MO‐CSO‐based load‐balanced routing in MRMC WMN

Rathan, Karunya; Roslin, S. Emalda; Brumancia, E.

doi:10.1049/iet-com.2018.6060

Cited by 6 publications

(1 citation statement)

References 29 publications

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“…This section is the continuation of the briefing of existing approaches of communication in wireless mesh network carried out in our prior work [10]. The recent work carried out by Rathan et al [11] has presented a load balancing approach in wireless mesh network where an analytical approach has been used. The work is mainly focused on performing traffic management in gateway system where the author has used swarm intelligence with an objective function for delay reduction.…”

Section: Related Workmentioning

confidence: 99%

Optimized Framework for QoS Efficient Routing Scheme in Wireless Mesh Network

T.H*,

2020

IJITEE

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Adoption of Wireless Mesh Network offers cost effective data transmission system; however, there is always a problems associated with larger scale of deployment where resource consumption is inevitable and beyond control. After reviewing the existing approaches toward improving the routing operation in Wireless Mesh Network, it has been seen that there are still a larger scope in improvement. Therefore, the proposed study introduces an optimized framework for quality of service that jointly works towards resolving hidden terminal problem as well as performs enhance data delivery in presence of challenging traffic scenario. The proposed system uses analytical modeling approach for channel occupancy is formulated and it performs computation of channel capacity. Further, an improved scheduling approach has been formulated in order to ensure superior saving of energy by considering various novel ranges of empirical parameters. Simulated in MATLAB, the proposed system highlights that it offers reduced delay, increased throughput, and highly controlled energy efficiency when compared with the existing routing protocols claims of traffic management in wireless mesh network.

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Section: Related Workmentioning

confidence: 99%