Issue No. 06 - June (2013 vol. 12)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TMC.2012.87
Chien-Chun Huang-Fu , National Chiao Tung University, Hsinchu
Yi-Bing Lin , National Chiao Tung University, Hsinchu
Nabil Alrajeh , King Saud University, Riyadh
Investigating human movement behavior is important for studying issues such as prediction of vehicle traffic and spread of contagious diseases. Since mobile telecom network can efficiently monitor the movement of mobile users, the telecom's mobility management is an ideal mechanism for studying human movement issues. The problem can be abstracted as follows: What is the probability that a person at location $(A)$ will move to location $(B)$ after $(T)$ hours. The answer cannot be directly obtained because commercial telecom networks do not exactly trace the movement history of every mobile user. In this paper, we show how to use the standard outputs (handover rates, call arrival rates, call holding time, and call traffic) measured in a mobile telecom network to derive the answer for this problem.
Mobile computing, Telecommunications, Accuracy, Biomedical monitoring, Global Positioning System, Mobile radio mobility management, mobility management, Human movement, Little's Law, mobile computing
Chien-Chun Huang-Fu, Yi-Bing Lin, Nabil Alrajeh, "Predicting Human Movement Based on Telecom's Handoff in Mobile Networks", IEEE Transactions on Mobile Computing, vol. 12, no. , pp. 1236-1241, June 2013, doi:10.1109/TMC.2012.87