Abstract—The continuous evolution of applications and the introduction of novel service models have significantly intensified the computational demands on Internet of Things (IoT) Mobile Terminal Devices (MTDs). In order to improve service capability, edge computing-enabled IoT shifts the computational burden from MTDs to edge computing hosts through task offloading. However, current task-to-host matching approaches exhibit significant limitations, particularly in their inability to anticipate tasks that are nearing the completion of data transmission and are about to arrive at the edge computing network. This shortcoming results in matching conflicts between tasks offloaded horizontally across sites and those directly offloaded from MTDs. To address this challenge, a Two-layer Asynchronous Conflict-reduced Task-to-host Matching (TACTM) scheme is proposed. The proposed scheme jointly considers the data upload progress of tasks and the dynamic load of edge computing hosts, aiming to reduce matching conflicts while optimizing task-to-host assignment. Simulation results demonstrate that the proposed TACTM scheme outperforms existing methods by achieving a 20.79% reduction in average conflict ratio, an 8.26% decrease in average processing time, a 4.30% drop in average task failure ratio, and a 4.05% improvement in average Quality of Experience (QoE).
 
Keywords—edge computing, internet of things, task offloading, task-to-host matching


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