作者：史宝会, 刘海燕

作者单位：北京信息职业技术学院计算机工程系, 北京 100018

关键词：蚁群优化算法;信息素;自主;路由协议;无线传感网

摘要：

面对无线传感网络(wireless sensor network,WSN)路由问题,提出新颖生物激励-自我组织的安全自适应路由协议(biological inspired self-organized secure autonomous routing protocol,BIOSARP)。BIOSARP采用改进蚁群优化算法(improved ant colony optimization,IACO),利用端到端传输时延、剩余电量和链路质量计算信息素,并据此信息决策最优转发节点,从而减小广播次数和数据包负担,降低时延、数据包丢失率和功率消耗。仿真结果表明:提出的BIOSARP在数据包传递率、能量消耗优于安全实时负荷分配协议(secure real-time load distribution,SRTLD),数据包传递率提高24.75%,能量消耗降低31.8%。

A novel improved ant colony optimization-based routing protocol in wireless sensor networks

SHI Baohui, LIU Haiyan

Computer Department, Beijing Information Technology College, Beijing 100018, China

Abstract: To solve routing problems in wireless sensor networks(WSN), a biological inspired self-organized secure autonomous routing protocol (BIOSARP) has been proposed in this paper. In the BIOSARP mechanism, an optimal forwarding decision was obtained by the improved ant colony optimization(IACO). With the help of the IACO, the pheromone value was computed according to the end-to-end delay, remaining battery power, and link quality metrics. The proposed BIOSARP has been designed to reduce the broadcast and packet overhead to minimize the delay, packet loss, and power consumption in WSNs. Simulation results show that the delivery ratio of the BIOSARP has been improved by 24.75% so as to reduce the energy consumption by 31.8% compared to the secure real-time load distribution(SRTLD).

Keywords: ant colony optimization;pheromone;autonomous agents;routing protocols;wireless sensor networks

2015, 41(9): 106-109  收稿日期: 2014-11-27;收到修改稿日期: 2015-2-1

基金项目: 国家自然科学基金(20121302167)水沙科学与水利水电工程国家重点实验室科研课题(2012-KY-05)

作者简介: 史宝会(1964-),女,北京市人,副教授,硕士,主要研究领域为计算机网络技术、网络存储与数据安全技术。

参考文献

[1] Vuran M C, Akyildiz I F. XLP: A cross-layer protocol for efficient communication in wireless sensor networks[J]. IEEE Trans Mobile Comput,2010,9(11):1578-1591.
[2] He T, Stankovic J, Lu C, et al. SPEED:A stateless protocol for real-time communication in sensor networks[C]∥ Proc of 23rd Int Conf Distrib Comput Syst, Providence RI USA,2003:46-55.
[3] Wenning B L, Pesch D A. Environmental monitoring aware routing: Making environmental sensor networks more robust[J]. Telecommun Syst,2010,43(2):3-11.
[4] Cerpa A, Wong J L, Kuang L, et al. Statistical model of lossy links in wireless sensor networks[C]∥Proc of ACM/IEEE 4th Int Symp IPSN, Los Angeles, USA, 2005:81-88.
[5] Garcia M, Sendra S, Lloret J, et al. Saving energy and improving communications using cooperative group-based wireless sensor networks[J]. Telecommun Syst,2013,52(4):2489-2502.
[6] Ahmed A, Fisal N F. Secure real-time routing protocol with load distribution in wireless sensor networks[J]. Security Commun Netw,2011,4(8):839-869.
[7] Mármol F G, Pérez G M. Providing trust in wireless sensor networks using a bio-inspired technique[J]. Telecommun Syst,2011,46(2):163-180.
[8] Muñoz A, Anton P, Maña A. Multiagent systems protection[J]. Adv Softw Eng,2011,4(3):23-31.
[9] Zhang B, Wu Y, Lu J, et al. Evolutionary computation and its applications in neural and fuzzy systems[J]. Appl Comput Intell Soft Comput,2011,9(2):34-40.
[10] Zungeru A M, Ang L M, Seng K P. Classical and swarm intelligence based routing protocols for wireless sensor networks: A survey and comparison[J]. J Netw Comput Appl,2012,35(5):1508-1536.
[11] Saleem K, Fisal N. Empirical studies of bio-inspired self-organized secure autonomous routing protocol[J]. IEEE Sensors Journal,2014,14(7):2232-2240.
[12] Wen Y F, Chen Y Q, Pan M. Adaptive ant-based routing in wireless sensor networks using energy delay metrics[J]. J Zhejiang Univ Sci,2008,9(4):531-538.
[13] Zungeru A M, Seng K P, Ang L M, et al. Energy efficiency performance improvements for ant-based routing algorithm in wireless sensor networks[J]. J Sensors,2013(4):34-42.
[14] Saleem K, Fisal N, Baharudin M A, et al. Ant colony inspired self-optimized routing protocol based on cross layer architecture for wireless sensor networks[J]. Wseas Trans Commun,2010,9(10):669-678.
[15] Chen G, Guo T D, Yang W G, et al. An improved ant based routing protocol in wireless sensor networks[J]. Collaborative Comput,2006,3(4):1-7.
[16] Ghoseiri K, Morshedsolouk F. ACS-TS:Train scheduling using ant colony system[J]. Math Decision Sci,2006,45(6):23-31.