Metaheuristics in Mobile AdHoc Network Route Optimization

Nivetha, S.; Asokan, R.; Senthilkumaran, N.

doi:10.1109/imicpw.2019.8933284

Cited by 3 publications

(3 citation statements)

References 5 publications

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“…𝐅 𝐬 = 𝐏𝐒𝐏 𝐢 (10) PSPsare computed for route I for every connection l in the collection of links L. To calculate the new PSPs number and modify the PSPs, utilize eq (11). Lastly, eq (12) chooses the most reliable AOMDV method pathway.…”

Section: Mutation Strength Alterationmentioning

confidence: 99%

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Optimization of Mobile Ad-hoc Networks Communication Using Ad-hoc On-demand Multipath Distance Vector With Novel Aging Multi Population Strategy for Effectual Energy Utilization

2024

Informacije MIDEM

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In today's world, wireless technologies play a vital role in numerous real-world applications, particularly Mobile Ad-hoc Networks (MANETs), which offer bidirectional transmission capabilities through intermediary nodes. However, packet collision poses a significant challenge in MANETs due to the random movement of nodes at unpredictable speeds, leading to degraded throughput, increased routing overhead, and higher end-to-end delays. Moreover, frequent node mobility causes topological shifts and link instability, further lowering data delivery rates. Limited possible routes to the destination network also contribute to traffic congestion at intermediary nodes, hindering successful packet delivery, especially in real-world MANET applications. The proposed approach introduces a novel strategy utilizing the concept of "age" to evaluate each particle's local area search capacity within the MANET environment, termed Aging Multi Population Optimization (AMPO). Particles are categorized into distinct age groups based on their ages to maintain population diversity during the search process. Particles within each age group can only select younger particles or those within their own clusters/groups as preferred neighbors. To determine the optimal route to the destination, multiple pathways returned by the Adhoc On-demand Multipath Distance Vector (AOMDV) mechanism are optimized, considering the route with the highest fitness value as the most ideal. Additionally, a parameter setting mechanism based on age groups is introduced to accelerate convergence, where particles in different age groups possess distinct parameters. Finally, the proposed approach is evaluated against existing methods such as AOMDV-TA and EHO-AOMDV, considering network overhead, throughput, delay, energy usage, and packet delivery range as crucial performance metrics.

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Section: Mutation Strength Alterationmentioning

confidence: 99%

“…Numerous clustering algorithms have been proposed to handle complex and dynamic environments [8,9]. For one-hop, multi-hop, and self-organizing networking, many routing techniques have been created [10,11]. Three sorts of routing exist: reactive, proactively, and mixed.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Mobile Ad-hoc Networks Communication Using Ad-hoc On-demand Multipath Distance Vector With Novel Aging Multi Population Strategy for Effectual Energy Utilization

2024

Informacije MIDEM

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show abstract

“…𝐅 𝐬 = 𝐏𝐒𝐏 𝐢 (10) PSPs are computed for route I for every connection l in the collection of links L. To calculate the new PSPs number and modify the PSPs, utilize eq (11). Lastly, eq (12) chooses the most reliable AOMDV method pathway.…”

Section: Path Stability Probabilities (Psps)mentioning

confidence: 99%

Optimization of Manets Using Aomdv With Novel Aging Multi Population Strategy for Effectual Energy Utilization

R.S.¹

2023

Preprint

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In today’s world wireless technologies plays vital role for many real world applications particularly the Mobile Ad-hoc Network (MANET) with bidirectional transmission capacity through numerous intermediary nodes is having dynamic scope in near future. Whereas, packet collision is regarded as the most important restrictions in MANETs since nodes move randomly through the network at unpredictable speeds, increasing the likelihood of collision and degrading throughput, routing overhead, and end-to-end delay. Additionally, a topological shift and link instability caused by frequent node mobility lower the rate of data delivery. The probability of traffic crowding increases at the intermediary nodes due to limited possible routes to the destination network, which affects the successful delivery of packets, especially with real-world applications on MANETs. In the proposed work, a novel strategy of age to evaluate each particle's local area search capacity is anticipated with Aging Multi Population Optimization (AMPO). The particles are divided into distinct age groups according to their ages so that population variety can be maintained when searching. Particles within every group of age can only choose those in younger or from their own clusters / groups as preferred neighbors. To choose the optimum route to the destination, we optimise the many pathways that the Adhoc On-demand Multipath Distance Vector (AOMDV) mechanism returned. The most ideal route is thought to be the one with the highest value for fitness. In order to speed up convergence, we also create a parameter setting mechanism based on age groups, where particles in various age groups have distinct parameters. Finally, we evaluate our suggested approach in comparison to AOMDV-TA and EHO-AOMDV. For the performance assessment of the suggested model, network overhead, throughput, delay, energy usage, and delivery of packets range as vital aspects.

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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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Metaheuristics in Mobile AdHoc Network Route Optimization

Cited by 3 publications

References 5 publications

Optimization of Mobile Ad-hoc Networks Communication Using Ad-hoc On-demand Multipath Distance Vector With Novel Aging Multi Population Strategy for Effectual Energy Utilization

Optimization of Mobile Ad-hoc Networks Communication Using Ad-hoc On-demand Multipath Distance Vector With Novel Aging Multi Population Strategy for Effectual Energy Utilization

Optimization of Manets Using Aomdv With Novel Aging Multi Population Strategy for Effectual Energy Utilization

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

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