Abstract: Example methods and systems for decentralized network topology adaptation in a in a peer-to-peer (P2P) network are described. In one example, a first computer system may obtain first attribute information associated with the first computer system; and second attribute information associated with a second computer system. Based on the first and second attribute information, the first computer system may generate a connection confidence prediction associated with a connection between the first computer system and the second computer system. The connection confidence prediction may indicate whether the connection is a suboptimal connection associated with a suboptimal network topology. In response to determination that the connection confidence prediction satisfies a break condition, the first computer system may break the connection between the first computer system and the second computer system, but otherwise maintain the connection.

Abstract: The current document is directed to methods and systems that automatically instantiate complex distributed applications by deploying distributed-application instances across the computational resources of one or more distributed computer systems and that automatically manage instantiated distributed applications. The current document discloses decentralized, distributed automated methods and systems that instantiate and manage distributed applications using multiple agents installed within the computational resources of one or more distributed computer systems. The agents exchange distributed-application instances among themselves in order to locally optimize the set of distributed-application instances that they each manage. In addition, agents organize themselves into groups with leader agents to facilitate efficient, decentralized exchange of control information acquired by employing machine-learning methods.

Abstract: The current document is directed to methods and systems that automatically instantiate complex distributed applications by deploying distributed-application instances across the computational resources of one or more distributed computer systems and that automatically manage instantiated distributed applications. Automatic deployment of multiple instances of a distributed application across computational resources, such as distribution of microservices of a microservice-based application across one or more distributed computer systems, and scaling of instantiated distributed applications are computationally difficult optimization problems that are not amenable to traditional centralized approaches. The current document discloses decentralized, distributed automated methods and systems that instantiate and manage distributed applications. Reinforcement-learning-based agents are installed within the computational resources of one or more distributed computer systems.

Abstract: The current document is directed to improved distributed service-oriented applications developed according to a new and improved architecture for developing distributed service-oriented applications. The new and improved architecture includes a stateless-communications-protocol interface to external users and clients, services implemented by actors that communicate using message passing, and a distributed data grid for persistent storage of data. Distributed service-oriented applications developed according to the new and improved architecture are referred to as “RAD-squared applications” (“RAD{circumflex over (?)}2 applications”). The acronym “RAD{circumflex over (?)}2” stands for “Rapid Application Development with REST-actor-data-grid” and the acronym “REST” stands for the Representational State Transfer (“REST”) protocol. Alternative stateless communications protocols can be used as alternatives to REST in RAD{circumflex over (?)}2 applications.