and coverage guarantees through distributed coordinate-free sensor activation. IEEE/ACM Trans Netw 19:470–483
Min Chen Y, Hao Y, Li D W (2015) On the computation offloading at ad hoc cloudlet: architecture and service models. IEEE Commun
Balister P, Zheng Z, Kumar S, Sinha P (2009) Trap coverage: allowing coverage holes of bounded diameter in wireless sensor networks. In: The 28th IEEE international conference on computer communications. Rio de Janeiro, Brazil
Xiaohua X, Li XY, Song M (2013) Efficient aggregation scheduling in multihop wireless sensor networks with SINR constraints. IEEE Trans Mob Comput 12:2518–2528
Bai X, Yun Z, Xuan D, Lai TH, Jia W (2010) Optimal patterns for four-connectivity and full coverage in wireless sensor networks. IEEE Trans Mob Comput 9:435–448
Cardei M, Ding-Zhu D (2005) Improving wireless sensor network lifetime through power aware organization. Wireless Netw 11:333–340
Tham C-K, Ai X, Srinivasan V (2006) Coverage game in wireless sensor networks. In: 14th IEEE international conference on networks. Singapore
Zhengyang Q, Chen D, Sun G (2012) Efficient wireless sensor networks scheduling scheme: game theoretic analysis and algorithm. In: IEEE international conference on communications (ICC). Ottawa, Canada
Chen J, Guo W (2013) A game theoretical fault-tolerant task scheduling algorithm for wireless sensor network. In: International conference on cloud computing and big data. Fuzhou, China
Abdeyazdan M, Parsa S, Rahmani A M (2013) Task graph prescheduling using Nash equilibrium in game theory. J Supercomput 64:177–203
Gao L, Wang X, Xu Y (2009) Multi-radio channel allocation in multi-hop wireless networks. IEEE Trans Mob Comput 8:1454–1468
Wang X, Li Z, Xu P, Xu Y, Gao X, Chen H (2010) Spectrum sharing in cognitive radio networks-an auction based approach. IEEE Trans Syst 40:587–596
Acknowledgments
This research is partially supported by the National Science Foundation of China (NSFC) under Grant No. 61103234. And the authors would like to extend their sincere appreciation to the Deanship of Scientific Research at King Saud University for its funding of this research through the Research Group Project no. RGP-VPP-281.
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Lin, K., Xu, T., Hassan, M.M. et al. An Energy-efficiency Node Scheduling Game Based on Task Prediction in WSNs. Mobile Netw Appl 20, 583–592 (2015). https://doi.org/10.1007/s11036-015-0609-0
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DOI: https://doi.org/10.1007/s11036-015-0609-0