吉林大学学报(工学版) ›› 2015, Vol. 45 ›› Issue (5): 1586-1591.doi: 10.13229/j.cnki.jdxbgxb201505030

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Delay-tolerant mobile-sink strategy on energy saving for wireless sensor networks

KUANG Zhe-jun1, SHI Wei-jia2, HU Liang1, ZHOU Hang3   

  1. 1.College of Computer Science and Technology, Jilin University, Changchun 130012,China;
    2.Office of Institutional Research and Academic Planning, Rutgers, The State University of New Jersey, New Brunswick 08901, USA;
    3.College of Mathematics, Jilin University, Changchun 130012,China
  • Received:2014-03-14 Online:2015-09-01 Published:2015-09-01

Abstract: In this paper, the static and mobile sink models of wireless sensor networks are analyzed; then based on the application layer delay-tolerant level, a mobile-sink delay tolerance strategy is proposed. Using mobile agent node instead of static sink node, this strategy moves to the nearby resource node to send and receive data, thus alleviating “energy hole” problem. Using the application layer delay-tolerant level, the delay tolerance model under the environment of the mobile-sink nodes can reduce the energy consumption and greatly prolong the network lifetime.

Key words: computer application, wireless sensor network, mobile-sink, delay-tolerant, energy saving

CLC Number: 

  • TP393
[1] Popa L, Rostamizadeh A, Karp R, et al. Balancing traffic load in wireless networks with curveball routing[C]∥Proceedings of the Proceedings of the 8th ACM International Symposium on Mobile ad Hoc Networking and Computing, ACM, 2007: 170-179.
[2] Li J, Mohapatra P. An analytical model for the energy hole problem in many-to-one sensor networks[C]∥Proceedings of the IEEE Vehicular Technology Conference, IEEE,2005: 2721-2725.
[3] Wang Z M, Basagni S, Melachrinoudis E, et al. Exploiting sink mobility for maximizing sensor networks lifetime[C]∥Proceedings of the System Sciences, 2005 HICSS'05 Proceedings of the 38th Annual Hawaii International Conference on, IEEE, 2005: 287a.
[4] Luo J, Hubaux J-P. Joint mobility and routing for lifetime elongation in wireless sensor networks[C]∥Proceedings of the INFOCOM 2005 24th Annual Joint Conference of the IEEE Computer and Communications Societies Proceedings IEEE, IEEE, 2005: 1735-1746.
[5] Shi Y, Hou Y T. Theoretical results on base station movement problem for sensor network[C]∥Proceedings of the INFOCOM 2008 The 27th Conference on Computer Communications IEEE, IEEE, 2008:1-5.
[6] Chang J H,Tassiulas L. Maximum lifetime routing to mobile sink in wireless sensor networks[J].IEEE/ACM Transactions on Networking,2004,12(4):609-619.
[7] Shah R C, Roy S, Jain S, et al. Data mules: Modeling and analysis of a three-tier architecture for sparse sensor networks[J]. Ad Hoc Networks, 2003, 1(2): 215-233.
[8] 庄伟,宋光明,魏志刚,等. 具有机动能力的无线传感器网络节点的设计与实现[J]. 吉林大学学报:工学版,2007,37(4):939-943. Zhuang Wei,Song Guang-ming,Wei Zhi-gang,et al.Design and implementation of a mobile node for wireless sensor networks[J].Journal of Jilin University(Engineering and Technology Edition),2007,37(4):939-943.
[9] 王毅,张德运,马新新,等. 无线传感器网络传感器节点动态功耗管理方法[J]. 吉林大学学报:工学版,2008,38(4):880-885. Wang Yi, Zhang De-yun, Ma Xin-xin, et al. Novel dynamic power management of sensor node in wireless sensor networks[J]. Journal of Jilin University (Engineering and Technology Edition),2008,38(4):880-885.
[10] 孙强, 徐晨, 黄勋. 无线传感器网络移动汇聚节点的研究[J]. 通信技术, 2008,40(11):173-175. Sun Qiang, Xu Chen, Huan Xun. Research on mobile sink of wireless sensor network[J]. Communications Technology, 2008,40(11):173-175.
[11] 孟中楼, 王殊, 王骐. 分簇式无线传感器网络汇聚节点移动策略研究[J]. 华中科技大学学报: 自然科学版, 2009(6):67-70. Meng Zhong-lou, Wang Shu, Wang Qi. Research on the moving strategy for mobile sink in cluster wireless sensor networks[J]. Journal of Huazhong University of Science and Technology(Nature Science Edition), 2009(6):67-70.
[12] Basagni S, Carosi A, Melachrinoudis E, et al. A new MILP formulation and distributed protocols for wireless sensor networks lifetime maximization[C]∥Proceedings of the Communications, 2006 ICC'06 IEEE International Conference on, IEEE, 2006: 3517-3524.
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