Optimal Shortest Path in Mobile Ad-Hoc Network Based on Fruit Fly Optimization Algorithm

Darwish, Saad M.; Elmasry, Amr; Ibrahim, Shaymaa H.

doi:10.1007/978-3-030-14118-9_10

Cited by 8 publications

(1 citation statement)

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“…The following necessary steps are describing the fruit fly characteristics of searching for a source node which is described in [25]. The random initial position of a mobile sink is in (0, 0) coordinates such that, 𝐼𝑛𝑖𝑡 𝑋 𝑎𝑥𝑖𝑠 = 0; 𝐼𝑛𝑖𝑡 𝑌 𝑎𝑥𝑖𝑠 = 0 (7) the regulated direction of the mobile sink and the distance of the source search were determined by each CH individual's fitness score.…”

Section: Fruit Fly Optimization Algorithmmentioning

confidence: 99%

Energy efficient secured-quality of service routing protocol for mobile ad hoc network using multi-objective optimization

Ramasamy,

Ramalingam,

Chitraivel

2023

IJEECS

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This article proposed a hybrid energy-efficient secured quality of service (QoS) based multipath routing protocol. A modified crow search combined with the tunicate swarm butterfly optimisation algorithm (TSBO) with a density-based clustering technique strategy is proposed for the selection of cluster heads after the initial cluster formations. Among all the nodes, the cluster head is selected, and employing the collaborative trust-based approach (CTBA), which employs the trust factor for mobile ad hoc network (MANET) data transmission, a node's authentication is supplied. Finally, to implement the safe routing technique, this article suggested a hybrid multipath routing protocol combining multi-objective grey wolf optimisation (MO-GWO) with a fruit fly algorithm. The NS3 simulator is used to assess the proposed work. The packet delivery ratio metric performs 4% better than the current models. As a result, the suggested approach performs better for the end-to-end delay, energy consumption, packet delivery ratio (PDR), and throughput; it also uses less energy and has a shorter delay. Additionally, single-path nodes with the same energy value have lower throughput than multi-path nodes.

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Section: Fruit Fly Optimization Algorithmmentioning

confidence: 99%