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无线自组网中基于离散粒子群优化的睡眠调度感知最小功率广播 被引量:3

Sleep scheduling-aware minimum power broadcast in wireless ad hoc networks based on discrete particle swarm optimization
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摘要 针对当网络使用睡眠调度并且节点的传输功率连续可调节时的最小功率广播调度问题,首先给出了一种计算节点内部最优发送调度的递归方法,然后提出了一种构造最小功率广播调度的离散粒子群算法。该算法搜索最优广播树结构,并融合基于最小广播功率增量的贪心算法和基于启发式调整广播树结构的局部优化算法以提高收敛速度和求解质量。模拟实验结果表明所提算法能够有效地减少广播功率。 For the minimum power broadcast scheduling problem where network uses sleep scheduling and each node's transmission power is continuously adjustable, a recursive approach to compute the optimal transmission scheduling of a node was firstly presented, and then a discrete particle swarm optimization algorithm to construct the minimum power broadcast scheduling was proposed. This algorithm searches for the optimal broadcast arborescence, and utilizes the greedy algorithm based on the minimization of the broadcast's power increment and the local optimization algorithm based on the heuristic adjustment of the broadcast arborescence to improve the convergence speed and the result quality. The simulation results show that the proposed algorithm is able to effectively reduce the broadcast power.
作者 朱晓建 沈军
出处 《通信学报》 EI CSCD 北大核心 2013年第6期16-28,共13页 Journal on Communications
基金 国家重点基础研究发展计划("973"计划)基金资助项目(2009CB320501)~~
关键词 无线自组网 睡眠调度 最小功率 广播调度 离散粒子群优化 wireless ad hoe networks sleep scheduling minimum power broadcast scheduling discrete particle swarm optimization
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参考文献29

  • 1WIESELTHIER J E, NGUYEN G D, EPHREMIDES A. On the con- struction of energy-efficient broadcast and multicast trees in wireless networks[A]. Proceedings of the IEEE INFOCOM'2000[C]. Tel Aviv, Israel, 2000.585-594.
  • 2WAN P J, CALINESCU G, LI X Y, et al. Minimum-energy broadcast routing in static ad hoc wireless networks[A]. Proceedings of the IEEE INFOCOM'2001 [C]. Anchorage, Alaska, USA, 2001.1162-1171.
  • 3DAS A K, MARKS R J, EL-SHARKAWI M, et al. Minimum power broadcast trees for wireless networks: integer programming formula- tions[A]. Proceedings of the IEEE 1NFOCOM'2003[C]. San Francisco, CA, USA, 2003.1001-1010.
  • 4CAGALJ M, HUBAUX J P, ENZ C. Minimum-energy broadcast in all-wireless networks: NP-completeness and distribution issues[A]. Pro- ceedings of the Eighth Annual /ntemational Conference on Mobile Computing and Networking[C]. Atlanta, Georgia, USA, 2002. 172-182.
  • 5MIN M, PARDALOS P M. Total energy optimal rnulticasting in wire- less ad hoe networks[J]. Journal of Combinatorial Optimization, 2007, 13(4):365-378.
  • 6DAS A K, MARKS R J, EL-SHARKAWI M, et al. R-shrink: a heuristic for improving minimum power broadcast trees in wireless networks[A]. Proceedings of the 2003 IEEE Global Telecommunica- tions Conference[C]. San Francisco, CA, USA, 2003. 523-527.
  • 7LIANG W. Constructing minimum-energy broadcast trees in wireless ad hoc networks[A]. Proceedings of the Third ACM International Symposium on Mobile Ad Hoc Networking and Computing[C]. Lausanne, Switzerland, 2002.112-122.
  • 8AL-SHIHABI S, MERZ P, WOLF S. Nested partitioning for the minimum energy broadcast problem[A]. Proceedings of the Second International Conference on Learning and Intelligent Optimization(LION 2007 II)[C]. Trento, Italy, 2007. 1-11.
  • 9MONTEMANNI R, GAMBARDELLA L M, DAS A K. The mini- mum power broadcast problem in wireless networks: a simulated an- nealing approach[A]. Proceedings of the 2005 IEEE Wireless Com- munications and Networking Conference[C]. New Orleans, LA, USA, 2005.2057-2062.
  • 10WOLF S, MERZ P. Evolutionary local search for the minimum energy broadcast problem[A]. Proceedings of the 8th European Conference onEvolutionary Computation in Combinatorial Optimization (EvoCOP 2008)[C]. Naples, Italy, 2008.61-72.

二级参考文献17

  • 1武晓今,朱仲英.遗传算法多样性测度问题研究[J].信息与控制,2005,34(4):416-422. 被引量:17
  • 2ZHONG W L,HUANG J,ZHANG J.A novel particle swarm optimi-zation for the Steiner tree problem in graphs[A].Proceedings of the2008 IEEE Congress on Evolutionary Computation[C].Hong Kong,China,2008.2460-2467.
  • 3YUAN P,JI C L,ZHANG Y,et al.Optimal multicast routing in wire-less ad hoc sensor networks[A].Proceedings of 2004 IEEE Interna-tional Conference on Networking,Sensing and Control[C].2004.367-371.
  • 4KENNEDY J,EBERHART R.Particle swarm optimization[A].Proceedings of the 1995 IEEE International Conference on NeuralNetworks[C].Perth,Australia,1995.1942-1948.
  • 5EBERHART R,KENNEDY J.A new optimizer using particle swarmtheory[A].Proceedings of the Sixth International Symposium on Mi-cro Machine and Human Science[C].Nagoya,Japan,1995.39-43.
  • 6KENNEDY J,EBERHART R.A discrete binary version of the particleswarm algorithm[A].Proceedings of the 1997 IEEE InternationalConference on Systems,Man,and Cybernetics[C].Orlando,FL,USA,1997.4104-4108.
  • 7SHI Y,EBERHART R.A modified particle swarm optimizer[A].Proceedings of the 1998 IEEE International Conference on Evolution-ary Computation[C].1998.69-73.
  • 8SHI Y,EBERHART R.Empirical study of particle swarm optimiza-tion[A].Proceedings of the 1999 Congress on Evolutionary Computa-tion[C].Washington,DC,USA,1999.1945-1950.
  • 9SHI Y,E-BERHART R.Parameter selection in particle swarm opti-mization[A].Proceeding of the 1998 Annual Conference on Evolu-tionary Programming[C].San Dingo,CA,USA,1998.591-600.
  • 10AL-SHIHABI S,MERZ P,WOLF S.Nested partitioning for theminimum energy broadcast problem[A].LIUN 2007 II,Learning andIntelligent Optimization[C].2007.1-11.

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