Shortest Path Evaluation in Wireless Network Using Fuzzy Logic

被引:11
作者
Mali, G. U. [1 ]
Gautam, D. K. [1 ]
机构
[1] North Maharashtra Univ, Dept Elect Engn & Technol, Jalgaon, Maharashtra, India
关键词
Fuzzy logic; Shortest path; Crisp values; Inference engine; Wireless network;
D O I
10.1007/s11277-018-5645-1
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Evaluation of the shortest path in a wireless network is to ensure the fast and guaranteed delivery of the data over the established wireless network. Most of the wireless protocols are using a shortest path evaluation technique which is based on the random weights assigned to the network nodes. This alone may not be sufficient to get the accurate shortest path for routing process. Most of the shortest path evaluation algorithms perform the blind search to find the shortest routes for routing, this eventually increase the complexity of the whole process itself. This article puts some light on facts of using real time estimated routing delay from source node to other nodes by broadcasting a "knock" message. And this delay is being used to evaluate the shortest path for routing using fuzzy logic. This process is enhanced with its improved inference engine model and furnished fuzzy crisp patterns to deploy the shortest routing path in real time wireless nodes.
引用
收藏
页码:1393 / 1404
页数:12
相关论文
共 50 条
  • [31] Optimal Routing Protocol for Wireless Sensor Network Using Genetic Fuzzy Logic System
    Beevi, S. Zulaikha
    Alabdulatif, Abdullah
    CMC-COMPUTERS MATERIALS & CONTINUA, 2022, 70 (02): : 4107 - 4122
  • [32] Prediction Scheme Using Fuzzy Logic System to Control the Congestion in Wireless Sensor Network
    Faisal, Zainab G.
    Hussein, Maysam Sameer
    Abood, Amany Mohammad
    DISTRIBUTED COMPUTING AND OPTIMIZATION TECHNIQUES, ICDCOT 2021, 2022, 903 : 737 - 747
  • [33] Mobile robot path tracking using fuzzy logic
    Stankovski, M
    Kolemishevska-Gugulovska, T
    Stankovski, D
    Boshkovski, P
    Mileva, B
    Soft Computing with Industrial Applications, Vol 17, 2004, 17 : 257 - 262
  • [34] Code evaluation using fuzzy logic
    Avdagic, Zikrija
    Boskovic, Dusanka
    Delic, Aida
    PROCEEDINGS OF THE 9TH WSEAS INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS: ADVANCED TOPICS ON FUZZY SYSTEMS, 2008, : 20 - 25
  • [35] Agility evaluation using fuzzy logic
    Lin, CT
    Chiu, H
    Tseng, YH
    INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2006, 101 (02) : 353 - 368
  • [36] Quantitative feature evaluation using hybrid neural network and fuzzy logic approach
    Jiang, H
    Feng, X
    PROCEEDINGS OF THE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS 2003, VOLS 1-4, 2003, : 421 - 425
  • [37] Fuzzy Logic Based Path Establishment in Heterogeneous Wireless Multimedia Sensor Networks
    Seo, Hee Suk
    Kwak, Jin
    JOURNAL OF INTERNET TECHNOLOGY, 2011, 12 (05): : 725 - 732
  • [38] Using Fuzzy Logic for Clustering in Wireless Sensor Networks
    Choudhary, Devendra
    Sharma, Iti
    2017 INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING, INSTRUMENTATION AND CONTROL TECHNOLOGIES (ICICICT), 2017, : 861 - 866
  • [39] Clustering using Fuzzy Logic in Wireless sensor Networks
    Singh, Manjeet
    Soni, Surender
    Gaurav
    Kumar, Vicky
    PROCEEDINGS OF THE 10TH INDIACOM - 2016 3RD INTERNATIONAL CONFERENCE ON COMPUTING FOR SUSTAINABLE GLOBAL DEVELOPMENT, 2016, : 1669 - 1674
  • [40] Wireless Signal and Information Tracking Using Fuzzy Logic
    Chan, Eddie C. L.
    Baciu, George
    Mak, S. C.
    COMPUTATIONAL INTELLIGENCE, 2011, 343 : 59 - 72