一种基于AHP和FIS的WSN路由算法

doi:10.19678/j.issn.1000-3428.0061332

摘要/Abstract

摘要： 无线传感器网络（WSN）由许多传感器节点组成，这些传感器节点为了降低能量消耗会周期性地在醒与睡2种模式下进行切换。在异步WSN中，发送节点往往要等接收节点醒来才能进行数据转发，为了缩短该等待时延，发送节点选择多个节点作为候选转发节点，由于任何候选转发节点都有可能进行数据路由，使得邻居节点评估和候选转发节点选择对网络性能产生较大影响。为了更好地进行节点评估与选择，提出一种基于层次分析法（AHP）和模糊推理系统（FIS）的WSN路由算法DAF。将剩余能量、距离和角度作为评估准则，利用AHP确定评估准则的权重，通过FIS动态构建AHP中的成对比较矩阵，并根据该矩阵动态计算出邻居节点的评分，按评分高低选择候选转发节点。实验结果表明，在改变节点数量、睡眠时长和通信半径的对比测试中，DAF在生命周期、能量消耗和平均冗余传输性能方面均优于ORW和ORR算法。

关键词: 无线传感器网络, 醒睡周期, 层次分析法, 模糊推理系统, 生命周期

Abstract: Wireless Sensor Network(WSN) is composed of many sensor nodes.To save on energy consumption, sensor nodes periodically switch between wake-up and sleep modes.In asynchronous WSN, transmitting nodes often wait for receiving nodes to wake up before forwarding the data.To shorten the waiting delay, transmitting nodes select multiple nodes as candidate forwarding nodes.Any candidate forwarding node may carry out data routing, which has neighbor node evaluation and candidate forwarding node selection greatly impact network performance.To better select nodes and evaluate, a WSN routing algorithm DAF, based on Analytic Hierarchy Process(AHP) and Fuzzy Inference System(FIS) is proposed.The residual energy, distance, and angle are used as the evaluation criteria, the weights of which are determined by AHP.The pairwise comparison matrix in AHP is dynamically constructed by FIS, whereby the score of neighbor nodes is dynamically calculated according to the AHP matrix.The candidate forwarding nodes are then selected according to the scores.Experimental results show that in the comparative test of changing the number of nodes, sleep time and communication radius, DAF is better than ORW and ORR algorithms in life cycle, energy consumption and average redundant transmission performance.

Key words: Wireless Sensor Network(WSN), sleep-wake cycle, Analytic Hierarchy Process(AHP), Fuzzy Inference System(FIS), life cycle

中图分类号:

TP391

周文康, 王行甫. 一种基于AHP和FIS的WSN路由算法[J]. 计算机工程, 2022, 48(3): 131-138,161.

ZHOU Wenkang, WANG Xingfu. A Routing Algorithm for WSN Based on AHP and FIS[J]. Computer Engineering, 2022, 48(3): 131-138,161.

