Affiliation:
1. Indian Institute of Technology Kharagpur, India
Abstract
Nature-Inspired algorithms have gained relevance particularly for solving complex optimization problems in engineering domain. An overview of implementation modeling of the established algorithms to newly developed algorithms is outlined. Mobile location management has vital importance in wireless cellular communication and can be viewed as an optimization problem. It has two aspects: location update and paging where the objective is to reduce the overall cost incurred corresponding to these two operations. The potential application of the Nature-Inspired algorithms to mobile location management is studied. Many such algorithms are recently being explored along with incremental modifications to the existing techniques. Finally, analysis and insights highlight the further scopes of the Nature-Inspired algorithms to mobile location management application.
Reference32 articles.
1. Alba, E., Garcia-Nieto, J., Taheri, J., & Zomaya, A. Y. (2008). New research in Nature Inspired Algorithms for Mobility Management in GSM Networks. Lecture Notes in Computer Science, 4974, 1-10.
2. Differential evolution for solving the mobile location management
3. A hybrid swarm intelligence approach to the registration area planning problem
4. Chu, S. C., Tsai, P., & Pan, J. S. (2006). Cat swarm optimization. In Q. Yang, & G. Webb (Eds.), Trends in artificial intelligence. Berlin: Springer.
5. Cui, Z., & Cai, X. (2013). Artificial plant optimization algorithm. Swarm intelligence and bio-inspired computation: Theory and applications, 351–365.