Prediction-Based Task Allocation and Processor Control for Distributed Green Data Centers with Optical Satellite Links

The scale of data centers has increased significantly in recent years, with their energy demands adversely impacting the environment. Consequently, distributed green data centers, equipped powered renewable energy, have gained considerable attention. However, conventional optical fibers installations for such data centers incur high costs and face locations constraints. Therefore, this study explores the use of optical satellite communications for distributed green data centers. Efficient task allocation is crucial to minimize service delays. However, task transmission time depends on satellite-ground link performance, while processing time is affected by the energy at data centers. Additionally, the non-linear relationship between the server per-formance and power consumption highlights the inefficiency, task allocation without future-aware considerations. To address this, we propose a method for task allocation and processing performance control that minimizes service delays through predictions of task generation, link performance, and power generation. In the proposed method, we formulate an optimization problem based on prediction data and find its solution by exploration. Simulations demonstrate that the proposed method significantly reduces tasks transmission and processing times.