https://www.ecice06.com/CN/Y2022/V48/I3/131

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参考文献

[1] BENSALEH M S, SAIDA R, KACEM Y H, et al.Wireless sensor network design methodologies:a survey[J].Journal of Sensors, 2020(1):1-13.
[2] DINH T, KIM Y, GU T, et al.An adaptive low-power listening protocol for wireless sensor networks in noisy environments[J].IEEE Systems Journal, 2018, 12(3):2162-2173.
[3] YADAV R V S M N.Performance analysis of optimized medium access control for wireless sensor network[J].IEEE Sensors Journal, 2010, 10(12):1863-1868.
[4] BUETTNER M, YEE G V, ANDERSON E, et al.X-MAC:a short preamble MAC protocol for duty-cycled wireless sensor networks[C]//Proceedings of the 4th International Conference on Embedded Networked Sensor Systems.Washington D.C., USA:IEEE Press, 2006:307-320.
[5] MOSS D, LEVIS P.BoX-MACs:exploiting physical and link layer boundaries in low-power networking[EB/OL].[2021-02-05].http://coronet2010.stanford.edu/pubs/sing-08-00.pdf.
[6] GHADIMI E, LANDSIEDEL O, SOLDATI P, et al.Opportunistic routing in low duty-cycle wireless sensor networks[J].ACM Transactions on Sensor Networks, 2014, 10(4):1-39.
[7] SO J, BYUN H.Load-balanced opportunistic routing for duty-cycled wireless sensor networks[J].IEEE Transactions on Mobile Computing, 2016, 16(7):1940-1955.
[8] ARORA S, SINGH S.Node localization in wireless sensor networks using butterfly optimization algorithm[J].Arabian Journal for Science and Engineering, 2017, 42(8):3325-3335.
[9] EU Z A, TAN H P.Adaptive opportunistic routing protocol for energy harvesting wireless sensor networks[C]//Proceedings of 2012 IEEE International Conference on Communications.Washington D.C., USA:IEEE Press, 2012:318-322.
[10] BEHESHTIHA S S, TAN H P, SABAEI M.Opportunistic routing with adaptive harvesting-aware duty cycling in energy harvesting WSN[C]//Proceedings of the 15th International Symposium on Wireless Personal Multimedia Communications.Washington D.C., USA:IEEE Press, 2012:90-94.
[11] HAWBANI A, WANG X, ZHAO L, et al.Novel architecture and heuristic algorithms for software-defined wireless sensor networks[J].IEEE/ACM Transactions on Networking, 2020, 28(6):2809-2822.
[12] LIU P, WANG X, HAWBANI A, et al.FRCA:a novel flexible routing computing approach for wireless sensor networks[J].IEEE Transactions on Mobile Computing, 2019, 19(11):2623-2639.
[13] LEAL J E.AHP-express:a simplified version of the analytical hierarchy process method[J].MethodsX, 2020, 7:100748.
[14] VILELA M, OLUYEMI G F, PETROVSKI A.Sensitivity analysis applied to fuzzy inference on the value of information in the oil and gas industry[J].International Journal of Applied Decision Sciences, 2020, 13(3):344-362.
[15] REN Y, ZHANG C, ZHAO F, et al.An MCDM-based multiobjective general variable neighborhood search approach for disassembly line balancing problem[J].IEEE Transactions on Systems, Man, and Cybernetics, 2018, 50(10):3770-3783.
[16] KOSHELEVA O, KREINOVICH V.Why Triangular membership functions are often efficient in F-transform applications:relation to probabilistic and interval uncertainty and to Haar wavelets[C]//Proceedings of International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems.Berlin, Germany:Springer, 2018:127-138.
[17] MUDIA H.Comparative study of mamdani-type and sugeno-type fuzzy inference systems for coupled water tank[J].Indonesian Journal of Artificial Intelligence and Data Mining, 2020, 3(1):42-49.
[18] NAIMI M, TAHAYORI H, SADEGHIAN A.A fast and accurate method for calculating the center of gravity of polygonal interval type-2 fuzzy sets[J].IEEE Transactions on Fuzzy Systems, 2020, 29(6):1472-1483.
[19] HAWBANI A, WANG X, ZHAO L, et al.Novel architecture and heuristic algorithms for software-defined wireless sensor networks[J].IEEE/ACM Transactions on Networking, 2020, 28(6):2809-2822.
[20] 朱莉, 顾能华, 姚英彪, 等.基于RSSI的WSN二维对数搜索定位算法[J].计算机工程, 2014, 40(4):87-90, 95. ZHU L, GU N H, YAO Y B, et al.RSSI-based two-dimensional logarithmic search localization algorithm for WSN[J].Computer Engineering, 2014, 40(4):87-90, 95.(in Chinese)
[21] SANTI P.Topology control in wireless ad hoc and sensor networks[J].ACM Computing Surveys, 2005, 37(2):164-194.
[22] HEINZELMAN W R, CHANDRAKASAN A, BALAKRISHNAN H.Energy-efficient communication protocol for wireless microsensor networks[C]//Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.Washington D.C., USA:IEEE Press, 2000:102-123.

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