“Location Tracking Strategies” is an important issue for Personal Communications Services (PCS). Usually, callee’s location may vary from time to time. Therefore, in mobile communications’ environment, the system must keep track of callee’s location all the times to transfer information to the required callee correctly. This thesis proposes a “Moving Patterns Strategy (MP)” for PCS with the following steps. First, the local system will collect user’s history moving data, find the periodic users through statistic method, and generate the forecasting location for any time period. Then the caller and callee may exchange their forecasting data properly within communications period. Using this strategy, the time for call delivery may be shorted, and overall system’s performance may be prompted due to decreasing the frequencies of querying HLR database. On the implementation, we will study user’s history moving data, design a general algorithm to figure out its periodic rules. Next, a protocol will be presented to combine MP strategy into PCS. Then, we will simulate our system to verify its functions and possible benefits.
“Location Tracking Strategies” is an important issue for Personal Communications Services (PCS). Usually, callee’s location may vary from time to time. Therefore, in mobile communications’ environment, the system must keep track of callee’s location all the times to transfer information to the required callee correctly. This thesis proposes a “Moving Patterns Strategy (MP)” for PCS with the following steps. First, the local system will collect user’s history moving data, find the periodic users through statistic method, and generate the forecasting location for any time period. Then the caller and callee may exchange their forecasting data properly within communications period. Using this strategy, the time for call delivery may be shorted, and overall system’s performance may be prompted due to decreasing the frequencies of querying HLR database. On the implementation, we will study user’s history moving data, design a general algorithm to figure out its periodic rules. Next, a protocol will be presented to combine MP strategy into PCS. Then, we will simulate our system to verify its functions and possible benefits.