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Efficient strategies to reduce power consumption in MANETs

In current circumstances, where amelioration in technology is elevating, power optimization is of grave concern, whilst perceiving portable conditions. The focus is to design an efficient system with an aim to reduce power consumption and improve performance of other metrics. Heterogeneous wireless...

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Detalles Bibliográficos
Autores principales: Fatima, Lubna Naaz, Mahin, Syeda Hajra, Taranum, Fahmina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7924446/
https://www.ncbi.nlm.nih.gov/pubmed/33816881
http://dx.doi.org/10.7717/peerj-cs.228
Descripción
Sumario:In current circumstances, where amelioration in technology is elevating, power optimization is of grave concern, whilst perceiving portable conditions. The focus is to design an efficient system with an aim to reduce power consumption and improve performance of other metrics. Heterogeneous wireless systems will command in the next-generation wireless networks with the aggregation of different remote access mechanisms. A node in MANET (Mobile Adhoc NETworks) while consuming significant amount of energy practices data transmission and data retrieval process whilst bonding with other neighboring nodes that are within its range. The proposed work implements User Specified energy model and DYMO (DYnamic Manet On-demand) routing protocol. Further, additional features of IEEE 802.11 i.e., Power Saving Mode is employed. To obtain enhanced coverage at targeted areas, multi-hop relay strategy is taken into account, also to achieve a less power consuming network with a greater service life. Consequently, the efficiency of the devices is monitored by opting Residual Life Accurate battery model, by using different datasets of Duracell AA and AAA batteries. Simultaneously, battery model, energy model and DYMO (DYnamic Manet On-demand) are applied for IEEE 802.16 to get a comparative assessment of power consumption between IEEE 802.11 and IEEE 802.16. Results are generated for both the architectures i.e., 802.11 and 802.16 for metrics such as residual amount of energy for varying simulation time for all the nodes and for energy consumption in AODV (Ad Hoc On-Demand Distance Vector) and DYMO (DYnamic Manet On-demand) routing protocol using Qualnet version 7.4.