基于局部拓扑控制的认知网络路由方法

doi:10.11959/j.issn.1000-436x.2016098

摘要/Abstract

摘要：

针对认知网络研究一种融合主、次用户多因素优化的局部拓扑控制和路由方法。该方法综合考虑主用户频谱使用情况以及次用户对主用户干扰影响，预测认知链路的稳定性，结合链路功耗，定义一种联合链路代价，提出链路代价最小的局部认知拓扑控制路由(LCTCR)算法，优化网络拓扑，并在优化后的拓扑上进行网络路由的选择。算法分析和仿真实验证明，在进行认知网络路径选择时，链路功耗和链路稳定性均为重要参数，需联合优化以保证选择更优的实际路由。

关键词: 认知网络, 拓扑控制, 路由, 链路稳定性, 链路功耗

Abstract:

An approach of topology control and routing was proposed according to the characteristics of cogni ive radio networks,which considered multi factors optimization with fusion of primary users and secondary users.And the ap-proach took the spectrum utilization of primary users the interference from secondary users to primary users into ac-count.Then a joint link cost was defined combining the predicted cognitive link stability with the link power consump-tion.Furthermore,the local cognitive topology control routing(LCTCR)algorithm with minimizing the link cost was presented,which was used to optimize the network topology.Meanwhile,the network path was selected according to the optimized network topology.Theoretical analysis and simulation experiments show that the link power consumption and the link stability are also important parameters and need to be jointly optimized when selecting the network path.Only by doing so can it guarantee that the selected path is optimal.

Key words: cognitive radio network, topology control, routing, link stability, link power consumption

刘舒祺,汪一鸣,崔翠梅. 基于局部拓扑控制的认知网络路由方法[J]. 通信学报, 2016, 37(5): 106-114.

Shu-qi LIU,Yi-ming WANG,Cui-mei CUI. Routing approach based on local topology control in cognitive radio networks[J]. Journal on Communications, 2016, 37(5): 106-114.

图/表 9

图1

图2

图3

图4

图5

图6

图7

图8

图9

参考文献 24

[1]	HAYKIN S . Cognitive radio:brain-empowered wireless communica-tions[J]. IEEE J Sel Areas Commun., 2005,23(2): 201-220.
[2]	JIANG D D , WANG Y T , YAO C P , HAN Y . An effective dyna ic spectrum access algorithm for multi-hop cognitive wireless net-works[J]. Computer Networks, 2015,84: 1-16.
[3]	SUN L , WANG W Y , LI Y J . The impact of network size and mobility on information delivery in cognitive radio networks[J]. IEEE Transac-tions on Mobile Computing, 2016,15(1): 217-231.
[4]	WEST D B . Introduction to graph theory[M]． Beijing: China Machine Press, 2004.
[5]	李云, 周娴, 尤肖虎 , 等. IMECN:一种新的无线传感器网络拓扑控制算法[J]．电子学报, 2010,38(1): 48-53. LI Y , ZHOU X , YOU X H , et al. IMECN:a new topology control al-gorithm for wireless sensor networks[J]. Acta Electronica Sinica, 2010,38(1): 48-53.
[6]	刘军, 于耕, 张慧鹏 . 基于节点控制的空间信息网拓扑重构算法[J]．电子学报, 2011,39(8): 1837-1844. LIU J , YU G , ZHANG H P . A topology reconfiguration algorithm through node position control for space information networks[J]. Acta Electronica Sinica, 2011,39(8): 1837-1844.
[7]	XIANG Y , WU Y , PENG J . A kind of topology control algorithm aimed at extending the life cycle of the WSN[C]// IEEE 13th Conf.on Cognitive Informatics & Cognitive Computing. c2014: 386-391.
[8]	SAJJAD Z , NASSER Y , AMIR N . Energy-efficient topology control in wireless ad hoc networks with selfish nodes[J]. Computer Networks, 2012,56(2): 902-914.
[9]	WU J , DAI F . Mobility-sensitive topology control in mobile ad hoc networks[J]. IEEE Transactions on Parallel and Distributed Systems, 2006,17(6): 522-535.
[10]	KOMALI R S , THOMAS R W , DASILVA L A , et al. The price f ignorance:distributed topology control in cognitive networks[J]. IEEE Transactions on Wireless Communications, 2010,9(4): 1434-1445.
[11]	ZHAO J , CAO G H . Robust topology control in multi-hop cognitive radio networks[J]. IEEE Transactions on Mobile Computing, 2014,13(11): 2634-2647.
[12]	PETRI M , MARINA P , JANNE R . Applications of topology informa-tion for cognitive radios and networks[C]// The 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks. c2007: 103-114.
[13]	JIANG D D , XU Z Z , LI W P , et al. Network coding-based ener-gy-efficient multicast routing algorithm for multi-hop wireless net-works[J]. The Journal of Systems and Software, 2015,104: 152-165.
[14]	JAVAD V , VENKATESHA P , ERTAN O , et al. Energy-aware routing algorithms for wireless ad hoc networks with heterogeneous power supplies[J]. Computer Networks, 2011,55(15): 3256-3274.
[15]	顾成杰, 张顺颐, 孙雁飞 . 基于业务感知和策略选择的认知路由算法[J]．通信学报, 2011,32(11): 168-175. GU C J , ZHANG S Y , SUN Y F . Cognitive network routing algorithm based on service awareness and policy choice[J]. Journal on Commu-nications, 2011,32(11): 168-175.
[16]	JAVAD V R , VENKATESHA P , IGNAS N . On the lifetime of node-to-node communication in wireless ad hoc networks[J]. Com-puter Networks, 2012,56(16): 1685-1709.
[17]	JIANG S M , HE D J , RAO J Q . A prediction-based link availability estimation for routing metrics in MANETs[J]. IEEE/ACM ransac-tions on Networking, 2005,13(6): 1302-1312.
[18]	RANGO F D , GUERRIERO F , MARANO S , et al. A multiobject ve approach for energy consumption and link stability issues in ad hoc networks[J]. IEEE Communications Letters, 2006,10(1): 28-30.
[19]	YOUSSEF M , IBRAHIM M , ABDELATIF M , et al. Routing metrics of cognitive radio networks:a survey[J]. IEEE Communications Sur-veys & Tutorials, 2014,16(1): 92-109.
[20]	MATTEO C , FRANCESCA C , EYLEM E . Routing in cognitive radio networks:challenges and solutions[J]. Ad Hoc Networks, 2011,9(13): 228-248.
[21]	HUANG X L , WANG G , HU F , et al. Stability-capacity-adaptive routing for high-mobility multihop cognitive radio networks[J]. IEEE Transactions on Vehicular Technology, 2011,60(6): 2714-2729.
[22]	JIANG D D , YING X , HAN Y , et al. Collaborative multi-hop routing in cognitive wireless networks[J]. Wireless Personal Communications, 2015: 1-23.
[23]	KANCHAN H , SUNITA B . Link prediction-based topology control and adaptive routing in cognitive radio mobile ad-hoc networks[C]// IEEE Global Conference on Wireless Computing and Networking. c2014: 11-15.
[24]	GUAN Q S, , YU F R , JIANG S M , et al. Prediction-based topology control and routing in cognitive radio mobile ad hoc networks[J]. IEEE Transactions on Vehicular Technology, 2010,59(9): 4443-4452.