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 virtualization technique, in accordance with one embodiment of the present invention, includes emulating the small computing system interface (SCSI) protocol to access a virtual SCSI storage device backed by a file stored on network attached storage (NAS).

SCSI protocol emulation for virtual storage device stored on NAS device

Embodiments maintain high availability of software application instances in a fault domain. Subordinate hosts are monitored by a master host. The subordinate hosts publish heartbeats via a network and datastores. Based at least in part on the published heartbeats, the master host determines the status of each subordinate host, distinguishing between subordinate hosts that are entirely inoperative and subordinate hosts that are operative but partitioned (e.g., unreachable via the network). The master host may restart software application instances, such as virtual machines, that are executed by inoperative subordinate hosts or that cease executing on partitioned subordinate hosts.

Maintaining high availability of a group of virtual machines using heartbeat messages

Selecting a master node in a group of computing nodes Computing nodes exchange suitability messages, candidate messages, and master messages to indicate the state of each node A deterministic algorithm based on scores and timings is executed by each computing node to encourage each node to select the same master node

Selecting a master node using a suitability value

An elastic filesystem for temporary data provides storage space for virtual machines (VMs) in a distributed computing system. The filesystem redirects accesses to virtual disks in VMs to a common pool file. The system provides performance and storage efficiency at least on par with local, direct attached virtual disks, while providing a single pool of shared storage that is provisioned and managed independently of the VMs. The system provides storage isolation between VMs storing temporary data in that shared pool. Also, storage space for temporary data may be allocated on demand and reclaimed when no longer needed, thereby supporting a wide variety of temporary space requirements for different Hadoop jobs.

Elastic temporary filesystem

A computer has a hardware memory arranged into portions that are separately addressable using first identifiers, which are represented using a first number of address bits. A subsystem that is able to address a second space of the hardware memory using second identifiers initiates I/O requests directed to a device that is able to address a different, first memory space using first identifiers, which are represented using a second number of address bits. The second identifiers are initially mapped into the second memory space, but for any I/O request that meets a remapping criterion, the corresponding second identifier is remapped to one of the first identifiers that identifies a portion of the memory in the first memory space. The second space is different from the first space and the second number of address bits is greater less than the first number of address bits.

Michael Nelson

Papers

SCSI protocol emulation for virtual storage device stored on NAS device

Maintaining high availability of a group of virtual machines using heartbeat messages

Selecting a master node using a suitability value

Elastic temporary filesystem

Transparent memory address remapping