A Novel Self-Adaptation Approach for Multi-Domain Communication Considering Heterogeneous Power Service in Data Centers  
[PERSON]  
1 State Grid Smart Grid Research Institute Co., Ltd., Beijing 102209, China; [EMAIL_ADDRESS] (S.-D.L. ); [EMAIL_ADDRESS] (M.H. ); [EMAIL_ADDRESS] (C.L. ); [EMAIL_ADDRESS] (X.Z. )1 State Grid Smart Grid Research Institute Co., Ltd., Beijing 102209, China; [EMAIL_ADDRESS] (S.-D.L. ); [EMAIL_ADDRESS] (M.H. ); [EMAIL_ADDRESS]. significance for collecting, analyzing, and providing feedback on the internal composition of the data center. Data centers must meet the needs of reducing carbon emissions and lowering global temperatures. In the trend of complex load resources and diversified load structures in data centers, building a safe, reliable, and practical data center management system is the key to building data center information [4], and it is also the foundation for the coordinated operation of electricity and computing power. In 2016, 178 countries around the world approved the Paris Agreement in Paris to address global warming and reduce carbon emissions. As a major energy consumer, data centers will become increasingly important in this agreement. Building a data center management system can facilitate the coordinated operation of computing power and electricity, assist in the precise and efficient management of new energy absorption and carbon emissions, and promote the achievement of the goal of countries signing the Paris Agreement. Modern information and communication technology, as the key to building and carrying out data center management system services, can help data center management systems achieve precise monitoring and regulation, effectively support the construction of normalized demand side management work in the power grid, and improve the quality of energy services (QoS). However, with the surge of computing power racks, data management systems under low-carbon requirements are facing challenges such as a surge in data volume, diversification and differentiation of communication services, and difficulty in adapting appropriate communication technologies to power communication services. Reference [5] introduced a method to evaluate communication technologies in power systems, combining the Analytic Hierarchy Process (AHP) with triangular fuzzy numbers (TFN). This method, utilizing a fuzzy judgment matrix and AHP, effectively ranks technologies and identifies Power Line Carrier as the superior option. Reference [6] advanced electric power communication network security by introducing a fuzzy AHP. This work significantly bolsters network reliability and establishes a structured risk assessment framework, offering a notable contribution to power system security management. The AHP method was used in Reference [7] to select the best communication technologies for electrical substations. Optical fiber, NBPLC, and LoRa were identified for urban and suburban areas, while satellite communication was preferred for rural areas. This aids in improving the efficiency and reliability of electrical distribution networks. The F-TOPSIS method was used in Reference [8] to select smart grid communication technologies based on cost, security, and reliability. This approach provides a systematic framework for comparing technologies and guides the deployment of efficient and secure smart grid communication infrastructures. Reference [9] introduced a layered architecture integrating fog and cloud computing to enhance smart city communication networks, focusing on smart energy systems. However, this approach overlooks the AHP method's subjectivity, potentially leading to judgment errors. Additionally, a single form of communication technology cannot meet the diverse needs of power communication.