Copyright © 2004 Elsevier B.V. All rights reserved.
Received 3 May 2004;
References and further reading may be available for this article. To view references and further reading you must purchase this article.
Abstract
Mobility prediction is one of the most essential issues that need to be explored for mobility management in mobile computing systems. In this paper, we propose a new algorithm for predicting the next inter-cell movement of a mobile user in a Personal Communication Systems network. In the first phase of our three-phase algorithm, user mobility patterns are mined from the history of mobile user trajectories. In the second phase, mobility rules are extracted from these patterns, and in the last phase, mobility predictions are accomplished by using these rules. The performance of the proposed algorithm is evaluated through simulation as compared to two other prediction methods. The performance results obtained in terms of Precision and Recall indicate that our method can make more accurate predictions than the other methods.
Keywords: Location prediction; Data mining; Mobile computing; Mobility patterns; Mobility prediction
Article Outline
- 1. Introduction
- 2. Background
- 2.1. Problem definition
- 2.2. Related work
- 3. Mobility prediction based on mobility rules
- 3.1. Mining user mobility patterns from graph traversals
- 3.2. Generation of mobility rules
- 3.3. Mobility prediction
- 4. Experimental results
- 4.1. Simulation design
- 4.2. Algorithms used for comparison
- 4.3. Impact of maximum number of predictions
- 4.4. Impact of minimum support value
- 4.5. Impact of minimum confidence value
- 4.6. Impact of corruption factor
- 4.7. Impact of outlier percentage
- 5. Conclusion
- References
- Vitae






E-mail Article
Add to my Quick Links

Cited By in Scopus (13)







