计算机科学 ›› 2018, Vol. 45 ›› Issue (10): 130-137.doi: 10.11896/j.issn.1002-137X.2018.10.025

• 网络与通信 • 上一篇    下一篇

无线网络中具有信道感知的期望能耗最小化策略研究

黄荣喜1, 王淖2, 谢天骁2, 王高才2   

  1. 广西农业职业技术学院电子信息工程系 南宁530007 1
    广西大学计算机与电子信息学院 南宁530004 2
  • 收稿日期:2017-08-09 出版日期:2018-11-05 发布日期:2018-11-05
  • 作者简介:黄荣喜(1979-),男,硕士,讲师,主要研究方向为物联网技术及应用;王 淖(1977-),女,硕士,讲师,主要研究方向为移动网络能耗优化,E-mail:7482227@qq.com(通信作者);谢天骁(1990-),男,硕士生,主要研究方向为移动网络性能评价;王高才(1976-),男,博士,教授,博士生导师,CCF高级会员,主要研究方向为计算机网络技术、系统性能评价和随机方法。
  • 基金资助:
    国家自然科学基金:移动环境下基于博弈论的能量感知协同内容分发策略研究(61562006),广西自然科学基金(2016GXNSFBA380181)资助

Study on Channel-aware Expected Energy Consumption Minimization Strategy in Wireless Networks

HUANG Rong-xi1, WANG Nao2, XIE Tian-xiao2, WANG Gao-cai2   

  1. Department of Electronic and Information Engineering,Guangxi Agricultural Vocational College,Nanning 530007,China 1
    School of Computer and Electronic Information,Guangxi University,Nanning 530004,China 2
  • Received:2017-08-09 Online:2018-11-05 Published:2018-11-05

摘要: 随着无线网络技术的快速发展,节省能耗已成为构建绿色无线网络的一个非常重要的课题。由于信道的时变特性,在无线通信中利用好的信道状态能够获得更高的能量利用率。从整个无线网络的数据传输能耗出发,提出一种基于最优停止理论的数据传输期望能耗最小化策略(E2CMS)。E2CMS策略延迟数据的传输直到找到最好的期望信道状态,同时考虑了最大传输延迟和给定的接收端功率。首先,构建具有QoS约束的能耗最小化问题;接着,通过最优停止理论证明E2CMS策略是一种纯粹的阈值策略;然后,通过逆向归纳法求解定点方程,以求出功率阈值;最后,在典型的小尺度衰落信道模型中进行仿真实验,将E2CMS策略与多种不同的传输调度策略进行对比。结果表明,E2CMS策略具有更小的单位数据平均能耗,显著提高了网络性能。

关键词: 能耗优化, 数据传输, 无线网络, 信道感知, 最优停止理论

Abstract: With the rapid development of wireless network technology,saving energy consumption has become a very important topic to build green wireless networks.Due to the time-varying characteristics of the channel,it is possible to obtain a higher utilization for energy by using the channel with good state in wireless communication.From the view of the data transmission energy consumption of the whole wireless network,this paper proposed the expected energy consumption minimization strategy(E2CMS) for data transmission based on the optimal stopping theory.The E2CMS delays the transmission of data until the best desired channel state is found,taking into account the maximum transmission delay and the given receiver power.This paper first constructed an energy consumption minimization problem with qua-lity of service constraints.Then it proved that the E2CMS is a pure threshold strategy by the optimal stopping theory,and obtained the power threshold by solving a fixed-point equation with backward induction.Finally,it conducted si-mulations in a typical small-scale fading channel model and compared E2CMS with a variety of different transmission scheduling strategies.The results show that E2CMS has smaller average energy consumption per unit of data and signi-ficantly improves the network performance.

