Improved genetic algorithm for channel allocation with channel borrowing in mobile computing

This paper exploits the potential of the Genetic Algorithm to solve the cellular resource allocation problem. When a blocked host is to be allocated to a borrowable channel, a crucial decision is which neighboring cell to choose to borrow a channel. It is an optimization problem and the genetic algorithm is efficiently applied to handle this. The Genetic Algorithm, for this particular problem, is improved by introducing a new genetic operator, named pluck, that incorporates a problem-specific knowledge in population generation and leads to a better channel utilization by reducing the average blocked hosts. The pluck operator makes the crucial decision of when and which cell to borrow with the future consideration that the borrowing should not lead the network to chaos. It makes a channel borrowing decision that minimizes the number of blocked hosts and improves the long-term performance of the network. Efficacy of the proposed method has been evaluated by experimentation.