Google llc (20240231943). Bin Packing simplified abstract
Contents
Bin Packing
Organization Name
Inventor(s)
Md Ehtesamul Haque of Santa Clara CA (US)
Thomas John Chestna of Middleborough MA (US)
Samuel Justin Smith of Mountain View CA (US)
Pedro Daniel Valenzuela Salvatierra of Santa Clara CA (US)
Olivier Robert Sevin of Winston-Salem NC (US)
Bin Packing - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240231943 titled 'Bin Packing
The abstract describes a system and method for assigning workloads to candidate host machines in a computing environment based on expected waste scores.
- The method involves receiving a workload scheduling request.
- Selecting a virtual machine type for executing the workload.
- Determining expected waste scores for each candidate host machine.
- Selecting the candidate host machine with the lowest waste score.
- Assigning the workload to the selected candidate host machine.
Potential Applications: - Cloud computing environments - Data centers - Virtualization technologies
Problems Solved: - Efficient workload assignment - Resource optimization - Minimizing waste in computing environments
Benefits: - Improved resource utilization - Cost savings - Enhanced performance in computing environments
Commercial Applications: Title: "Optimized Workload Assignment System for Cloud Computing" This technology can be used in cloud service providers to optimize resource allocation and improve overall efficiency in workload management.
Prior Art: Readers can explore prior research on workload scheduling algorithms in cloud computing environments to understand the evolution of this technology.
Frequently Updated Research: Stay updated on the latest advancements in workload optimization algorithms and resource management techniques in cloud computing environments.
Questions about Workload Assignment Optimization: 1. How does this system improve resource utilization in computing environments? - The system optimizes resource allocation by selecting candidate host machines with the lowest waste scores, ensuring efficient workload assignment. 2. What impact does this technology have on overall performance in cloud computing environments? - By assigning workloads to the most suitable host machines, the technology enhances performance and reduces resource wastage.
Original Abstract Submitted
a system and method for assigning a workload to one of a plurality of candidate host machines of a computing environment. the method may include receiving a request to schedule a workload, selecting a virtual machine type for executing the workload, for each candidate host machine of the plurality of candidate host machines, determining an expected waste score indicating a likelihood of resources at the candidate host machine remaining unused if the virtual machine type is assigned to the candidate host machine, selecting the candidate host machine for which the expected waste score is the lowest, and assigning the workload to the selected candidate host machine.
