Research on Task Encoding Scheme in Edge Computing Scenarios

To overcome the additional computation delay caused by straggler nodes in edge computing environments, a task encoding strategy based on systematic MDS code is proposed. The objective is to minimize the weighted sum of the total task processing delay and total energy consumption. A three-tier task allocation model consisting of network terminal devices, task encoding schedulers, and edge servers is established. Additionally, an optimal encoding parameter search algorithm is designed. The task encoding scheduler uses the encoding parameters determined by the algorithm to segment and encode the tasks, generating redundant subtasks. These subtasks are then allocated to edge servers for parallel processing, and the computation results are returned to the task encoding scheduler to recover the final results. Simulation results show that the proposed encoding scheme effectively reduces the total system cost compared to uncoded, replication-coded, and FRC schemes, while also demonstrating strong stability.