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CloudTops: Latency aware placement of Virtual Desktops in Distributed Cloud Infrastructures
Matti Hiltunen, Kaustubh Joshi, Richard Schlichting, Nishio Yamada, Toshiyuki Moritsu
CLOSER 2013: 3rd International Conference on Cloud Computing and Services Science,
2013.
[PDF]
[BIB]
SciTePress Copyright
The definitive version was published in 2013. , 2013-05-08
{Latency sensitive interactive applications such as virtual desktops for enterprise workers are slated to be important driving applications for next generation cloud infrastructures. Determining where to geographically place desktop VMs in a globally distributed cloud so as to optimize user-perceived performance is an important and challenging problem. Historically, the performance of thin-client-based systems has been predominantly characterized in terms of the front-end network link between the thin client and the desktop. In this paper, we show that for typical enterprise applications, back-end network connectivity to the filesystems and applications that support the desktop can be equally important, and that the optimal balance between the front-end and back-end links depends on the precise workload. To help make dynamic decisions about desktop VM placement, we propose a per-user model that can be used to automatically construct user profiles, and to predict the optimal location for a user’s desktop based on their past and current usage patterns. Using experimental evaluation of several typical Enterprise applications, we show that our methodology can accurately predict which of many distributed data centers to use for a particular user’s workload even if details of the precise applications being used are not known.}
Self-management of Adaptable Component-based Applications
Liliana Rosa, Luis Rodrigues, Antonia Lopes, Matti Hiltunen, Richard Schlichting
IEEE Transactions on Software Engineering,
2012.
[PDF]
[BIB]
IEEE Copyright
This version of the work is reprinted here with permission of IEEE for your personal use. Not for redistribution. The definitive version was published in 2012. , 2012-08-01
{The problem of self-optimization and adaptation in the context of customizable systems is becoming increasingly important with the emergence of complex software systems and unpredictable execution environments. Here, a general framework for automatically deciding on when and how to adapt a system whenever it deviates from the desired behavior is presented. In this framework, the system’s target behavior is described as a high-level policy that establishes goals for a set of performance indicators. The decision process is based on information provided independently for each component that describes the available adaptations, their impact on performance indicators, and any limitations or requirements. The technique consists of both offline and online phases. Offline, rules are generated specifying component adaptations that may help to achieve the established goals when a given change in the execution context occurs. Online, the corresponding rules are evaluated when a change occurs to choose which adaptations to perform. Experimental results using a prototype framework in the context of a web-based application demonstrate the effectiveness of this approach.}
Using CPU Gradients for Performance-aware Energy Conservation in Multitier Systems
Kaustubh Joshi, Matti Hiltunen, Richard Schlichting, Shuyi Chen, William Sanders
Sustainable Computing: Informatics and Systems ,
2011.
[PDF]
[BIB]
Elsevier Copyright
The definitive version was published in Sustainable Computing: Informatics and Systems. , 2011-05-01
{Dynamic voltage and frequency scaling (DVFS) and virtual machine (VM) based server consolidation are techniques that hold promise for energy conservation, but can also have adverse impacts on system performance. For the responsiveness-sensitive multitier applications running in today�s data centers, queuing models should ideally be used to predict the impact of CPU scaling on response time, to allow appropriate runtime trade-offs between performance and energy use. In practice, however, such models are difficult to construct and thus are often abandoned for ad-hoc solutions. In this paper, an alternative measurement-based approach that predicts the impacts without requiring detailed application knowledge is presented. The approach uses a new set of metrics, the CPU gradients, that can be automatically measured on a running system using lightweight and nonintrusive CPU perturbations. The practical feasibility of the approach is demonstrated using extensive experiments on multiple multitier applications, and it is shown that simple energy controllers can use gradient predictions to derive as much as 57% energy savings while still meeting response time constraints.}
Diagnosis in Practice
Richard Schlichting
Website of 5th Latin American Symposium on Dependable Computing (LADC) ,
2011.
[BIB]
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An Exploration of L2 Cache Covert Channels in Virtualized Environments
Yunjing Xu, Michael Bailey, Farnam Jahanian, Kaustubh Joshi, Matti Hiltunen, Richard Schlichting
Proceedings of the ACM Cloud Computing Security Workshop (CCSW),
CCSW 2011: The ACM Cloud Computing Security Workshop in conjunction with the 17th ACM Conference on ,
ACM,
pp To appear.,
2011.
[PDF]
[BIB]
ACM Copyright
(c) ACM, 2011. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in CCSW 2011: The ACM Cloud Computing Security Workshop in conjunction with the 17th ACM Conference on , 2011-10-21.
Recent exploration into the unique security challenges of cloud computing have shown that when virtual machines belonging to different customers share the same physical machine, new forms of cross-VM covert channel communica- tion arise. In this paper, we explore one of these threats, L2 cache covert channels, and demonstrate the limits of these this threat by providing a quantification of the channel bit rates and an assessment of its ability to do harm. Through progressively refining models of cross-VM covert channels from the derived maximums, to implementable channels in the lab, and finally in Amazon EC2 itself we show how a variety of factors impact our ability to create effective chan- nels. While we demonstrate a covert channel with consider- ably higher bit rate than previously reported, we assess that even at such improved rates, the harm of data exfiltration from these channels is still limited to the sharing of small, if important, secrets such as private keys.
