A general framework of genetic multi-agent routing protocol for improving the performance of MANET environment

Abstract

These days, the fields of Mobile Ad hoc Network (MANET) have provided increasing prevalence and consequently, MANET is now a subject of considerable significance for the researchers to instigate research activities. MANET is the collaborative commitment of an assemblage of portable (or mobile) hubs (or nodes) without the necessary mediation of any unified (or centralized) gateway (or access point) or existent framework. There exists a growing inclination or course to embrace MANET for business utilization. MANET is a rising domain of research to give different services in communication to end-clients or consumers. However, these communication services of MANET utilize a large amount of transfer speed (or bandwidth) and a huge measure of web speed. Bandwidth optimization is essential in different information interchanges for fruitful acknowledgement and the application of such a technological innovation. This paper integrates the Genetic Algorithm (GA) and the Multi-Agent System (MAS) to improve the QoS requirements. The proposed framework called Genetic Multi-Agent Routing Protocol (GMARP). The aims of the proposed framework are to utilize the benefits of both approaches in order to fulfil QoS such as (delay, bandwidth, and the number of hops) in the different types of routing conventions (or protocols) such as being (proactive and reactive). In this paper is a simulation scenario to demonstrate the ability of the proposed framework to be satisfied with QoS requirements.

An adaptive multi-hop routing with IoT abstraction for minimizing delay-node capacity trade-offs in mobile ad-hoc network

“…The throughput observed in ( 6) is high compared to that in ( 9) and (10). Similarly, the delay in ( 5) is less compared to the delay in (8) and (11).…”

“…The limited node capacity is utilized for effective transmission with the aid for offloading. In this constraint, throughput and cost is given by (10),…”

“…MANET-IoT systems provide composite routing solutions for service discovery and providing multi-level application support. MANET nodes are equipped with smart computational abilities that help to form the core components of IoT [9], [10]. The interoperable nature of IoT aids MANET integration at ease intending to support large-scale smart applications.…”

“…The interoperable nature of IoT aids MANET integration at ease intending to support large-scale smart applications. MANET's general issues and challenges are resolved by the intelligent computing and communication characteristics of IoT systems [10]- [12]. The main contribution of the proposed work is described as follows: a) Designing MANET's adaptive multi-hop routing (A.M.R.)…”

A self adaptive new crossover operator to improve the efficiency of the genetic algorithm to find the shortest path

“…The order crossover (OX) suggested in [19]- [22] generates offspring by choosing a sub-tour from one parent and retaining the general order of bits of the other parent, which is also focused on the crossover operator with two points. In case of Cycle crossover operator (CX) proposed in [22]- [24] bits are taken from both parents in a circular order along with their position. This operator gives a good result but the drawback is that it gives the same offspring's with the same parents [25], [26].…”