文亚凤, 程祖铭, 刘欣雅, et al. Energy Optimization Management of Edge Data Centers Considering Computing Power-electrothermal Coupling[J]. 2026, 46(1): 186-197.
文亚凤, 程祖铭, 刘欣雅, et al. Energy Optimization Management of Edge Data Centers Considering Computing Power-electrothermal Coupling[J]. 2026, 46(1): 186-197. DOI: 10.13334/j.0258-8013.pcsee.241546.
考虑算力-电热耦合的边缘数据中心能量优化管理
摘要
用户日益增长的算力需求催生出大量数据中心边缘化部署,其相应的能耗成本不断增加,碳排放量大幅上升。为解决上述问题,该文提出考虑边缘数据中心算力-电热耦合特性的能量优化管理方法。首先,提出包含边缘数据中心内负载处理、任务迁移、电池电量调控、边缘数据中心网络服务质量(quality of service,QoS)、可再生能源消纳与功率管理多个子系统的协同能量管理模型,并设计考虑主机内部中央处理单元(central processing unit,CPU)温度感知与算力调节的任务迁移策略,避免任务迁移可能导致的主机过热与任务阻塞问题;其次,构建以边缘数据中心长期运营成本最小化为目标的优化问题;最后,基于李亚普诺夫优化技术,将上述问题转化为短期在线求解问题。仿真分析表明,所提方法能够有效降低数据中心整体运营成本,并保证数据中心长期稳定运行。
Abstract
Growing user demand for computing power has spawned a large number of edge data center deployments
which have correspondingly increased energy costs and carbon emissions. In order to solve above problems
this paper presents an energy optimization management considering the coupling characteristics of computing power and electrothermal behaviors in edge data centers. Firstly
a collaborative energy management model is proposed
which integrates modules of task migration
battery power regulation
quality of service (QoS)
renewable energy consumption and power management. A task migration strategy based on internal Central Processing Unit temperature sensing and computing power adjustment is designed to avoid overheating and task blocking. Secondly
an optimization problem is formulated to minimize the long-term operating cost of edge data centers. Lastly
leveraging the Lyapunov optimization algorithm
the aforementioned issues are transformed into short-term online optimization problems. Simulation analysis demonstrates that the proposed method can effectively reduce the overall operational costs while ensuring long-term stable operation.