Virtualization can provide significant benefits in data centers by enabling virtual machine migration to eliminate hotspots. We present Sandpiper, a system that automates the task of monitoring and detecting hotspots, determining a new mapping of physical to virtual resources and initiating the necessary migrations. Sandpiper implements a black-box approach that is fully OS- and application-agnostic and a gray-box approach that exploits OS- and application-level statistics. We implement our techniques in Xen and conduct a detailed evaluation using a mix of CPU, network and memory-intensive applications. Our results show that Sandpiper is able to resolve single server hotspots within 20 seconds and scales well to larger, data center environments. We also show that the gray-box approach can help Sandpiper make more informed decisions, particularly in response to memory pressure.

/pdf/black-box-and-gray-box-strategies-for-virtual-machine-4dlglfch88.pdf

Black-box and gray-box strategies for virtual machine migration

Cloud computing allows business customers to scale up and down their resource usage based on needs. Many of the touted gains in the cloud model come from resource multiplexing through virtualization technology. In this paper, we present a system that uses virtualization technology to allocate data center resources dynamically based on application demands and support green computing by optimizing the number of servers in use. We introduce the concept of "skewness&#x201D; to measure the unevenness in the multidimensional resource utilization of a server. By minimizing skewness, we can combine different types of workloads nicely and improve the overall utilization of server resources. We develop a set of heuristics that prevent overload in the system effectively while saving energy used. Trace driven simulation and experiment results demonstrate that our algorithm achieves good performance.

Dynamic Resource Allocation Using Virtual Machines for Cloud Computing Environment

A management capability is provided for a virtual computing platform. In one example, this platform allows interconnected physical resources such as processors, memory, network interfaces and storage interfaces to be abstracted and mapped to virtual resources (e.g., virtual mainframes, virtual partitions). Virtual resources contained in a virtual partition can be assembled into virtual servers that execute a guest operating system (e.g., Linux). In one example, the abstraction is unique in that any resource is available to any virtual server regardless of the physical boundaries that separate the resources. For example, any number of physical processors or any amount of physical memory can be used by a virtual server even if these resources span different nodes. A virtual computing platform is provided that allows for the creation, deletion, modification, control (e.g., start, stop, suspend, resume) and status (i.e., events) off the virtual servers which execute on the virtual computing platform and the management capability provides controls for these functions. In a particular example, such a platform allows the number and type of virtual resources consumed by a virtual server to be scaled up or down when the virtual server is running. For instance, an administrator may scale a virtual server manually or may define one or more policies that automatically scale a virtual server. Further, using the management API, a virtual server can monitor itself and can scale itself up or down depending on its need for processing, memory and I/O resources. For example, a virtual server may monitor its CPU utilization and invoke controls through the management API to allocate a new processor for itself when its utilization exceeds a specific threshold. Conversely, a virtual server may scale down its processor count when its utilization falls. Policies can be used to execute one or more management controls. More specifically, a management capability is provided that allows policies to be defined using management object's properties, events and/or method results. A management policy may also incorporate external data (e.g., an external event) in its definition. A policy may be triggered, causing the management server or other computing entity to execute an action. An action may utilize one or more management controls. In addition, an action may access external capabilities such as sending notification e-mail or sending a text message to a telephone paging system. Further, management capability controls may be executed using a discrete transaction referred to as a 'job.' A series of management controls may be assembled into a job using one or management interfaces. Errors that occur when a job is executed may cause the job to be rolled back, allowing affected virtual servers to return to their original state.

