Collaborative Task Offloading Optimization for Satellite Mobile Edge Computing Using Multi-Agent Deep Reinforcement Learning

Hangyu Zhang

doi:10.1109/TVT.2024.3405642

Collaborative Task Offloading Optimization for Satellite Mobile Edge Computing Using Multi-Agent Deep Reinforcement Learning

2024-10-01

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DOI：10.1109/TVT.2024.3405642

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Satellite mobile edge computing (SMEC) achieves efficient processing for space missions by deploying computing servers on low Earth orbit (LEO) satellites, which supplements a strong computing service for future satellite-terrestrial integrated networks. However, considering the spatio-temporal constraints on large-scale LEO networks, inter-satellite cooperative computing is still challenging. In this paper, a multi-agent collaborative task offloading scheme for distributed SMEC is proposed. Facing the time-varying available satellites and service requirements, each autonomous satellite agent dynamically adjusts offloading decisions and resource allocations based on local observations. Furthermore, for evaluating the behavioral contribution of an agent to task completion, we adopt a deep reinforcement learning algorithm based on counterfactual multi-agent policy gradients (COMA) to optimize the strategy, which enables energy-efficient decisions satisfying the time and resource restrictions of SMEC. An actor-critic (AC) framework is effectively exploited to separately implement centralized training and distributed execution (CTDE) of the algorithm. We also redesign the actor structure by introducing an attention-based bidirectional long short-term memory network (Atten-BiLSTM) to explore the temporal characteristics of LEO networks. The simulation results show that the proposed scheme can effectively enable satellite autonomous collaborative computing in the distributed SMEC environment, and outperforms the benchmark algorithms.

Keyword:

Satellites

Task analysis

Satellite broadcasting

Optimization

Low earth orbit satellites

Computational modeling

Resource management

Satellite mobile edge computing

distributed cooperative computing

computation offloading

resource allocation

multi-agent deep reinforcement learning

Collaborative Task Offloading Optimization for Satellite Mobile Edge Computing Using Multi-Agent Deep Reinforcement Learning

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