Minimization of Information Asymmetry Interference using Partially Overlapping Channel Allocation in Wireless Mesh Networks

Abstract

Wireless Mesh Network (WMN) is a developing technology that has a great impact on the improvement of the performance, flexibility and reliability over the traditional wireless networks. Using multi-hop communication facility these networks are installed as a solution to extend last-mile access to the Internet. WMN has already been deployed but still it faces certain issues regarding channel assignment and interfer-ence. One of the well-known interference issues is Information Asymmetry (IA) interface that results in increased retransmission ratio, end-to-end delay, and thus decreases the overall network capacity of WMN. Various studies have been done in the past to minimize information asymmetry interference using limited number of orthogonal or non-overlapping channels i.e. 1, 6 and 11 from IEEE 802.11b radio technology. In recent studies, it is mentioned that partially overlapping channels called POCs can be used to maximize network capacity. The purpose of this research is to minimize Information Asymmetry (IA) interference problem by proposing a channel assignment model called Optimal Partially Overlapping Channel Assignment (OPOCA). In this research, comparison has been made between OPOCA and existing Information Asymmetry Minimization (IAM) model. Through extensive simulations it has been verified that the proposed OPOCA model gives 8% better results as compared to existing IAM model.

Authors and Affiliations

Sadiq Shah, Khalid Saeed, Mustafa Khan, Rafi Ullah Khan

Keywords

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  • EP ID EP376652
  • DOI 10.14569/IJACSA.2018.090879
  • Views 110
  • Downloads 0

How To Cite

Sadiq Shah, Khalid Saeed, Mustafa Khan, Rafi Ullah Khan (2018). Minimization of Information Asymmetry Interference using Partially Overlapping Channel Allocation in Wireless Mesh Networks. International Journal of Advanced Computer Science & Applications, 9(8), 626-634. https://europub.co.uk/articles/-A-376652