Inter-Satellite Cooperative Offloading Decision and Resource Allocation in Mobile Edge Computing-Enabled...

Area of Science:

• Computer Science
• Electrical Engineering
• Aerospace Engineering

Background:

• Mobile edge computing (MEC) integrated with satellite-terrestrial networks (STNs) offers task computing for Internet of Things (IoT) devices.
• Resource limitations on local satellite MEC servers can hinder the processing of demanding IoT tasks.
• Redundant computing resources on neighboring satellites present an opportunity for inter-satellite cooperation.

Purpose of the Study:

• To investigate and develop an inter-satellite cooperation strategy for MEC-enabled STNs.
• To address the challenge of insufficient local satellite MEC resources by leveraging neighboring satellites.
• To minimize the overall task completion delay for IoT devices within the network.

Main Methods:

• Designed a system model for MEC-enabled STNs incorporating inter-satellite cooperation.
• Formulated and decomposed the task completion delay minimization problem.
• Proposed a joint offloading decision and resource allocation scheme using the Grey Wolf Optimizer (GWO) and Lagrange multiplier method.

Main Results:

• The proposed inter-satellite cooperative scheme effectively utilizes idle resources from neighboring satellites.
• The optimization scheme successfully balances task offloading decisions and resource allocation.
• Simulation results indicate superior performance compared to existing baseline schemes.

Conclusions:

• Inter-satellite cooperation is a viable strategy to enhance MEC-enabled STNs.
• The developed GWO-based offloading and Lagrange-based resource allocation scheme effectively minimizes task completion delay.
• The findings contribute to more efficient and robust IoT services in satellite networks.