Abstract
Edge computing allows users to access to applications with high-bandwidth and low-latency. The advantages include fast data transmission and task migration between mobile devices and edge cloud. In this work, we propose a novel task migration model with cached data to reduce service response time and energy consumption. An evolutionary task offloading schema is then developed to optimize the migration strategy on the edge cloud. As a result, our schema is able to minimize the aforementioned objective function while satisfying the resource constraints. We have conducted simulations to prove the effectiveness of our schema in energy-saving, during task migration.
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