IEEE concentrates on the development of effective media independent handover (IEEE 802.21 MIH) services. The major aim of IEEE 802.21 MIH is to optimise the handover process to make an uninterrupted handover service with less delay. The handover process is categorised into two types a horizontal and vertical process. Among them, vertical handover (VH) needs parameter optimisation for better performance. The optimised result depends on the parameter selection to avoid the rate of handover failure. Although the availability of various optimisation procedures for VH management, many existing works consider one/two parameters for VH optimisation. So that resultant optimal handover solution will not be better in terms of failure rate, latency, and accuracy. Thus, a method of multi-objective emperor penguin handover optimisation (MOEPHO) is developed in the proposed work, which includes almost overall network parameters for VH optimisation. So that, accurate handover with less delay and the minimum energy consumption is achieved in this work. Network simulator 2 working platform is used for the research evaluation. The resultant performances are compared with whale optimisation algorithm-based neural network, adaptive cross-layer design, fuzzy intelligent decision making and novel type 2-fuzzy logic controller to show the effectiveness of MOEPHO.

中文翻译：

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异构网络中IEEE 802.21的多目标帝企鹅切换优化

IEEE专注于有效的媒体独立切换（IEEE 802.21 MIH）服务的开发。IEEE 802.21 MIH的主要目标是优化切换过程，以减少延迟，实现不间断的切换服务。切换过程分为水平过程和垂直过程两种。其中，垂直切换（VH）需要优化参数以获得更好的性能。优化结果取决于参数选择，以避免切换失败率。尽管可以使用各种优化程序进行VH管理，但许多现有工作都考虑了VH优化的一两个参数。因此，最终的最佳切换解决方案在故障率，延迟和准确性方面将不会更好。从而，在提出的工作中，开发了一种多目标帝企鹅切换优化（MOEPHO）的方法，该方法几乎包括用于VH优化的整个网络参数。因此，在这项工作中可以实现更准确的切换，且延迟更少且能耗最低。网络模拟器2工作平台用于研究评估。将所得结果与基于鲸鱼优化算法的神经网络，自适应跨层设计，模糊智能决策和新型2型模糊逻辑控制器进行了比较，以证明MOEPHO的有效性。