Routing algorithm based on layered mechanism in river underwater sensor networks

doi:10.11772/j.issn.1001-9081.2016.05.1183

Journal of Computer Applications ›› 2016, Vol. 36 ›› Issue (5): 1183-1187.DOI: 10.11772/j.issn.1001-9081.2016.05.1183

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Routing algorithm based on layered mechanism in river underwater sensor networks

LIU Yang¹, PENG Jian¹, LIU Tang^1,2, WANG Bin¹

1. College of Computer Science, Sichuan University, Chengdu Sichuan 610065, China;
2. College of Fundamental Education, Sichuan Normal University, Chengdu Sichuan 610068, China

Received:2015-10-16 Revised:2015-12-09 Online:2016-05-10 Published:2016-05-09
Supported by:
This work is partially supported by the National Natural Science Foundation of China(U1333113), the National Science Foundation for Young Scientists of China (61303204).

基于分层的河流水下传感器网络路由算法

刘洋¹, 彭舰¹, 刘唐^1,2, 王彬¹

1. 四川大学计算机学院, 成都 610065;
2. 四川师范大学基础教学学院, 成都 610068

通讯作者: 刘唐
作者简介:刘洋(1991-),男,重庆人,硕士研究生,主要研究方向:无线传感器网络、水下无线传感器网络;彭舰(1970-),男,四川成都人,教授,博士,主要研究方向:无线传感器网络、大数据、云计算;刘唐(1980-),男,四川乐山人,副教授,博士,主要研究方向:无线传感器网络、无线充电;王彬(1991-),男,四川广安人,硕士研究生,主要研究方向:云计算。
基金资助:
国家自然科学基金资助项目(U1333113);国家自然科学青年基金资助项目(61303204)。

Abstract

Abstract: For the unique environment of the Underwater Wireless Sensor Network (UWSN) in river, the model was built by method of fluid dynamics to obtain the real-time position of sensor nodes and simulate the movement law of sensor nodes in real river environment. Furthermore, on the problem of data transmission in UWSN, a Routing Algorithm based on Layered Mechanism (RALM) was proposed for river environment. The topology information was calculated and updated by each node periodically based on the receiving speed from sink. The node to transmit data would choose the neighbor node in upper layer which has the most residual energy to be the next hop. If the node has no neighbor node in upper layer, the next hop would be the neighbor node in the same layer which has the most residual energy. The simulation results show that, compared with DBR (Depth-Based Routing) and Layered-DBR (Layered-Depth Based Routing), RALM algorithm can effectively reduce the network redundancy and packet loss rate, and the network life cycle is raised by 71% and 45%.

Key words: Underwater Wireless Sensor Network (UWSN), fluid dynamics, residual energy, layered routing algorithm, life cycle

摘要： 为了获取传感器节点的实时位置,在河流水下传感器网络(UWSN)的独特环境中,采用流体力学的方法对河流水下传感器网络进行建模,模拟真实河流环境下传感器节点的运动规律。为了研究河流水下无线传感器网络数据传输的问题,提出了一种河流环境下基于分层的路由算法(RALM)。每个节点根据收到Sink广播的速度信息周期性地计算并更新各自的拓扑信息,数据待发送节点优先选择当前剩余能量最多的上一层的邻居节点进行数据转发,若上层无邻居节点,则转发给剩余能量最多的同层邻居节点。仿真实验表明,所提算法在网络的冗余度和丢包率上都要优于基于深度的路由算法(DBR)和基于分层的水下传感器网络路由协议(Layered-DBR),网络生存周期分别提高了71%和45%。

关键词: 水下传感器网络, 流体力学, 剩余能量, 分层路由算法, 生存周期

CLC Number:

TP393

LIU Yang, PENG Jian, LIU Tang, WANG Bin. Routing algorithm based on layered mechanism in river underwater sensor networks[J]. Journal of Computer Applications, 2016, 36(5): 1183-1187.

刘洋, 彭舰, 刘唐, 王彬. 基于分层的河流水下传感器网络路由算法[J]. 计算机应用, 2016, 36(5): 1183-1187.

