The large model and block-chain contract mechanism in cloud native scenarios have always been a focus of attention in the engineering and scientific research fields. Data silos are repositories of diverse data inputs, characterized by discrete storage and decentralized nodes. They contrast with the heterogeneous mechanisms employed by services like MINO and NAS. Multipoint fusion, as a digital twin middleware with multidimensional table structure topology, can be used to present noise, loss function, and reward mechanism applications based on the fragmented information of data silos. In order to better solve the current difficulties of data silos and distributed multi-point fusion storage of application and business data analysis in the financial field, This magazine focuses on the splitting methods and service governance of cloud native infrastructure layer (Opstack+K8S), paas layer (mq+sdk+monitoring component+DB, etc.), and upper application servicemesh and other fields, more to solve the performance bottleneck problems such as commercial landing in the current big model, metaverse and other fields based on scientific research theory, and also from one side to essentially solve the constraint relationship between network and computing power, Better serve the leading companies in the current mainstream financial field and the multiple nodes in the research and development of frontline internet products. The performance bottleneck is mainly to solve the high concurrency, high reliability, and The trade-off between different indicators such as high availability is equivalent to the application layer, middle layer, and technology base being able to act as third-party calls through a unified external REST. The problem of mapping matching is demonstrated through various methods to demonstrate the compatibility and adaptability of optimization algorithms, optimization models, and multi-dimensional architectures.

The special issue can explore topics such as:

(1) Data silos and their characteristics in cloud native environments

(2) Techniques and methodologies for multi-point fusion of fragmented information

(3) Performance bottlenecks and optimization approaches in big data models, metaverse, and other fields

(4) Application of optimization algorithms, models, and multi-dimensional architectures

(5) Challenges and solutions in high concurrency, high reliability, and high availability in cloud native systems

(6) Compatibility and adaptability of optimization algorithms and multi-dimensional architectures in cloud native scenarios

(7) Decentralized Metaverse: Vision, Trends and Challenges

(8) Security network system supporting Metaverse applications: CoG MIN

(9) Open standards and Open-source model guide the Metaverse and AI