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Adaptive handover based on traffic balancing and multi-dimensional collaborative resource management in MEC environment


Due to the massive deployment of mobile terminal equipment in the multi-access edge computing environment, user terminals will frequently handover between different base stations, resulting in problems such as reduced device response speed and increased performance loss. In light of the foregoing, this study presents a method for terminal equipment in the MEC environment to execute adaptive handover between wireless access points. To achieve elastic and dynamic network resource management and minimize the load index, an adaptive handover model based on traffic perception is proposed. Then, the adaptive handover algorithm based on AP weight is used to calculate the AP with the highest weight, and the network state is centrally controlled and monitored in real time by software-defined network controller. Then, a multi-factor joint resource management method based on SDN is proposed to reduce the delay caused by computing task offloading. This includes a resource allocation model based on minimizing communication, computing, and energy consumption performance established, and the optimal values of task offloading decision and resource allocation vector calculated through the greedy strategy. The suggested technique may successfully increase system reaction speed and task offloading loss, according to the experimental findings.

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The work was supported by the National Natural Science Foundation of China (NSFC) under grants (No. 62171330, 61873341), Opening Project of Key Laboratory of Agricultural Information Service Technology, Ministry of Agriculture and Rural Affairs. Key Research and Development Plan of Hubei Province (No. 2020BAB102). Any opinions, findings, and conclusions are those of the authors and do not necessarily reflect the views of the above agencies.

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Correspondence to Youlong Luo.

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Li, C., Zhang, Y. & Luo, Y. Adaptive handover based on traffic balancing and multi-dimensional collaborative resource management in MEC environment. J Supercomput (2021).

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  • Multi-access edge computing
  • Resource allocation
  • Adaptive handover