Route Optimization and Congestion Control in Wireless Network: Route optimization, Congestion control, Genetic Algorithm

Chauhan, Ms. Sheetal (Author)/ Sarao, Prof. Pushpender (Author)

ISBN 10: 9999319661 / ISBN 13: 9789999319669

Published by Eliva Press, 2024

About this Item

78 pages. 6.00x0.18x9.00 inches. In Stock.

Seller Inventory # x-9999319661

Bibliographic Details

• Title: Route Optimization and Congestion Control in Wireless Network: Route optimization, Congestion control, Genetic Algorithm
• Publisher: Eliva Press
• Publication Date: 2024
• Language: English
• ISBN 10: 9999319661
• ISBN 13: 9789999319669
• Binding: Paperback
• Condition: Brand New
• Weight: 0.12 kilograms

About this title

Synopsis

The network is made up of two types of components: nodes and communication lines. The nodes typically handle the network protocols and provide switching capabilities. A node is usually itself a computer (general or special) which runs specific network software. The communication lines may take many different shapes and forms, even in the same network. Examples include: copper wire cables, optical fiber, radio channels, and telephone lines. By applying mathematics to a problem of the real world mostly means, at first, modeling the problem mathematically, may be with hard restrictions, idealizations, or simplifications, then solving the mathematical problem, and finally drawing conclusions about the real problem based on the solutions of the mathematical problem. Since about 60 years, a shift of paradigms has taken place in some sense; the opposite way has come into fashion. The point is that the world has done well even in times when nothing about mathematical modeling was known. The one of the alternate ways is evolutionary computation, which encompasses three main components- Evolution strategies, Genetic Algorithms and Evolution programs. Genetic Algorithms encode a potential solution to a specific problem on a simple chromosome like data structure and apply recombination operators to several structures so as to preserve critical information. Shortest path routing algorithms are well established problem and addressed by many researchers in different ways. One such alternative is to use a GA-based routing algorithm. However, it is also known that GA-based routing algorithm is not fast enough for real-time computation. We propose to use this huge stochastic optimization tool for Optimum Path Routing Problem. GA may be used for optimization of searching process for optimum path routing in a network for optimization of both the distance and the congestion problem in a network. The proposed book “Congestion control in Wireless Networks” has been implemented in MATLAB 7.0.