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公开(公告)号:US20230342177A1
公开(公告)日:2023-10-26
申请号:US17729249
申请日:2022-04-26
Applicant: VMware, Inc.
Inventor: Vamshik Shetty , Madan Singhal , Seena Ann Sabu
CPC classification number: G06F9/45558 , G06F9/30036 , G06F9/45545 , G06F2009/45562 , G06F2009/4557
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. Leader agents are periodically elected and/or reelected and agent groups change, over time, resulting in dissemination of control information across the agents of the distributed application-instantiation system.
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公开(公告)号:US20230028934A1
公开(公告)日:2023-01-26
申请号:US17458618
申请日:2021-08-27
Applicant: VMWARE, INC.
Inventor: VAMSHIK SHETTY , Madan Mohan Singhal , Seena Ann Sabu
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. Distributed-application instances are initially distributed to one or more agents. The agents then exchange distributed-application instances among themselves in order to locally optimize the set of distributed-application instances that they each manage.
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