Key words: Channel awareness, Data transmission, Energy consumption optimization, Optimal stopping theory, Wireless networks

中图分类号: 

  • TP393
[1]LIN C,TIAN Y,YAO M.Green network and green evaluation:mechanism,modeling and evaluation [J].Chinese Journal of Computers,2011,34(4):593-612.(in Chinese)
林闯,田源,姚敏.绿色网络和绿色评价:节能机制、模型和评价[J].计算机学报,2011,34(4):593-612.
[2]ZHANG F,ANTA A F,WANG L,et al.Network energy consumption models and energy efficient algorithms[J].Chinese Journal of Computers,2012,35(3):603-615.(in Chinese)
张法,ANTA A F,王林,等.网络能耗系统模型及能效算法[J].计算机学报,2012,35(3):603-615.
[3]SIMON M K,ALOUINI M S.Digital Communications Over Fading Channels[M].Hoboken,NJ:Wiley,2005.
[4]LIU B,LIN C,JIANG X,et al.Performance analysis of sleep scheduling schemes in sensor networks using stochastic Petri net [C]∥Proceedings of the International Conference on Communications(ICC 2008).Beijing,China,2008:4278-4283.
[5]ZUO J,DONG C,NGUYEN H V,et al.Cross-layer aided energy-efficient opportunistic routing in Ad Hoc networks [J].IEEE Transactions on Communications,2014,62(2):522-535.
[6]KOHAN M,KHOTANLOU H,NASSIRI M.An efficient mechanism for data rate adaptation in wireless LAN’s [J].Advances in Computer Science:an International Journal,2013,2(3):19-25.
[7]WENG C C,CHEN C W,CHEN P Y,et al.Design of an energy-efficient cross-layer protocol for mobile ad hoc networks [J].IET Communications,2013,7(3):217-228.
[8]VAN PHAN C.A game-theoretic framework for opportunistic transmission in wireless networks [C]∥Proceedings of the 2014 IEEE Fifth International Conference on Communications and Electronics(ICCE 2014).Danang,Vietnam,2014:150-154.
[9]ZHENG D,GE W Y,ZHANG J S.Distributed opportunistic scheduling for Ad Hoc networks with random access:an optimal stopping approach [J].IEEE Transactions on Information Theo-ry,2009,55(1):205-222.
[10]POULAKIS M I,PANAGOPOULOS A D,CONSTANTINOU P.Channel-aware opportunistic transmission scheduling for ener-gy-efficient wireless links [J].IEEE Transactions on Vehicular Technology,2013,62(1):192-204.
[11]PENG Y,WANG G C,HUANG S Q,et al.An Optimization Strategy of Energy Consumption for Data Transmission Based on Optimal Stopping Theory in Mobile Networks[J].Chinese Journal of Computers,2016,39(6):1162-1175.(in Chinese)

彭颖,王高才,黄书强,等.移动网络中基于最优停止理论的数据传输能耗优化策略[J].计算机学报,2016,39(6):1162-1175.
[12]QIN X,BERRY R.Exploiting multiuser diversity for medium access control in wireless networks [C]∥IEEE INFOCOM,Sun Francisco.USA,2003:1084-1094.
[13]SHEN X,AGRAWAL S.Kernel Density Estimation for An Anomaly Based Intrusion Detection System [C]∥International Conference on Machine Learning;Models,Technologies & Applications(Mlmta 2006).Las Vegas,Nevada,USA,DBLP,2006:161-167.
[14]YUE G,ZHOU X,WANG X.Performance comparisons of chan- nel estimation techniques in multipath fading CDMA[J].IEEE Transactions on Wireless Communications,2004,3(3):716-724.
[15]FERGUSON T.Optimal Stopping and Applications 2006 [OL].http://www.math.ucla.edu/~tom/Stopping/contents.html.
[16]FREEMAN P R.The secretary problem and its extensions:a review[J].International Statistical Review,1983,51(51):189-206.
[17]LI C P,NEELY M J.Energy-optimal scheduling with dynamic channel acquisition in wireless downlinks[C]∥2007 46th IEEE Conference on Decision and Control.IEEE,2007:1140-1147.
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