Parallel genetic approach for routing optimization in large ad hoc networks

Abstract

<span>This article presents a new approach of integrating parallelism into the genetic algorithm (GA), to solve the problem of routing in a large ad hoc network, the goal is to find the shortest path routing. Firstly, we fix the source and destination, and we use the variable-length chromosomes (routes) and their genes (nodes), in our work we have answered the following question: what is the better solution to find the shortest path: the sequential or parallel method?. All modern systems support simultaneous processes and threads, processes are instances of programs that generally run independently, for example, if you start a program, the operating system spawns a new process that runs parallel elements to other programs, within these processes, we can use threads to execute code simultaneously. Therefore, we can make the most of the available central processing unit (CPU) cores. Furthermore, the obtained results showed that our algorithm gives a much better quality of solutions. Thereafter, we propose an example of a network with 40 nodes, to study the difference between the sequential and parallel methods, then we increased the number of sensors to 100 nodes, to solve the problem of the shortest path in a large ad hoc network.</span>

A new routing method based on ant colony optimization in vehicular ad-hoc network

“…In (17), the authors presented the new approach for integrating parallelism into the genetic algorithm (GA), with the objective to solve the routing problem in ad-hoc network containing 40 nodes. The results obtained show the better quality of solutions for 40 nodes.…”

Effects of different geometric patterns on free form gridshell structures

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Parallel Binary Rafflesia Optimization Algorithm and Its Application in Feature Selection Problem

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