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Bio-Inspired Algorithms for Mobile Location Management-A New Paradigm

机译:移动位置管理的生物启发算法 - 一个新的范式

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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.
机译:移动位置管理(MLM)在当今的蜂窝无线通信场景中获得了一个新方面。它有两个观点:位置登记和位置搜索以及两者之间的权衡给出了位置管理的最佳成本。调查了使用各种生物启发计算的位置管理成本优化的突出解决方案的概要。为了解决各种工程应用中的复杂优化问题,最近探讨了现有算法的增量改进以及更高的生物启发算法。本文调查并探讨了使用十五生物启发算法,遗传算法对新开发的花卉授粉算法和人工植物优化等十五生物启发算法的成本优化潜在方法。最后,我们调查了这些生物启发算法的潜在应用,以便在最近的文献中提供的移动位置管理问题中的成本优化,并指出了使用生物启发算法的性能优化和最佳蜂窝网络设计的动机。

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