research-article

A prediction algorithm for coexistence problem in multiple WBANs environment

Authors:

Tae-Seong KimAuthors Info & Claims

ICUIMC '14: Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication

Article No.: 68, Pages 1 - 7

https://doi.org/10.1145/2557977.2558017

Published: 09 January 2014 Publication History

Abstract

Coexistence problem occurs when a single WBAN(Wireless Body Area Network) locates in multiple WBANs environment. In that case, WBANs are suffered from serious channel interferences which may degrade the performance of each WBAN due to failure of data transmission. Because WBAN handles physical signal or emergency data affecting human life, WBAN requires the detection of coexistence condition to guarantee reliable communication continuously for each sensor node of WBAN. In this paper, we present a prediction algorithm to detect coexistence problem efficiently in multiple WBANs environment. The algorithm measures PRR(Packet Reception Ratio) and SINR(Signal to Interference and Noise Ratio) to detect interference reliably. In order to handle coexistence problem efficiently, the algorithm employs the naive Bayesian classifier which is one of machine learning techniques to classify the coexistence condition into four states. We conduct extensive simulations for coexistence detection with various packet transmit rates of sender node and speeds of mobile WBAN by using Castalia 3.2 simulator based on OMNet++ platform. Consequently, we demonstrate that the proposed algorithm provides more reliable and accurate performance than existing studies to detect coexistence in multiple WBANs environment.

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Cited By

Sun YChen TWang JJi Y(2020)A Machine Learning Based Method for Coexistence State Prediction in Multiple Wireless Body Area Networks13th EAI International Conference on Body Area Networks10.1007/978-3-030-29897-5_17(203-217)Online publication date: 4-Mar-2020
https://doi.org/10.1007/978-3-030-29897-5_17
Movassaghi SSmith DAbolhasan MJamalipour A(2018)Opportunistic Spectrum Allocation for Interference Mitigation Amongst Coexisting Wireless Body Area NetworksACM Transactions on Sensor Networks10.1145/313925714:2(1-22)Online publication date: 21-Jul-2018
https://dl.acm.org/doi/10.1145/3139257
Movassaghi SMajidi AJamalipour ASmith DAbolhasan M(2016)Enabling interference-aware and energy-efficient coexistence of multiple wireless body area networks with unknown dynamicsIEEE Access10.1109/ACCESS.2016.25776814(2935-2951)Online publication date: 2016
https://doi.org/10.1109/ACCESS.2016.2577681

Index Terms

A prediction algorithm for coexistence problem in multiple WBANs environment
1. Networks
  1. Network services
    1. Network monitoring

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cover image ACM Conferences

ICUIMC '14: Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication

January 2014

757 pages

ISBN:9781450326445

DOI:10.1145/2557977

Conference Chairs:
Dongsoo S. Kim
Indiana University
,
Sang-Wook Kim
Hanyang University, Korea
,
General Chairs:
Suk-Han Lee
Sungkyunkwan University
,
Korea Lajos Hanzo
University of Southampton, UK
,
Roslan Ismail
Universiti Kuala Lumpur, Malaysia

Copyright © 2014 ACM.

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SIGAPP: ACM Special Interest Group on Applied Computing
SKKU: SUNGKYUNKWAN UNIVERSITY

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Association for Computing Machinery

New York, NY, United States

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Published: 09 January 2014

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SIGAPP
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ICUIMC '14: The 8th International Conference on Ubiquitous Information Management and Communication

January 9 - 11, 2014

Siem Reap, Cambodia

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ICUIMC '14 Paper Acceptance Rate 116 of 407 submissions, 29%;

Overall Acceptance Rate 251 of 941 submissions, 27%

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Cited By

Sun YChen TWang JJi Y(2020)A Machine Learning Based Method for Coexistence State Prediction in Multiple Wireless Body Area Networks13th EAI International Conference on Body Area Networks10.1007/978-3-030-29897-5_17(203-217)Online publication date: 4-Mar-2020
https://doi.org/10.1007/978-3-030-29897-5_17
Movassaghi SSmith DAbolhasan MJamalipour A(2018)Opportunistic Spectrum Allocation for Interference Mitigation Amongst Coexisting Wireless Body Area NetworksACM Transactions on Sensor Networks10.1145/313925714:2(1-22)Online publication date: 21-Jul-2018
https://dl.acm.org/doi/10.1145/3139257
Movassaghi SMajidi AJamalipour ASmith DAbolhasan M(2016)Enabling interference-aware and energy-efficient coexistence of multiple wireless body area networks with unknown dynamicsIEEE Access10.1109/ACCESS.2016.25776814(2935-2951)Online publication date: 2016
https://doi.org/10.1109/ACCESS.2016.2577681

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