7 results about "Virtual machine scheduling" patented technology

This application provides a virtual machine scheduling method, apparatus, electronic device, storage medium, and computer program product. The method includes: generating a first optical signal based on the computing resource data of each of a plurality of computing nodes; processing the first optical signal by calling a diffraction deep neural network model to obtain a second optical signal; and determining a first computing node for creating a virtual machine among the plurality of computing nodes based on the position of the second optical signal projected on a set imaging plane.

The application discloses a virtual machine scheduling method, device and equipment and a computer storage medium. The method comprises the following steps: obtaining an IP address of a virtual machine in a first source host; calculating an IP address of a first virtual machine to be migrated in the first source host according to a preset IP number contained in continuous IP and the IP of the virtual machine; obtaining first resource data of the first virtual machine to be migrated according to the IP address of the first virtual machine to be migrated; obtaining second resource data of a first target host; calculating resource utilization rate estimation data of the first target host according to the first resource data and the second resource data; and determining first migration information according to the first resource data and the second resource data when the first source host and the first target host satisfy a first migration rule. According to the embodiment of the application, the problem that multiple virtual machines carrying the same service function are simultaneously faulty due to the failure of a single host can be solved.

This invention discloses a virtual machine scheduling method, apparatus, device, storage medium, and program product. The method includes: acquiring current optimization target preference information and physical host cluster status information; wherein the optimization target preference information is used to indicate the optimization preference ratio of at least two optimization targets; based on the optimization target preference information and the physical host cluster status information, optimizing virtual machine placement on the target physical host cluster to obtain a target virtual machine placement scheme; and scheduling virtual machines on the target physical host cluster based on the target virtual machine placement scheme. This invention optimizes virtual machine placement on the target physical host cluster by considering optimization target preference information, thereby focusing on optimizing the virtual machine placement scheme for the optimization target with the higher optimization preference ratio while considering multiple optimization targets, thus ensuring a globally optimal scheduling scheme and improving the accuracy of virtual machine scheduling.

The application discloses a virtual machine vcpu thread special-purpose scheduler based on a linux kernel and KVM, and the main body is VMSCH, characterized in that: the VMSCH is a virtual machine vcpu scheduler, the VMSCH priority is between an RT scheduling strategy and a CFS scheduling strategy, the priority is 99, and the RT priority is adjusted from 1-99 to 1-98, the VMSCH only manages the scheduling of vcpu threads and does not manage other threads. In the application, the duty cycle of vcpu exclusive pcpu can be dynamically configured, and it is unnecessary to configure at booting, so that the flexibility of the scheme of isolating pcpu for vcpu use by using isolate is avoided, pcpu resource waste caused by bandwidth limitation and idle state of the RT scheduling strategy is avoided, and the application has CPU architecture independence, and after implementation, any CPU architecture, such as X86, ARM and Loongson, can be naturally supported, so that the application has extremely wide application range.

A virtual machine orchestration scheduling method, an electronic device, and a storage medium are provided. The method includes: in response to a virtual machine secondary scheduling request, creating a first virtual machine planning model according to a deployment attribute feature of an initial virtual machine deployed on a physical machine, and determining a first deployment plan that minimizes a total scheduling cost; determining an initial virtual machine to be migrated out in each type of initial virtual machine in each physical machine; creating a second virtual machine planning model for a target initial virtual machine to be migrated out with an anti-affinity constraint in the initial virtual machine to be migrated out, and determining a second deployment plan that minimizes a scheduling cost of the target initial virtual machine to be migrated out; and performing virtual machine scheduling according to the first deployment plan and the second deployment plan.

This application provides a sandbox virtual machine scheduling method and apparatus based on a large language model, relating to the field of computer technology. The method includes: upon receiving a task request, performing metadata extraction and feature analysis on the target task to obtain a structured task object corresponding to the target task; the task object includes: metadata and task features; acquiring the current running state of the system and the text description corresponding to the target task, and using a large language model to perform semantic analysis and reasoning on the current running state, text description, and task object to generate a target scheduling plan; and scheduling virtual machines to execute the target task based on the target scheduling plan. The sandbox virtual machine scheduling method and apparatus based on a large language model provided in this application can not only dynamically allocate virtual machines according to task semantics and risk, but also optimize the scheduling strategy through self-learning via task execution feedback, thereby improving resource utilization and scheduling efficiency while ensuring system security.

The application discloses a scheduling method and device of a virtual machine scheduling domain, equipment and a storage medium. First, the number of VCPU required by a to-be-scheduled virtual machine in a target processor is obtained to obtain core requirement number, and a scheduling domain binding strategy is determined based on the core requirement number. A plurality of PCPU corresponding to each L3 Cache in the target processor is obtained, and a topology information table is constructed based on the corresponding relationship between them. Then, the actual available states of each PCPU included in the topology information table are determined, and the PCPU with an idle state as the actual available state is determined as a target core. Then, all target cores are grouped based on the corresponding L3 Cache of each target core in the topology information table to obtain a plurality of candidate core groups, so that the above strategy and the plurality of candidate core groups are used for scheduling domain binding of all VCPU. The application can improve the processor cache hit rate, reduce the data access delay, and further improve the overall running performance of the virtual machine.