Dell products l.p. (20240305569). DYNAMIC QUALITY-OF-SERVICE (QOS) CONFIGURATION AND FORECASTING BASED ON WORKLOAD INTENT simplified abstract
Contents
DYNAMIC QUALITY-OF-SERVICE (QOS) CONFIGURATION AND FORECASTING BASED ON WORKLOAD INTENT
Organization Name
Inventor(s)
Narendrapal Singh of Pune (IN)
DYNAMIC QUALITY-OF-SERVICE (QOS) CONFIGURATION AND FORECASTING BASED ON WORKLOAD INTENT - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240305569 titled 'DYNAMIC QUALITY-OF-SERVICE (QOS) CONFIGURATION AND FORECASTING BASED ON WORKLOAD INTENT
Simplified Explanation: The patent application describes systems and methods that allow a client to determine the workload intent of an upcoming workload from an application running on the client. This workload intent is based on characteristics of the workload and is communicated to a server to optimize server resources accordingly.
Key Features and Innovation:
- Client determines workload intent of upcoming workload
- Workload intent is based on characteristics of the workload
- Client sends workload intent identifier to server
- Server optimizes resources based on workload intent identifier
- Client sends workload operations to server consistent with workload intent
Potential Applications: This technology could be used in cloud computing environments to efficiently allocate server resources based on anticipated workloads. It could also be applied in network management systems to optimize performance based on workload characteristics.
Problems Solved: This technology addresses the challenge of efficiently managing server resources in dynamic environments where workloads can vary in intensity and characteristics. By proactively determining workload intent, the system can optimize resource allocation and improve overall performance.
Benefits:
- Improved resource allocation
- Enhanced server performance
- Efficient utilization of server resources
- Proactive workload management
Commercial Applications: This technology could be valuable for cloud service providers, data centers, and enterprises with complex IT infrastructures. By optimizing server resources based on workload intent, organizations can improve efficiency and reduce operational costs.
Prior Art: Prior research in workload management and resource optimization in cloud computing environments may provide relevant background information for this technology. Researchers and practitioners in the field of network management and server optimization could offer insights into similar approaches.
Frequently Updated Research: Stay informed about the latest developments in workload management, resource optimization, and cloud computing to understand how this technology fits into the current research landscape.
Questions about Workload Intent Optimization: 1. How does workload intent optimization differ from traditional server resource allocation methods? 2. What are the potential challenges in implementing workload intent optimization in real-world IT environments?
Original Abstract Submitted
systems and methods are disclosed that determine, by a client, a workload intent of a workload that is forthcoming from an application executing on the client. the workload intent corresponds to one or more characteristics of the workload over a connection between the client and a server. the systems and methods send, by the client to the server, a workload intent identifier corresponding to the workload intent. the server is configured to optimize server resources based on the workload intent identifier. the systems and methods send, by the client, one or more workload operations to the server over the connection that are consistent with the workload intent.
