Mobile location management (MLM) has gained a new aspect in today’s cellular wireless communication scenario. It has two perspectives: location registration and location search and a trade-off between the two give optimal cost for location management. An outline of the prominent solutions for the cost optimization in location management using various bio-inspired computations is surveyed. For solving complex optimization problems in various engineering applications more and more such bio-inspired algorithms are recently being explored along with incremental improvement in the existing algorithms. This paper surveys and discusses potential approaches for cost optimization using fifteen bio-inspired algorithms such as Artificial Neural Network, Genetic Algorithm to newly developed Flower Pollination Algorithm and Artificial Plant Optimization. Finally, we survey the potential application of these bio-inspired algorithms for cost optimization in mobile location management issue available in the recent literature and point out the motivation for the use of bio-inspired algorithms in cost optimization and design of optimal cellular network.
CITATION STYLE
Swayamsiddha, S., Parija, S., Singh, S. S., & Sahu, P. K. (2017). Bio-inspired algorithms for mobile location management—a new paradigm. In Advances in Intelligent Systems and Computing (Vol. 516, pp. 35–44). Springer Verlag. https://doi.org/10.1007/978-981-10-3156-4_4
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