An Approach to Improve Lifetime of MANET via Power Aware Routing Protocol and Genetic Algorithm

Kumar, Sunil; Sinha, Deepak K.; Kumar, Vinesh

doi:10.1109/icimia48430.2020.9074912

Cited by 4 publications

(1 citation statement)

References 8 publications

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“…The challenge is reducing routing overheads in spite of the changing topology. This is a critical issue because both link bandwidth and battery power are premium resources [4][5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Link Life Time and Energy-Aware Stable Routing for MANETs

Gudakahriz,

Mirzaei,

Khiavi

2023

Preprint

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One of the major problems in mobile ad hoc networks (MANETs) routing is the short lifetime of their routes. This problem has roots in the dynamic topology of the network and the limited battery capacity of its nodes. One of the solutions to upgrade the efficiency of this routing scheme is necessary to select the most stable paths to reduce the latency and the overhead arising from the routes’ reconstructions. This paper designs a routing protocol that calculates multiple stable paths between the source and the destination and then selects the best available path among them. The proposed protocol is based on the AODV protocol. In comparison with previous works on AODV, this work has two significant improvements. First, it selects only node-disjoints paths, hence failure of one path doesn’t affect other paths. Second, it selects high-quality stable routes using an efficient formula. Extensive simulations in the NS-2 environment show that the proposed protocol called ST-AODV (Stable Ad hoc On-demand Distance Vector) outperforms AODV in terms of packet delivery ratio, end-to-end delay, routing frequency, and routing overhead.

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Section: Introductionmentioning

confidence: 99%

Link Life Time and Energy-Aware Stable Routing for MANETs

Gudakahriz,

Mirzaei,

Khiavi

2023

Preprint

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show abstract

Lotus effect optimization algorithm (LEA): a lotus nature-inspired algorithm for engineering design optimization

Dalirinia,

Jalali,

Yaghoobi

et al. 2023

J Supercomput

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Here we introduce a new evolutionary algorithm called the Lotus Effect Algorithm, which combines efficient operators from the dragonfly algorithm, such as the movement of dragonflies in flower pollination for exploration, with the self-cleaning feature of water on flower leaves known as the lotus effect, for extraction and local search operations. The authors compared this method to other improved versions of the dragonfly algorithm using standard benchmark functions, and it outperformed all other methods according to Fredman's test on 29 benchmark functions. The article also highlights the practical application of LEA in reducing energy consumption in IoT nodes through clustering, resulting in increased packet delivery ratio and network lifetime. Additionally, the performance of the proposed method was tested on real-world problems with multiple constraints, such as the welded beam design optimization problem and the speed-reducer problem applied in a gearbox, and the results showed that LEA performs better than other methods in terms of accuracy.

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Hybrid data transmission scheme based on source node centrality and community reconstruction in opportunistic social networks

Deng

Gou

2021

Peer-to-Peer Netw. Appl.

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An Approach to Improve Lifetime of MANET via Power Aware Routing Protocol and Genetic Algorithm

Cited by 4 publications

References 8 publications

Link Life Time and Energy-Aware Stable Routing for MANETs

Link Life Time and Energy-Aware Stable Routing for MANETs

Lotus effect optimization algorithm (LEA): a lotus nature-inspired algorithm for engineering design optimization

Hybrid data transmission scheme based on source node centrality and community reconstruction in opportunistic social networks

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