Abstract
With the development of informatization, network businesses are expanding and business functions are becoming more powerful; thus, network infrastructure has begun to face new challenges in serving businesses. Research regarding the dynamic deployment of network slices according to business requirements is urgently needed. To develop a realistic and complete view of service providers' decision-making process, adaptation costs must be considered. Function orchestration of virtualized radio access networks is a critical way for network slices to offer web apps customized service. In this paper, we develop a mathematically optimized model for function orchestration and propose an orchestration strategy using a form of particle swarm optimization (VNFPSO), in virtualized radio access network. Bearing in mind the openness of radio access network frameworks, discreteness of network functions, and proliferation of network traffic, we have enhanced the state-of-the-art PSO algorithm in terms of inertia weight, particle mutation, and factor learning to improve the speed of obtaining a global approximate optimal solution. Simulated experimental results show that this strategy could decrease rejection rates in virtualized radio access networks and improve the utility of network system resources.
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