A Prediction Based Resource Reservation Algorithm for Service Handover in Edge Computing

Abstract

Handover is a crucial issue in ensuring the continuity of edge services in edge computing (EC) systems. Failure to handle hand-off properly may result in delays, data loss, or service interruption during service switching. Therefore, optimizing the hand-off process to ensure service continuity and satisfactory user experience is a significant challenge in the design of edge computing systems. In this paper, we propose a resource reservation algorithm that reserves a portion of computing resources in each base station to meet quality of service (QoS) requirements during service switching. We use an LSTM model to predict the number of new and existing users at a future time point to provide decision guidance for the resource reservation algorithm. Extensive simulation experiments demonstrate that the proposed algorithm outperforms the benchmark algorithms in a variety of environmental conditions.