Differential evolution for cost reduction in cellular network

Abstract

In cellular network cost involved in location management is higher but this issue is more common, crucial and complex problem. Although location management issues have been emerged in the field of communications no specific definition has been devised for it. Wireless network area is usually consisting of location area and paging area. The cost involved when a mobile subscriber moving in a particular service area. Since during a call the exact location of the subscriber must be known to the network the management of the network is to track the subscriber when a call comes to mobile device. For the same some cost is incurred that is location update cost and paging cost of the subscriber during the movement in a location service area. This study proposes a new evolutionary approach named Binary Differential Evolution (BDE) minimizes the total cost involved in wireless network. This technique is a stochastic, population-based optimization strategy proposed for combinatorial optimization problem to solve the location management issue. Here the given cellular network is partitioned into reporting cell and non-reporting cell so as to optimize the location area of a given cellular area. BDE is a meta-heuristic strategy presented to be a very powerful widely used technique based on evolutionary algorithms with some specific characteristics. Among the various evolutionary strategies BDE is one of the biological global optimization approach with reduced complexity has received a wide attraction from many fields such as computer science, economics and engineering fields. With the help of the realistic data for generating the test network simulation are carried out in different networks and the results are demonstrated and discussed in this work. The objective of this work is to define the best values to the Differential Evolution (DE) configuration by considering various parameters using realistic network.