Docker-based Heterogeneous Resource Configuration and Task Allocation Mechanism

As wireless communication and Internet of Things (IoT) technologies advance, edge computing brings computing and storage capabilities closer to users, providing low-latency and high-quality services. However, the limited resources of edge servers and the diverse resource demands of heterogeneous tasks may result in high latency and poor energy efficiency. To address this challenge, we investigate a Docker-based resource management framework for edge servers, involving the allocation of heterogeneous tasks and the configuration of the Docker container clusters. Then, we formulate the problem as one of minimizing energy consumption and task latency, concerning task allocation and server resource management, subject to server resource constraints. To solve this problem, we propose an effective task assignment and resource management strategy, which is developed based on convex optimization theory, aiming to achieve an approximate optimal solution. Simulation results demonstrate that, compared to other algorithms, the proposed algorithm significantly reduces server operating power consumption and task response latency.