Congestion Control in Wireless Networks
Route Optimization with Genetic Algorithm
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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. 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 an...
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. 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.
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