Xen术语

Basics

  • guest operating system: An operating system that can run within the Xen environment.

  • hypervisor: Code running at a higher privilege level than the supervisor code of its guest operating systems.

  • virtual machine monitor ("vmm"): In this context, the hypervisor.

  • domain: A running virtual machine within which a guest OS executes.

  • domain0 ("dom0"): The first domain, automatically started at boot time. Dom0 has permission to control all hardware on the system, and is used to manage the hypervisor and the other domains.

  • unprivileged domain ("domU"): A domain with no special hardware access.

Approaches to Virtualization

  • full virtualization: An approach to virtualization which requires no modifications to the hosted operating system, providing the illusion of a complete system of real hardware devices.

  • paravirtualization: An approach to virtualization which requires modifications to the operating system in order to run in a virtual machine. Xen uses paravirtualization but preserves binary compatibility for user space applications.

Address Spaces

  • MFN (machine frame number): Real host machine address; the addresses the processor understands.

  • GPFN (guest pseudo-physical frame number): Guests run in an illusory contiguous physical address space, which is probably not contiguous in the machine address space.

  • GMFN (guest machine frame number): Equivalent to GPFN for an auto-translated guest, and equivalent to MFN for normal paravirtualised guests. It represents what the guest thinks are MFNs.

  • PFN (physical frame number): A catch-all for any kind of frame number. "Physical" here can mean guest-physical, machine-physical or guest-machine-physical.

Page Tables

  • l4 table: Define me.

  • l3 table: Define me.

  • l2 table: Define me.

  • l1 table: Define me.

  • SPT (shadow page table): shadow version of a guest OSes page table. Useful for numerous things, for instance in tracking dirty pages during live migration.

  • PAE: Intel's Physical Addressing Extensions, which enable x86/32 machines to address up to 64 GB of physical memory.

  • PSE (page size extension): used as a flag to indicate that a given page is ahuge/super page (2/4 MB instead of 4KB).

Shadow Page Table Modes

  • external: Define me.

  • translate: Define me.

x86 Architecture

  • HVM: Hardware Virtual Machine, which is the full-virtualization mode supported by Xen. This mode requires hardware support, e.g. Intel's Virtualization Technology (VT) and AMD's Pacifica technology.

  • SVM: full-virtualization support on AMD's Pacifica-enabled processors

  • VT-x: full-virtualization support on Intel's x86 VT-enabled processors

  • VT-i: full-virtualization support on Intel's IA-64 VT-enabled processors

  • shadow mode: Define me.

  • writable page tables: Define me.

Networking Infrastructure

  • backend: one half of a communication end point - interdomain communication is implemented using a frontend and backend device model interacting via event channels.

  • frontend: the device as presented to the guest; other half of the communication endpoint.

  • vif: virtual interface; the name of the network backend device connected by an event channel to a network front end on the guest.

  • event channel: Define me.

  • vethN: local networking front end on dom0; renamed to ethN by xen network scripts in bridging mode (FIXME)

  • pethN: real physical device (after renaming)

Migration

  • Live migration: A technique for moving a running virtual machine to another physical host, without stopping it or the services running on it.

Scheduling

  • BVT: The Borrowed Virtual Time scheduler is used to give proportional fair shares of the CPU to domains.

  • SEDF: The Simple Earliest Deadline First scheduler provides weighted CPU sharing in an intuitive way and uses realtime algorithms to ensure time guarantees.

 
【无人机】基于改进粒子群算法的无人机路径规划研究[和遗传算法、粒子群算法进行比较](Matlab代码实现)内容概要:本文围绕基于改进粒子群算法的无人机路径规划展开研究,重点探讨了在复杂环境中利用改进粒子群算法(PSO)实现无人机三维路径规划的方法,并将其与遗传算法(GA)、标准粒子群算法等传统优化算法进行对比分析。研究内容涵盖路径规划的多目标优化、避障策略、航路点约束以及算法收敛性和寻优能力的评估,所有实验均通过Matlab代码实现,提供了完整的仿真验证流程。文章还提到了多种智能优化算法在无人机路径规划中的应用比较,突出了改进PSO在收敛速度和全局寻优方面的优势。; 适合人群:具备一定Matlab编程基础和优化算法知识的研究生、科研人员及从事无人机路径规划、智能优化算法研究的相关技术人员。; 使用场景及目标:①用于无人机在复杂地形或动态环境下的三维路径规划仿真研究;②比较不同智能优化算法(如PSO、GA、蚁群算法、RRT等)在路径规划中的性能差异;③为多目标优化问题提供算法选型和改进思路。; 阅读建议:建议读者结合文中提供的Matlab代码进行实践操作,重点关注算法的参数设置、适应度函数设计及路径约束处理方式,同时可参考文中提到的多种算法对比思路,拓展到其他智能优化算法的研究与改进中。
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