Kirk A. Beaty

Dynamic Placement of Virtual Machines for Managing SLA Violations

A dynamic server migration and consolidation algorithm is introduced. The algorithm is shown to provide substantial improvement over static server consolidation in reducing the amount of required capacity and the rate of service level agreement violations. Benefits accrue for workloads that are variable and can be forecast over intervals shorter than the time scale of demand variability. The management algorithm reduces the amount of physical capacity required to support a specified rate of SLA violations for a given workload by as much as 50% as compared to static consolidation approach. Another result is that the rate of SLA violations at fixed capacity may be reduced by up to 20%. The results are based on hundreds of production workload traces across a variety of operating systems, applications, and industries.

On Strategies for Dynamic Resource Management in Virtualized Server Environments

Virtualization rapidly gains popularity affecting multiple levels of the computing stack. Since it decouples resources from their users it provides greater flexibility in terms of resource allocation but also brings new challenges for optimal design, provisioning, and runtime management of systems. This paper presents an analytical model of virtual machine migration that provides an estimate of the expected improvement in response time due to a migration decision. The model explicitly accounts for predictability of resource demands and characteristics of the virtualization infrastructure, such as migration time and overhead. It brings new insights into the decision strategies that should be used to improve the overall responsiveness of the system when dynamically managing virtual machines. The model is validated using simulations driven by data center resource utilization traces.

FOCUS: clustering crowdsourced videos by line-of-sight

We present a demonstration of FOCUS [1], a system to appear in the SenSys 2013 main conference. FOCUS is a video-clustering service for live user video streams, indexed automatically and in realtime by shared content. FOCUS uniquely leverages visual, 3D model reconstruction and multimodal sensing to decipher and continuously track a videos line-of-sight. Through spatial reasoning on the relative geometry of multiple video streams, FOCUS recognizes shared content even when viewed from diverse angles and distances. We believe FOCUS can enable a new family of applications, such as instant replay, augmented reality, citizen journalism, security breach detection, and disaster assessment. In the demonstration, we will show 325 video clips taken at Duke University Wallace Wade Stadium being processed in real-time via FOCUS pipeline. The recorded video clips contain one of three spots in the stadium: East Stand, Scoreboard, and West Stand. The demo shall be shown in the form of a web interface, first showing randomly clustered video clips. Later, on a button click, FOCUS shall process displayed videos in real-time, outputting clusters of videos, containing the common shared subject in each of them. For each successfully processed video clip in a cluster, we will further show similar clips from near, medium, and wide angle. To display performance and accuracy of FOCUS in indoor environments, a similar demonstration will be shown for an office space. FOCUS shall run on multi-node Hadoop cluster built on top of IBM SmartCloud platform.

DeskBench: Flexible virtual desktop benchmarking toolkit

The thin-client computing model has been recently regaining popularity in a new form known as the virtual desktop. That is where the desktop is hosted on a virtualized platform. Even though the interest in this computing paradigm is broad there are relatively few tools and methods for benchmarking virtual client infrastructures. We believe that developing such tools and approaches is crucial for the future success of virtual client deployments and also for objective evaluation of existing and new algorithms, communication protocols, and technologies. We present DeskBench, a virtual desktop benchmarking tool, that allows for fast and easy creation of benchmarks by simple recording of the users activity. It also allows for replaying the recorded actions in a synchronized manner at maximum possible speeds without compromising the correctness of the replay. The proposed approach relies only on the basic primitives of mouse and keyboard events as well as screen region updates which are common in window manager systems. We have implemented a prototype of the system and also conducted a series of experiments measuring responsiveness of virtual machine based desktops under various load conditions and network latencies. The experiments illustrate the flexibility and accuracy of the proposed method and also give some interesting insights into the scalability of virtual machine based desktops.

Desktop workload study with implications for desktop cloud resource optimization

Desktop cloud is a new delivery model in which end users connect to virtual desktops running in remote data centers. This paradigm offers multiple benefits both in terms of manageability as well as efficiency improvements. However, realizing this potential requires better understanding of desktop workload and its implications for desktop consolidation. We analyze CPU and memory usage on a sample of 35 desktops using a fine-grained 10 second averaging interval. Results provide insights into achievable efficiency improvements from desktop consolidation as well as detailed autocorrelation and variability behavior as a function of number of aggregated desktops. We also propose an interactivity classification method leading to functional form suitable for estimating residual durations of interactivity states. This finding can be leveraged in on-line proactive management algorithms for desktop cloud optimization.

