Service-Aware Cooperative Task Offloading and Scheduling in Multi-access Edge Computing Empowered IoT

Multi-access edge computing(MEC) enables computation task offloading and data processing at close proximity to provide rich end-users services with ultra-low latency in Internet of things(IoT). However, the high heterogeneity of the edge node configuration and the diversity of services pose challenges in fully utilizing the computing capacity in MEC. In this paper, we consider the problem of service-aware cooperative task offloading and scheduling in a three-tier MEC empowered IoT where the service requests from IoT devices can be distributed among edge nodes or further offloaded to remote cloud. As this problem is proven to be NP-hard, we proposed a two-layer Cooperative workload Initialization and Distribution Algorithm (CIDA) to solve the problem with low time complexity by decomposing it into two subproblems: 1) the optimization problem of offloading profile under dynamic resource allocation determined by the workload type, and 2) optimization problem of computation resources allocation under given offloading profile. Extensive experiments demonstrate that CIDA achieves superior performance compared to other approaches and scales well as the system size increases.