Optimization of Multicast Ad Hoc On-demand Routing Protocol Based on Genetic Algorithm with Backup Paths in MANET

Rajadurai, S. Jebakumar; Veerappan, J.; Ramasamy, Karthikeyan

doi:10.1007/s11277-016-3363-0

Cited by 13 publications

(4 citation statements)

References 6 publications

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“…In 2017, Rajadurai et al [3] have utilized the genetic algorithm (GA) for best path selection in MANET on the basis of the objectives like the "packet deliver ratio, latency and energy consumption ". Further, with the backup paths of the network structure, the tree based multicast protocols validity was improved.…”

Section: Literature Review 21 Related Workmentioning

confidence: 99%

“…MANET has a gathering of versatile hubs, which makes a powerful autonomous system through completely movable framework. The hubs speak with one another without the contribution of concentrated base stations or the passageways [4].However, the MANET regularly contains remote hubs, which works with no fixed framework [3] [5]. The hub, which are available in these systems make the application traffic and client traffic for playing out the directing conventions and system control.…”

Section: Introductionmentioning

confidence: 99%

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Energy-Aware routing in MANET: Hybrid Genetic and Group Search Algorithm

Malik¹

2020

JNACS

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MANET is the infrastructure-less, self-organized wireless network. Here, the mobile nodes can join the group or leave from the network group dynamically. As the mobile ad hoc network (MANET) is established with the battery power nodes, reducing the power consumption of mobile node poses a major complex in the network system. Efficient and robust secure routing protocols are required in MANET due to the quickly changing network topology such that the overhead incurred in the track is excessive. To achieve the secure routing path mechanism with less delay and minimum energy consumption of the nodes, a multi-objective based optimization algorithm is introduced in this research work. Here, the best optimal route is chosen for routing the data packets from the source to the destination on the basis of defined multiobjectives like: energy, delay, distance and link state stability. The secure path energy efficient path is identified by the Crossover of GA with GSO Algorithm (CGA-GSO). This is the hybridized form of standard Genetic Algorithm (GA) and the Group search Optimization (GSO) algorithm. The performance of the proposed model will be analyzed over the traditional approaches concerning Energy and Delay as well.

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Section: Literature Review 21 Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Energy-Aware routing in MANET: Hybrid Genetic and Group Search Algorithm

Malik¹

2020

JNACS

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“…Accordingly, the routing schemes for WANET lay under three groups depending upon proactive, hybrid, and reactive. Proactive routing schemes tend to sustain recent and consistent routing data of all the nodes in the network 11–14 . In the reactive‐routing schemes, the route is revealed if it is necessary.…”

Section: Introductionmentioning

confidence: 99%

A novel congestion control approach for optimal routing in Wireless Adhoc Networks

Kanthimathi

Prathuri

2022

Int J Communication

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Summary Congestion is a demanding issue in WANET owing to dynamic routing and resource constraints. Congestion controlling (CC) is a huge concern in attaining equality among e2e flow control and optimal utilization of network resources. In WANET, with distributed resources, if numerous senders compete for a similar bandwidth link, the data rates should be adjusted to avoid network overload that leads to compromises in QoS. This paper introduces a new routing approach with CC model that deployed MAODV for WANETs. Initially, the destination and source nodes are initialized, and subsequently, the MAODV find out the various routing path. Consequently, SGD‐DLNN recognizes all nodes' congestion status in revealed paths. Further, the MAODV assigns traffic in optimal congestion‐less paths if congestion occurs. Here, the black widow‐mutated cat swarm (BWM‐CS) model is deployed to choose the optimal paths based on traffic load density, life span of path, traffic load, remaining energy, link cost, and path distance. Eventually, the advantage of the suggested model is proven.

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“…The genetic algorithm was applied to enhance the latency, packet delivery ratio, and energy consumption of the system, and the best path is selected depending on the best fitness value [10]. An AODV imitation to demonstrate a basic routing idea with a meaningful method for visual learning [11].…”

Section: Introductionmentioning

confidence: 99%

D2d Multi-Objective Route Optimization in Manet Environment

Farhan

Croock²

2022

Iraqi Journal of ICT

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Over the past decades, wireless networks and devices have experienced intensive growth. Route discovery and selection from device to device (D2D) that are randomly distributed came across services trade-offs. This paper presents an optimal routing technique for the MANET environment-based D2D network. The optimization method considers the Lagrange Multiplier approach to maximize bit rate along with constraints minimization of the latency and packet loss. This method is executed for D2D nodes by active route election for links. An intensive simulation is applied and the obtained simulation results manifest the effectiveness of the presented Lagrange Optimization of Rate, Delay, and Packet loss algorithm (LORDP) in the optimal routing as compared to the Particle Swarm Optimization (PSO) and Genetic Algorithm (GA).

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Optimization of Multicast Ad Hoc On-demand Routing Protocol Based on Genetic Algorithm with Backup Paths in MANET

Cited by 13 publications

References 6 publications

Energy-Aware routing in MANET: Hybrid Genetic and Group Search Algorithm

Energy-Aware routing in MANET: Hybrid Genetic and Group Search Algorithm

A novel congestion control approach for optimal routing in Wireless Adhoc Networks

D2d Multi-Objective Route Optimization in Manet Environment

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