Economics of cloud computing for enterprise IT

Enterprise adoption of cloud computing often requires a significant transformation of existing information technology (IT) systems and processes. To justify such a change, a viable business case must be made based on the economics of transformation such as cost of transformation, return on investment (ROI), and payback period analysis. The expected return from investing in the planned transformation and the estimated time to recoup the investments made determine whether such a transformation is to be undertaken. This paper describes models for determining the economics of transformation by considering the effects on the affected business and the IT processes. Using transformations to a development and test cloud and a desktop cloud as case studies, we develop models to quantify the costs associated with the transformation of traditional enterprise IT computing to one of these target cloud computing models. We discuss key factors that must be considered in determining the economic soundness of any transformation to cloud computing and in performing sensible ROI analysis. We also discuss best practices in developing practical ROI analysis tools for capturing the relevant factors affecting the economics of transformation.

Workload Monitoring in Hybrid Clouds

In this paper, we describe architecture and design of an innovative integrated monitoring solution for monitoring workloads in a hybrid cloud. Using off-the-shelf commercially available monitoring products and services, the solution described here allows for monitoring of a workload deployed across public and private clouds separated by enterprise firewall. The monitored data from endpoints distributed across the hybrid cloud is aggregated in a centralized monitoring system for analysis and for performing higher level management functions. Our solution is automated and can be integrated with other IT service management functions. The solution can leverage any endpoint monitoring functions and services a cloud service provider may offer. The monitoring framework described in this paper forms the basis for the hybrid cloud monitoring capability in IBMs hybrid cloud offering,IBM Service Management Extensions for Hybrid Cloud.

Managing responsiveness of virtual desktops using passive monitoring

Desktop virtualization is a new computing approach to application delivery and management. It leverages OS virtualization and remoting protocols to provide users with remote access to virtual machines running in a centralized data center. It promises significant benefits in terms of improved data security, reduced management complexity, and more efficient and flexible resource usage. However, it brings a lot of management challenges typical for centralized systems, with performance and quality of service management being one of the most important. This paper proposes a management algorithm suitable for efficient resource allocation in virtualized desktop environments and takes application performance QoS features into consideration. It proposes a novel, non-intrusive method for application and remoting protocol agnostic desktop responsiveness monitoring. Moreover, it is based on studies of desktop workload usage which enabled us to discover and leverage workload patterns that can lead to increased efficiency both in terms of desktop responsiveness and resource usage. We have prototyped the system and discuss several case studies validating the approach and illustrating the most important features of the solution.

IT autopilot: a flexible IT service management and delivery platform for small and medium business

IT Autopilot is a flexible architecture to support the delivery of information technology (IT) systems management services. Complex services that involve several tools require integration between the tools and automated processes that can invoke multiple tools. Designed primarily for the small and mid-sized enterprise, the architecture of IT Autopilot allows it to be deployed as a set of local and remote services delivered by the enterprise or by service providers as a flexible and extensible service offering. The IT Autopilot integrated IT service management platform is able to combine different tools and services to create specific, customized IT service solutions. Using the analogy of an autopilot on an airplane, the pilot first performs a set of manual operations to get the airplane off the ground and flying. Next, the autopilot is engaged to carry on normal flight operations. In our vision, there is an initial manual configuration step before IT Autopilot is enabled to take over and maintain the customers normal IT operational state. In this paper we explain our vision and describe the prototype system we have implemented.

Service Usage Metering in Hybrid Cloud Environments

With the proliferation of cloud based services - IaaS, PaaS, and SaaS - enterprises are increasingly consuming all type of IT services delivered by cloud providers. These cloud services are increasingly being used to create integrated solutions where some of the component services are delivered from on-premise private cloud environments and the remaining are provided by off-premise providers. While this best-of-breed approach results in flexible and agile business solutions, it also raises significant problems related to metering, billing, charge back and accounting. In this paper, after reviewing common hybrid cloud integration patterns, we discuss the importance of usage metering and the associated challenges in hybrid cloud environments. We then present a novel solution for metering of services delivered from multiple cloud providers. In this approach, service metering is keyed off of the life-cycle events generated by the service management controls across the hybrid cloud. By identifying life-cycle events associated with services consumed, service usage is tracked from all sources and then filtered and aggregated in a centralized manner. The aggregated information can then be used in an on-line manner for policy-based service delivery, charge-back, billing and reporting, and auditing. Based on this approach we have developed an end-to-end service usage metering and billing system for hybrid cloud environments. Some of the key underlying technologies have been incorporated in IBM SmartCloud Orchestrator - an IBM offering for managing workload patterns in multi cloud environments.