References

[1] 李建中, 高宏. 无线传感器网络的研究进展[J]. 计算机研究与发展, 2008, 45(1):1-15.(LI J Z, GAO H. Survey on sensor network research[J]. Journal of Computer Research and Development, 2008, 45(1):1-15.)
[2] 郭忠文, 罗汉江, 洪峰, 等. 水下传感器网络的研究进展[J]. 计算机研究与发展, 2010, 47(3):377-389.(GUO Z W, LUO H J, HONG F, et al. Current progress and research issues in underwater sensor networks[J]. Journal of Computer Research and Development, 2010, 47(3):377-389.)
[3] CAPELLA J V, BONASTRE A, ORS R, et al. A step forward in the in-line river monitoring of nitrate by means of a wireless sensor network[J]. Sensors and Actuators B:Chemical, 2014, 195:396-403.
[4] CAPELLA J V, BONASTRE A, ORS R, et al. In line river monitoring of nitrate concentration by means of a wireless sensor network with energy harvesting[J]. Sensors and Actuators B:Chemical, 2013, 177:419-427.
[5] BHUVANESWARI P T V, KARTHIKEYAN S, JEEVA B, et al. An efficient mobility based localization in underwater sensor networks[C]//Proceedings of the 2012 Fourth International Conference on Computational Intelligence and Communication Networks. Piscataway, NJ:IEEE, 2012:90-94.
[6] XIAO X, JI X P, YANG G, et al. LE-VBF:lifetime-extended vector-based forwarding routing[C]//Proceedings of the 2012 International Conference on Computer Science and Service System. Washington, DC:IEEE Computer Society, 2012:1201-1203.
[7] YAN H, SHI Z J, CUI J H, et al. DBR:depth-based routing for underwater sensor networks[C]//Proceedings of the 7th International IFIP-TC6 Networking Conference on Ad Hoc and Sensor Networks. Berlin:Springer-Verlag, 2008:72-86.
[8] 彭舰, 洪昌建, 刘唐, 等. 基于分层的水下传感器网络路由策略[J]. 通信学报, 2014, 35(6):25-31.(PENG J, HONG C J, LIU T, et al. Strategy of routing based on layered for underwater wireless sensor networks[J]. Journal on Communications, 2014, 35(6):25-31.)
[9] JAFRI M R, AHMED S, JAVAID N, et al. AMCTD:adaptive mobility of courier nodes in threshold-optimized DBR protocol for underwater wireless sensor networks[C]//Proceedings of the 20138th International Conference on Broadband and Wireless Computing, Communication and Applications. Piscataway, NJ:IEEE, 2013:93-99.
[10] DOMINGO M C. Marine communities based congestion control in underwater wireless sensor networks[J]. Information Sciences, 2013, 228(7):203-221.
[11] BASAGNI S, PETRIOLI C, PETROCCIA R, et al. CARP:a channel-aware routing protocol for underwater acoustic wireless networks[J]. Ad Hoc Networks, 2014, 34:92-104.
[12] PU L, LUO Y, MO H, et al. Comparing underwater MAC protocols in real sea experiments[J]. Computer Communications, 2015, 56:47-59.
[13] AKKAYA K, NEWELL A. Self-deployment of sensors for maximized coverage in underwater acoustic sensor networks[J]. Computer Communications, 2009, 32(7/8/9/10):1233-1244.
[14] SOZER E M, STOJANOVIC M, PROAKIS J G. Underwater acousticnetworks[J]. IEEE Journal of Oceanic Engineering, 2000, 25(1):72-83.
[15] 姚仕明, 卢金友, 徐海涛. 黄陵庙水文断面垂线流速分布特性研究[J]. 长江科学院院报, 2005, 22(4):8-11.(YAO S M, LU J Y, XU H T. Study of vertical velocity distribution at Huanglingmiao hydrologic section[J]. Journal of Yangtze River Scientific Research Institute, 2005, 22(4):8-11.)
[16] 李艳红, 赵敏.含植物河流动力学实验研究——流速、摩阻流速及曼宁糙率系数垂线分布[J]. 水动力学研究与进展, 2004, 19:513-519.(LI Y H, ZHAO M. Experimental studies of hydrodynamics in vegetated river flows-vertical profiles of velocity, shear velocity and Manning roughness[J]. Journal of Hydrodynamics, 2004, 19:513-519.)
[17] 卿利, 朱清新, 王明文. 异构传感器网络的分布式能量有效成簇算法[J]. 软件学报, 2006, 17(3):481-489.(QING L, ZHU Q X, WANG M W. A distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networks[J]. Journal of Software, 2006, 17(3):481-489.)

Routing algorithm based on layered mechanism in river underwater sensor networks

基于分层的河流水下传感器网络路由算法

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