Abstract
In wireless sensor networks with many-to-one transmission mode, a multi-objective TDMA (Time Division Multiple Access) scheduling model is presented, which concerns about the packet delay and the energy consumed on node state transition. To realize the scheme, a mapping between the problem and evolutionary algorithm is reasonably set up. A multi-objective particle swarm optimization based on Pareto optimality (PAPSO) is then proposed to solve such multi-objective optimization problem and find a better tradeoff between time delay and energy consumption. The simulation results validate the effectivity of PAPSO algorithm and also show that PAPSO outperforms other techniques in the literature.
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References
Jolly, G., Younis, M.: An Energy-Efficient, Scalable and Collision-Free MAC layer Protocol for Wireless Sensor Networks. Wireless Communications and Mobile Computing (2005)
Ergen, S.C., Varaiya, P.: TDMA: Scheduling Algorithms for Sensor Networks, Technical Report, Department of Electrical Engineering and Computer Sciences U.C. Berkeley (July 2005)
Cui, S., et al.: Energy-Delay Tradeoffs for Data Collection in TDMA-based Sensor Networks. In: The 40th annual IEEE International Conference on Communications. Seoul, Korea (May 16-20, 2005)
Sridharan, A., Krishnamachari, B.: Max-Min Fair Collision-free Scheduling for Wireless Sensor Networks. In: MWN 2004. Workshop on Multihop Wireless Networks (April 2004)
Gandham, S., Dawande, M., Prakash, R.: Link scheduling in sensor networks: Distributed edge coloring revisited. In: INFOCOM, pp. 2492–2501 (2005)
Ergen, S.C., Varaiya, P.: TDMA: scheduling algorithms for sensor networks, Technical Report, Department of Electrical Engineering and Computer Sciences University of California, Berkeley (July 2005)
Karp, B., Kung, H.T.: GPSR: Greedy perimeter stateless routing for wireless networks. In: Proc. ACM/IEEE MobiCom (August 2000)
Eberhart, R., Kennedy, J.: A new optimizer using particle swarm theory. In: Proceedings of the sixth international symposium on micro machine and human science, pp. 39–43 (1995)
Deb, K.: Evolutionary Algorithms for Multi-Criterion Optimization in Engineering Design [A]. In: EUROGEN 1999. Proceedings of Evolutionary Algorithms in Engineering and Computer Science, pp. 135–161 (1999)
Coello Coello, C.A., Salazer Lechuga, M.: MOPSO: A Proposal for Multi Objective Particle Swarm Optimization. In: Congr. on Evolutionary Computation, Piscataway, New Jersey. vol. 2, pp. 1051–1056 (2002)
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Wang, T., Wu, Z., Mao, J. (2007). A New Method for Multi-objective TDMA Scheduling in Wireless Sensor Networks Using Pareto-Based PSO and Fuzzy Comprehensive Judgement. In: Perrott, R., Chapman, B.M., Subhlok, J., de Mello, R.F., Yang, L.T. (eds) High Performance Computing and Communications. HPCC 2007. Lecture Notes in Computer Science, vol 4782. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75444-2_19
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DOI: https://doi.org/10.1007/978-3-540-75444-2_19
Publisher Name: Springer, Berlin, Heidelberg
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