Understanding spatial related network challenges from physical and network layers

Cheng Leong Lim, Cindy Goh, Asiya Khan, Yun Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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Abstract

Wireless Sensor Network's communication reliability is greatly influenced by the spatial related network challenges found in the physical space between communicating nodes. In this paper, ZigBee based sensor nodes are experimented under the influence of two distinct spatial related network challenges (i) poor deployed environment and (ii) human movements. WSN parameters obtained are used to develop an ANFIS based model designed to predict these spatial related network challenges. Using ANFIS model prediction accuracies as performance indices, WSN parameters are analysed from the physical and network layers perspective. Physical layer's link properties, reception strength and reception variability, are shown to be key indicators to spatial related network challenges. The parameters observed are Mean RSSI, Average Coefficient of Variation RSSI, Neighbour Table Connectivity and Bi-directional Neighbour Table Connectivity.

Original languageEnglish
Title of host publication2017 International Conference on Computing, Networking and Communications, ICNC 2017
Place of PublicationPiscataway, NJ.
PublisherIEEE
Pages368-373
Number of pages6
ISBN (Electronic)9781509045884
DOIs
Publication statusPublished - 10 Mar 2017
Event2017 International Conference on Computing, Networking and Communications, ICNC 2017 - Silicon Valley, United States
Duration: 26 Jan 201729 Jan 2017

Conference

Conference2017 International Conference on Computing, Networking and Communications, ICNC 2017
CountryUnited States
CitySilicon Valley
Period26/01/1729/01/17

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Keywords

  • wireless sensor network
  • WSN
  • network layers

Cite this

Lim, C. L., Goh, C., Khan, A., & Li, Y. (2017). Understanding spatial related network challenges from physical and network layers. In 2017 International Conference on Computing, Networking and Communications, ICNC 2017 (pp. 368-373). [7876156] Piscataway, NJ.: IEEE. https://doi.org/10.1109/ICCNC.2017.7876156