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Multi‐objective emperor penguin handover optimisation for IEEE 802.21 in heterogeneous networks
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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.
Institution of Engineering and Technology (IET)
Title: Multi‐objective emperor penguin handover optimisation for IEEE 802.21 in heterogeneous networks
Description:
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.
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