New Approach for Advanced Energy Efficiency in MANET (AEE-M) by Improving Optimized Link State Routing Protocol Version 2 (OLSRv2)

Battery vitality or the energy in the battery is said to be an uncommon asset in Mobile Ad-hoc network (MANET). This frequently influences the correspondence exercises in that are practiced in the network. The basic issue faced by MANET is the vitality proficiency. The simulation or test is the way...

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Veröffentlicht in:Wireless personal communications 2022-08, Vol.125 (3), p.2369-2392
Hauptverfasser: Anish Pon Yamini, K., Suthendran, K., Arivoli, T., Ravi, Vinayakumar
Format: Artikel
Sprache:eng
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Zusammenfassung:Battery vitality or the energy in the battery is said to be an uncommon asset in Mobile Ad-hoc network (MANET). This frequently influences the correspondence exercises in that are practiced in the network. The basic issue faced by MANET is the vitality proficiency. The simulation or test is the way to expand the restricted lifetime of energy that is there in the mobile nodes (MN). Vitality the board model is initially presented in this manuscript, in which every hub can move its state between dynamic mode power-spare modes. A novel routing Protocol (RP) has been proposed for additional vitality/energy control. In the convention, another routing capacity that manages both system layer as well as the Media Access Control (MAC) system layer has been characterized. Also, to deal with limiting the utilization of the energy, Advanced Energy Efficiency in MANET by improving Optimized Link State Routing Protocol version 2 (OLSRv2): (AEE-M-OLSRv2). AEE-M-OLSRv2 depends on the OLSRv2-RP and includes another vitality reasonableness boundary to the Multi-Point Relay (MPR) method. The new boundary is utilized by the proposed methodology and permits reasonableness vitality utilization in the equivalent set of Multi-point relay. Hubs with low force are forestalled in the network for routing procedure so as to keep up comparable force esteems for all the portable hubs. The results indicate that the proposed AEE-M-OLSRv2 approach out performs around 25% that the existing.
ISSN:0929-6212
1572-834X
DOI:10.1007/s11277-022-09663-5