Priority-based DAG task offloading and secondary resource allocation in IoT edge computing environments

Abstract

With the development of IoT, the concept of intelligent services has gradually come to the fore. Intelligent services usually involve a large number of computation intensive tasks with data dependencies that are often modelled as directed acyclic graphs (DAGs), and the offloading of DAG tasks is complex and has proven to be an NP hard challenge. As a key research issue, the task offloading process migrates the computation intensive tasks from resource-constrained IoT devices to nearby edge servers, and pursuing a lower delay and energy consumption. However, data dependencies among tasks are complex, and it is challenging to coordinate the computation intensive tasks among multiple edge servers. In this paper, a flexible and generic DAG task model is built to support the associative task offloading process with complex data dependencies in IoT edge computing environments. Additionally, a priority-based DAG task offloading algorithm and a secondary resource allocation algorithm are proposed to minimize the response delay and improve the resource utilization of edge servers. Experimental results demonstrate that the proposed method can well support the DAG task offloading process with the shortest response delay, while outperforming all the benchmark policies, which is suitable for IoT edge computing environments.