The Routing Control in Mobile Ad hoc Network Using Intelligent Optimization Algorithms

Omran, Khulood Moosa

doi:10.1109/icecce49384.2020.9179296

Cited by 5 publications

(3 citation statements)

References 10 publications

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“…This method is simulated with NS2-simulator and the outcomes look remarkably worthy in measures such as overall throughput, Packet Delivery Ratio (PDR), and energy in residual when equated with other existing techniques. One more research work utilized the FOA (Fruit fly Optimized Algorithm) Omran et al [12] to control the issue and find a fitting guiding as opposed to the briefest method. The results found are differentiated and the particle swarm smoothing out (PSO) approach and ordinary AODV directing show, the proposed (FOA) method offers the snappiest and most exact pathway.…”

Section: Related Workmentioning

confidence: 99%

Fuzzified Swarm Intelligence Framework Using Fpsor Algorithm for High-Speed Manet

Gopalan¹

2021

Preprint

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Ad-hoc routing protocols may be dispersed and involve every node in the route discovery process by making routing data more reliable. Mobile-Adhoc-Networks (MANETs) consist of many portable nodes that can commune directly with each other or through intermediate nodes. Repeatedly, nodes in MANETs operate with batteries and can roam freely, and thus, a node may exhaust its energy or move away without providing any notice to its cooperative nodes. In MANETs, a route consists of numerous links in sequence, and so, its lifetime is based on the lifetime of every node and also the wireless links among adjacent nodes. In this research work Fuzzified Particle Swarm Optimization oriented Routing (FPSOR) algorithm is planned to minimize data loss and computational overhead, which in turn maximizes the lifetime of MANETs. Particle Swarm Optimization oriented Routing protocol (PSOR) has taken energy competence as a significant criterion for processing routing and driving optimised path for the data accelerating and processing to the source node. The PSOR produces a fresh route for routing by considering the fitness value of energy to evaluate diverse paths and to choose the best-optimised path whose energy consumption is less as compared to ant colony optimization routing paths. This algorithm utilizes a good approach focusing energy levels/status of the nodes through fuzzification and the lengths of the routed ways. NS2 simulator is cast for performance evaluation.

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Section: Related Workmentioning

confidence: 99%

Fuzzified Swarm Intelligence Framework Using Fpsor Algorithm for High-Speed Manet

Gopalan¹

2021

Preprint

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“…With minimal computer and detecting equipment, the nodes in MANET must maintain exact time synchronization when gathering and disseminating data from wireless nodes. For dispersed data collection and supervision, a reliable transmission rate is essential [2]. MANET is a system of mobile nodes which lacks a wired connection, allowing nodes in the network to act as routers.…”

Section: Introductionmentioning

confidence: 99%

An Improved Multi-Objective Particle Swarm Optimization Routing on MANET

Rajeshkumar¹,

Kumar²,

Kumar³

et al. 2023

Computer Systems Science and Engineering

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A Mobile Ad hoc Network (MANET) is a group of low-power consumption of wireless mobile nodes that configure a wireless network without the assistance of any existing infrastructure/centralized organization. The primary aim of MANETs is to extend flexibility into the self-directed, mobile, and wireless domain, in which a cluster of autonomous nodes forms a MANET routing system. An Intrusion Detection System (IDS) is a tool that examines a network for malicious behavior/policy violations. A network monitoring system is often used to report/gather any suspicious attacks/violations. An IDS is a software program or hardware system that monitors network/security traffic for malicious attacks, sending out alerts whenever it detects malicious nodes. The impact of Dynamic Source Routing (DSR) in MANETs challenging blackhole attack is investigated in this research article. The Cluster Trust Adaptive Acknowledgement (CTAA) method is used to identify unauthorised and malfunctioning nodes in a MANET environment. MANET system is active and provides successful delivery of a data packet, which implements Kalman Filters (KF) to anticipate node trustworthiness. Furthermore, KF is used to eliminate synchronisation errors that arise during the sending and receiving data. In order to provide an energy-efficient solution and to minimize network traffic, route optimization in MANET by using Multi-Objective Particle Swarm Optimization (MOPSO) technique to determine the optimal number of clustered MANET along with energy dissipation in nodes. According to the research findings, the proposed CTAA-MPSO achieves a Packet Delivery Ratio (PDR) of 3.3%. In MANET, the PDR of CTAA-MPSO improves CTAA-PSO by 3.5% at 30% malware.

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“…In common, the algorithms that depend upon intelligence of swarm may be named nature-inspired algorithms such as PSO optimization scheme established by Eberhart et al [2], which was motivated via the performance of birds' swarm and fish flocking [3]. Various articles compact by optimization schemes motivated depending on animals' performance, for instance, crows, whale, fruit fly, bat and cuckoo search optimization that governed by the different features of animals [4][5][6][7][8]. Later, ant colony optimization ACO technique was established effectively in various fields of engineering applications [9,10].…”

Section: Introductionmentioning

confidence: 99%

Optimum speed controller structure utilizing the MCA approach

2021

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In this paper, an optimal speed controller for dc motor is considered using a PID controller and tuned its parameters of gain to offer an optimal solution by using a modified camel algorithm MCA approach. The proposed MCA scheme was applied to solve the difficulty of getting the optimum gains of PID parameters. The MCA has good evolutionary speed with the simple construction of optimization depend on camel searching performance. The characteristics of the MCA algorithm were confirmed by optimizing the gains parameters of proportional, integral, derivative PID controller. The performance of PID-MCA is comparing with a classic PID controller enhanced with GA genetic algorithm optimization method to tune the gain parameters of the speed controller system. It was shown that the utilize of optimization processes indicated better performance for the MCA procedure in term of speed of execution and the size of memory compared with the GA method by applying computer simulations analysis. The proposed scheme has an efficient feature that includes the ease of implementation, good efficiency of computational performances with stable convergence characteristics. The results indicated that the proposed MCA scheme is a useful tool for search ability, produced efficient outcomes compared with the GA optimized method when applied in the proposed system.

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The Routing Control in Mobile Ad hoc Network Using Intelligent Optimization Algorithms

Cited by 5 publications

References 10 publications

Fuzzified Swarm Intelligence Framework Using Fpsor Algorithm for High-Speed Manet

Fuzzified Swarm Intelligence Framework Using Fpsor Algorithm for High-Speed Manet

An Improved Multi-Objective Particle Swarm Optimization Routing on MANET

Optimum speed controller structure utilizing the MCA approach

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