Fairness-Oriented Semi-Chaotic Genetic Algorithm-Based Channel
Assignment Technique for Nodes Starvation Problem in Wireless Mesh Network
- URL: http://arxiv.org/abs/2006.09655v1
- Date: Wed, 17 Jun 2020 04:43:47 GMT
- Title: Fairness-Oriented Semi-Chaotic Genetic Algorithm-Based Channel
Assignment Technique for Nodes Starvation Problem in Wireless Mesh Network
- Authors: Fuad A. Ghaleb, Bander Ali Saleh Al-rimy, Maznah Kamat, Mohd. Foad
Rohani, Shukor Abd Razak
- Abstract summary: Multi-Radio Multi-Channel Wireless Mesh Networks (WMNs) support many types of innovative technologies such as the Internet of Things (IoT) and vehicular networks.
Due to the limited number of channels, interference between channels adversely affects the fair distribution of bandwidth among mesh clients.
A fair channel assignment is crucial for the mesh clients to utilize the available resources.
- Score: 0.39146761527401425
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Multi-Radio Multi-Channel Wireless Mesh Networks (WMNs) have emerged as a
scalable, reliable, and agile wireless network that supports many types of
innovative technologies such as the Internet of Things (IoT) and vehicular
networks. Due to the limited number of orthogonal channels, interference
between channels adversely affects the fair distribution of bandwidth among
mesh clients, causing node starvation in terms of insufficient bandwidth, which
impedes the adoption of WMN as an efficient access technology. Therefore, a
fair channel assignment is crucial for the mesh clients to utilize the
available resources. However, the node starvation problem due to unfair channel
distribution has been vastly overlooked during channel assignment by the extant
research. Instead, existing channel assignment algorithms either reduce the
total network interference or maximize the total network throughput, which
neither guarantees a fair distribution of the channels nor eliminates node
starvation. To this end, the Fairness-Oriented Semi-Chaotic Genetic
Algorithm-Based Channel Assignment Technique (FA-SCGA-CAA) was proposed in this
paper for Nodes Starvation Problem in Wireless Mesh Networks. FA-SCGA-CAA
optimizes fairness based on multiple-criterion using a modified version of the
Genetic Algorithm (GA). The modification includes proposing a semi-chaotic
technique for creating the primary chromosome with powerful genes. Such a
chromosome was used to create a strong population that directs the search
towards the global minima in an effective and efficient way. The outcome is a
nonlinear fairness oriented fitness function that aims at maximizing the link
fairness while minimizing the link interference. Comparison with related work
shows that the proposed FA_SCGA_CAA reduced the potential nodes starvation by
22% and improved network capacity utilization by 23%.
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