Affiliation:
1. Aden University, Yemen
2. Jawaharlal Nehru University - New Delhi, India
Abstract
The scarcity of the radio channel is the main bottleneck toward maintaining the quality of service (QoS) in a mobile cellular network. As channel allocation schemes become more complex and computationally demanding, alternative computational models that include knowledge-based algorithms and provide the means for faster processing are becoming a topic of research interest. An efficient deterministic technique, capable of handling channel allocation problems, is introduced as an alternative. The proposed model utilizes the Global Positioning System (GPS) data for tracing the hosts’ likely movements within and across the cells and allocates the channels to the mobile devices accordingly. The allocation of the channels to the mobile hosts is deterministic in the sense that the decision of the channel allocation is based on the realistic data received from the GPS about the hosts’ movements. The performance of the proposed technique has been evaluated by conducting the simulation experiments for the two parameters—call blocking and handoff failures. Also, a comparison of the proposed model with an earlier model has been carried out to estimate the effectiveness of the proposed technique. Experimental results reveal that the proposed technique performs better and is more realistic as well.
Subject
Computer Networks and Communications,Management Information Systems
Reference21 articles.
1. The geometric dynamic channel allocation as a practical strategy in mobile networks with bursty user mobility
2. Bisnath, S., Wells, D., Howden, S., & Stone, G. (2003, September 22-26). The use of a GPS-equipped buoy for water level determination. In Proceedings of IEEE OCEANS 2003, San Diego, CA (pp. 1241-1246). IEEE.
3. Boukerche, A., Tingxue, H., & Kaouther, A. (2005, September). Design and performance evaluation of a QoS-based dynamic channel allocation protocol for wireless and mobile networks. In Proceedings of 13th IEEE / ACM International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, Atlanta, Georgia (pp. 445-452). IEEE.
4. Fernando, G. L., Goldberg, D. E., & Pelikan, M. (2000, July 8-12). Time complexity of genetic algorithms on exponentially scaled problems. Proceedings of the Genetic and Evolutionary Computing Conference, Las Vegas, NV (pp. 151-158). Morgan Kaufmann.
5. Gupta, S. K., Low, M. K., & Tan, C. W. (1998, April 20-23). A new approach to simulate GPS measurements. In Proceedings of the 1998 IEEE Position Location and Navigation Symposium, Palm Springs, CA (pp. 236-242). IEEE.