A three-stage heuristic task scheduling for optimizing the service level agreement satisfaction in device-edge-cloud...

Area of Science:

• Distributed Computing
• Cloud Computing
• Edge Computing

Background:

• Device-edge-cloud cooperative computing addresses user device resource limitations.
• Task scheduling is crucial for resource efficiency in these environments.
• Existing methods often underutilize abundant cloud resources.

Purpose of the Study:

• Optimize task scheduling in device-edge-cloud cooperative computing.
• Maximize service level agreement satisfaction, focusing on meeting hard deadlines.
• Develop a resource-efficient scheduling method.

Main Methods:

• Formulated the problem as a binary nonlinear programming.
• Proposed a three-stage heuristic scheduling algorithm.
• Prioritized task scheduling across cloud, edge, and device resources.

Main Results:

• Achieved up to 59% improvement in service level agreement satisfaction.
• Maintained resource efficiency compared to existing methods.
• Demonstrated superior performance against eight classical and state-of-the-art methods.

Conclusions:

• The proposed heuristic method effectively optimizes task scheduling.
• It enhances service level agreement satisfaction without compromising resource efficiency.
• This approach offers a significant advancement for cooperative computing environments.