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Pure Edge computing (PEC) aims to bring cloud applications and services tothe edge of the network to support the growing user demand for time-sensitiveapplications and data-driven computing. However, mobility and limitedcomputational capacity of edge devices pose challenges in supporting someurgent and computationally intensive tasks with strict response time demands.If the execution results of these tasks exceed the deadline, they becomeworthless and can cause severe safety issues. Therefore, it is essential toensure that edge nodes complete as many latency-sensitive tasks as possible.\\In this paper, we propose a Robust Adaptive Workload Orchestration(R-AdWOrch) model to minimize deadline misses and data loss by using prioritydefinition and a reallocation strategy. The results show that R-AdWOrch canminimize deadline misses of urgent tasks while minimizing the data loss oflower priority tasks under all conditions.

A Robust Adaptive Workload Orchestration in Pure Edge Computing