Fuzzy preference ranking organization method for enrichment evaluation‐based node cooperation technique for improving QoS in MANETs

Mylsamy, Rajkumar; Jayaprakash, Karthika

doi:10.1002/dac.5168

Cited by 4 publications

(1 citation statement)

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“…Mylsamy and Jayaprakash 19 have proposed fuzzy preference ranking organization method for enrichment evaluation (FPROMETHEE) scheme for estimating the cooperation among nodes depending on trapezoidal fuzzy interval numbers that helps in choosing trusted mobile nodes for achieving increased data delivery. It involves numerous complex criteria for efficient ranking in a network with limited amount of mobile nodes.…”

Section: Related Workmentioning

confidence: 99%

Z number improved reference ideal method‐based decision‐making process for enforcing cooperation during data dissemination in mobile ad hoc networks

Mylsamy¹,

Jayaprakash²

2023

Int J Communication

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Summary In mobile ad hoc networks (MANETs), cooperative communication and resource constraint are the two important core characteristics essential to guarantee trusted data dissemination. The cooperative communication between mobile nodes depends on the trust rendered by them towards the process of reliable data routing. However, stringent resource constraints of mobile nodes such as energy, memory, communications, and computations result in the introduction of selfish and malicious node that completely degrades the network performance in different dimensions. In this paper, Z number improved reference ideal method (RIM)‐based decision‐making process (NIRIMDMP) is proposed with the merits of maximizing deviation method (MDM) and best–worst method (BWM) to ensure reliable data routing by modeling the cooperation degree in terms of Z number. This NIRIMDMP adopted Z number to represent the information reliability and handle the problem of inherent uncertainty during the process of evaluating each mobile node in the routing process. In specific, MDM and BWM are included into the proposed NIRIMDMP to determine comprehensive attribute weights based on the calculated objective and subjective weights that could be possible derived in routing. It extended the merits of classical RIM using Z numbers to confirm reliable ranking of mobile nodes, even when the optimal solution exists amid extreme values taken into consideration for assessing the mobile nodes during decision making. Simulation investigations of the proposed NIRIMDMP confirmed improved throughput and network lifetime with reduced control overhead, energy consumptions, and delay independent of the amount of malicious and non‐cooperative nodes.

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Section: Related Workmentioning

confidence: 99%