System and method for managing virtual servers

Power delivery, electricity consumption, and heat management are becoming key challenges in data center environments. Several past solutions have individually evaluated different techniques to address separate aspects of this problem, in hardware and software, and at local and global levels. Unfortunately, there has been no corresponding work on coordinating all these solutions. In the absence of such coordination, these solutions are likely to interfere with one another, in unpredictable (and potentially dangerous) ways. This paper seeks to address this problem. We make two key contributions. First, we propose and validate a power management solution that coordinates different individual approaches. Using simulations based on 180 server traces from nine different real-world enterprises, we demonstrate the correctness, stability, and efficiency advantages of our solution. Second, using our unified architecture as the base, we perform a detailed quantitative sensitivity analysis and draw conclusions about the impact of different architectures, implementations, workloads, and system design choices.

https://people.cs.pitt.edu/~kirk/cs3150spring2010/2008_asplos_nopowerstruggles.pdf

No "power" struggles: coordinated multi-level power management for the data center

A cloud computing environment having a plurality of computing nodes is described. A plurality of permissions associated with a cloud customer is created. A first set of permissions from the plurality of permissions is associated with one or more objects. Each of the first set of permissions describes an action performed on an object. A second set of permissions from the plurality of permissions is associated with one or more users. Each of the second set of permissions describes an action to be performed by one or more users.

Virtual computing infrastructure

A method for restarting a virtual machine in a virtual computing system having a plurality of hosts and a resource scheduler for the plurality of hosts includes writing a placement request for the virtual machine to a shared channel that is accessible by the resource scheduler. The method further includes reading a placement result from the shared channel, wherein the placement result is generated by the resource scheduler responsive to the placement request; and restarting the virtual machine in accordance with the placement result.

System and method for restarting a workload based on global load balancing

In virtualized computer system in which a guest operating system runs on a virtual machine of a virtualized computer system and has direct access to a hardware device coupled to the virtualized computer system via a communication interface, a computer-implemented method of handling interrupts from the hardware device to the guest operating system includes: (a) receiving a physical interrupt from the hardware device on a shared interrupt line of an interrupt controller; (b) masking the shared interrupt line of the interrupt controller; (c) generating a virtual interrupt corresponding to the physical interrupt to the guest operating system; and (d) the guest operating system executing an interrupt service routine.

Handling interrupts when virtual machines have direct access to a hardware device

Methods for logging and replaying input/output (I/O) events for a virtual machine (VM). The I/O events may be asynchronous or synchronous. In particular, one embodiment is a computer-implemented method for logging input/output (I/O) events for a virtual machine, the method including: executing the virtual machine from a checkpoint; and logging external events, including I/O events; wherein logging an I/O event comprises logging the event, and then, logging I/O data relating to the I/O event.

Logging and Replaying Input/Output Events for a Virtual Machine

A computer architecture includes a first operating system (COS), which may be a commodity operating system, and a kernel, which acts as a second operating system. The COS is used to boot the system as a whole. After booting, the kernel is loaded and displaces the COS from the system level, meaning that the kernel itself directly accesses predetermined physical resources of the computer. All requests for use of system resources then pass via the kernel. System resources are divided into those that, in order to maximize speed, are controlled exclusively by the kernel, those that the kernel allows the COS to handle exclusively, and those for which control is shared by the kernel and COS. In the preferred embodiment of the invention, at least one virtual machine (VM) runs via a virtual machine monitor, which is installed to run on the kernel. Each VM, the COS, and even each processor in a multiprocessor embodiment, are treated as separately schedulable entities that are scheduled by the kernel. Mechanisms for high-speed I/O between VM's and I/O devices are also included.

System software displacement in a virtual computer system

A backup VM is allowed to enter live execution mode at instruction boundaries but not in the middle of emulation of a single instruction. This is accomplished by having the last log entry of multiple entries generated during emulation of an instruction to have an indication of a “go-live” point and by having the backup VM not replay log entries provided by the primary VM beyond the log entry that indicates the “go-live” point.

Michael Nelson

Papers

System and method for restarting a workload based on global load balancing

Handling interrupts when virtual machines have direct access to a hardware device

Logging and Replaying Input/Output Events for a Virtual Machine

System software displacement in a virtual computer system

Transitioning of virtual machine from replay mode to live mode