Probabilistic Model-Driven Recovery in Distributed Systems
Kaustubh Joshi, Matti Hiltunen, Richard Schlichting, William Sanders
IEEE Transactions on Dependable and Secure Computing,
2010.
[BIB]
{Automatic system monitoring and recovery has the potential to provide effective, low-cost ways to improve dependability in distributed software systems. However, automating recovery is challenging in practice because accurate fault diagnosis is difficult given the common monitoring tools and techniques with low fault coverage, poor fault localization, detection delays, and false positives. In this paper, we present a holistic model-based approach that overcomes these challenges and enables automatic recovery in distributed systems. To do so, it uses theoretically sound techniques including Bayesian estimation and Markov decision theory to provide controllers that choose good, if not optimal, recovery actions according to a user-defined optimization criteria. By combining monitoring and recovery, the approach realizes benefits that could not have been obtained by using them in isolation. We experimentally validate our framework by fault injection on realistic e-commerce systems.}
CPU Gradients: Performance-aware Energy Conservation in Multitier Systems
Shuyi Chen, Kaustubh Joshi, Matti Hiltunen, Richard Schlichting, William Sanders
Proceedings of the 1st IEEE International Green Computing Conference,
IEEE International Green Computing Conference,
2010.
[BIB]
Dynamic voltage and frequency scaling (DVFS) and virtual machine (VM) based server consolidation are techniques that hold promise for energy conservation, but can also have adverse impacts on system performance. For the responsiveness-sensitive multitier applications running in today's data centers, queuing models should ideally be used
to predict the impact of CPU scaling on response time, to allow appropriate runtime trade-offs between performance and energy use. In practice, however, such models are difficult to construct and thus are often abandoned for ad-hoc solutions. In this paper, an alternative measurement-based approach that predicts the impacts without requiring detailed application knowledge is presented. The approach uses a new set of metrics, the CPU gradients, that can be automatically measured on a running system using lightweight and nonintrusive CPU perturbations. The practical feasibility of the approach is demonstrated using extensive experiments on multiple multitier applications, and it is shown that simple energy controllers can use gradient predictions to derive as much as 50% energy
savings while still meeting response time constraints.
Blackbox Prediction of the Impact of DVFS on End-toEnd Performance of Multitier Systems
Matti Hiltunen, Kaustubh Joshi, Richard Schlichting, Shuyi Chen, Sanders William
2009.
[PDF]
[BIB]
A Cost-Sensitive Adaptation Engine for Server Consolidation of Multitier Applications
Matti Hiltunen, Kaustubh Joshi, Richard Schlichting, Gueyoung Jung, Calton Pu
2009.
[PDF]
[BIB]
Link Gradients: Predicting the Impact of Network Latency on Multi-Tier Applications
Kaustubh Joshi, Matti Hiltunen, Richard Schlichting, Shuyi Chen, Sanders William
2008.
[PDF]
[BIB]
Generating Adaptation Policies for Multi-Tier Applications in Consolidated Server Environments
Matti Hiltunen, Richard Schlichting, Kaustubh Joshi, Gueyoung Jung, Calton Pu
2007.
[PDF]
[BIB]
An Off-Line Approach for Generating On-Line Adaptation Policies
Matti Hiltunen, Kaustubh Joshi, Richard Schlichting, Gueyoung Jung, Calton Pu
2007.
[PDF]
[BIB]
Peer-to-Peer Error Recovery for Hybrid Satellite-Terrestrial Networks
Matti Hiltunen, Richard Schlichting, Vinay Vaishampayan, Eric Weigle, Andrew . Chien
2005.
[PDF]
[BIB]
Methods And Systems For Transferring Data Over Electronic Networks,
Tue Mar 06 16:09:30 EST 2012
Methods and systems for managing the transfer of large data files across electronic data networks optimally in accordance with the desired results of the users. The present invention takes into consideration the user-defined transfer requirements, the data characteristics, and the characteristics of the entirety of the network, including both the access links and the backbone and processing and storage resources in the backbone. The present invention the enables users to more optimally transfer data within the limitations of the existing network capabilities, negating requirements to update local or remote network facilities.
Quantifying The Impact Of Network Latency On The End-To-End Response Time Of Distributed Applications,
Tue Dec 06 16:02:20 EST 2011
A method for measuring system response sensitivity, using live traffic and an analysis that converts randomly arriving stimuli and reactions to the stimuli to mean measures over chosen intervals, thereby creating periodically occurring samples that are processed. The system is perturbed in a chosen location of the system in a manner that is periodic with frequency p, and the system's response to arriving stimuli is measured at frequency p. The perturbation, illustratively, is with a square wave pattern.
Systems, Devices, And Methods For Initiating Recovery,
Tue May 19 15:38:39 EDT 2009
Certain exemplary embodiments comprise method that can comprise receiving information indicative of a fault from a monitor associated a network. The method can comprise, responsive to the information indicative of the fault, automatically determining a probability of a fault hypothesis. The method can comprise, responsive to a determination of the fault hypothesis, automatically initiating a recovery action to correct the fault.
IFIP Outstanding Service Award, 2011.
For outstanding contributions to the International Federation of Information Processing (IFIP) and the Informatics Community.
IEEE Fellow, 2002.
For contributions to fault-tolerant computing and distributed systems.
ACM Fellow, 2001.
For his influential research on fault-tolerant and dependable computing, configurable network protocols, and distributed systems, and for his outstanding leadership of and service to the computing community.
