Cost reduction using diffrential evolution in mobile network

Location management is a major issue of mobile network. As the subscribers travel to various locations different access points of the mobile terminal changes. The total cost involved is location update cost and paging cost for searching a subscriber when move in a particular service area. This work minimizes the total cost with the help of many different evolutionary techniques. This paper presents Binary Differential Evolution to solve the location management issue by partitioning the given cellular network into reporting cell and non-reporting cell so as to minimize the location management cost. Binary Differential Evolution (BDE) is a stochastic, population-based optimization strategy, is a meta-heuristic approach presented to be a very powerful widely used technique. BDE yet simple has shown to be very powerful and widely used method. Among the various optimization techniques BDE is a biological global optimization approach with reduced complexity. This paper uses the realistic data for generating the test network. With the help of reporting cell for simulation results in different networks are demonstrated and discussed in this paper. From the results of BDE result it is shown to be effective with less number of iteration. This work has the objective of defining the best values to the Differential Evolution (DE) parameters and setting the DE scheme, which allows us to obtain better results when compared to classical strategies and the other authors´ results.