Improving the Performance of Fuzzy Minimum Spanning Tree based Routing Process through P-Node Fuzzy Multicasting Approach in MANET

Bandyopadhyay, Soham; Polytechnic, Durgapur Dr.B.C.Roy; Karforma, Sunil

doi:10.5815/ijcnis.2018.06.02

Cited by 2 publications

(1 citation statement)

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“…It is significant to optimize the overall network energy utilization and improve packet sending performance. By introducing m-minimum (membership value as m) triangular fuzzy number at interval based cost and energy of the network, [16] to handle the atmospheric, environmental change and varying distance for topological change. They generated both fuzzy minimum spanning tree (FMST) for a given n-nodes network and p-node fuzzy multicast minimum spanning tree (pFMMST), in fuzzy interval based format and concluded that, pFMMST is better FMST based packet routing approach.…”

Section: Related Workmentioning

confidence: 99%

A Multi QoS Genetic-based Adaptive Routing in Wireless Mesh Networks with Pareto Solutions

Ibraheem¹,

Al-Hussainy²

2018

IJCNIS

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Wireless Mesh Networks(WMN) is an active research topic for wireless networks designers and researchers. Routing has been studied in the last two decades in the field of optimization due to various applications in WMN. In this paper, Adaptive Genetic Algorithm (AGA) for identifying the shortest path in WMN satisfying multi-QoS measure is introduced. The proposed algorithm is adaptive in the sense that it uses various selection methods during the reproduction process and the one with the best multi-QoS measure is adopted in that generation. The multi-objective QoS measure defined as the combination of the minimum number of hops, minimum delay, and maximum bandwidth. The multi-objective optimization has been formulated and solved using weighted sum approach with Pareto optimal solution techniques. The simulation experiments have been carried out in MATLAB environment with a wireless network modeled as weighted graph of fifty nodes and node coverage equals to 200 meter, and the outcomes demonstrated that the proposed AGA performs well and finds the shortest route of the WMN proficiently, rapidly, and adapts to the dynamic nature of the wireless network and satisfying all of the constraints and objective measures imposed on the networks.

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Section: Related Workmentioning

confidence: 99%