Tuning the Cell Planning Problem in Mobile Upbringing to Optimize the Cost and Path Using Self-Motivated Algorithm

The rapid growth of wireless mobile networks and services, fueled by the next generation mobile communications systems research, has ushered in the era of ubiquitous computing. It is expected that future wireless mobile network will be more heterogeneous and that every mobile user will be able to gain access to the internet backbone by attaching his or her mobile computing devices to a wireless access point. The existing location management environment contains location registration and call delivery. In the location registration, the mobile terminal updates its current location information to some network databases, and the information can be retrieved for the future call delivery procedure.  In this research, we proposed a new mobility management scheme based on minimizing the total cost and to balance the registration (Location update) and search (Paging) operation by maintaining the mobility history. Due to their popularity and robustness, we have a proposal to hybrid the Ant colony optimization and Tabu search to solve the reporting cells planning problem in an optimized manner. In this research, some cells in the network are designated as reporting cells; by default mobile terminals update their position upon entering one of these reporting cells. To create such a planner the proposed revised optimization algorithm going to be implemented to show that the total cost is very less as compared with the existing algorithm used for mobility management. Our main aim is to clearly identify the shortest path which is optimum to the mobile application.