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Efficient Management of Data Center Resources for Massively Multiplayer

by Online Games, Vlad Nae, Ru Iosup, Stefan Podlipnig, Radu Prodan, Dick Epema, Thomas Fahringer, Multiplayer Online Games
"... (MMOGs) can include millions of concurrent players spread across the world. To keep these highly-interactive virtual environments online, a MMOG operator may need to provision tens of thousands of computing resources from various data centers. Faced with large resource demand variability, and with m ..."
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(MMOGs) can include millions of concurrent players spread across the world. To keep these highly-interactive virtual environments online, a MMOG operator may need to provision tens of thousands of computing resources from various data centers. Faced with large resource demand variability

AN EFFICIENT ALGORITHM FOR MINING FREQUENT ITEMSETS OVER DATA STREAMS UNDER THE TIME- SENSITIVE SLIDING-WINDOW MODEL

by V. Soujanya, S. Ramanaiah
"... Mining frequent itemsets has been widely studied over the last decade, mostly focuses on mining frequent itemsets from static databases. In many of the new applications, data flow through the internet or sensor networks which extend the mining techniques to a dynamic environment. The main challenges ..."
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challenges include a quick response to the continuous request, a compact summary of the data stream, and a mechanism that adapts to the limited resources. Here, we propose a time-sensitive sliding window model for mining frequent itemsets from data streams. Our approach consists of a storage structure

Managing Overloaded Hosts for Dynamic Consolidation of Virtual Machines in Cloud Data Centers Under Quality of Service Constraints

by Anton Beloglazov, Rajkumar Buyya, Senior Member - IEEE Transactions on Parallel and Distributed Systems (TPDS , 2012
"... Abstract—Dynamic consolidation of Virtual Machines (VMs) is an effective way to improve the utilization of resources and energy efficiency in Cloud data centers. Determining when it is best to reallocate VMs from an overloaded host is an aspect of dynamic VM consolidation that directly influences th ..."
Abstract - Cited by 24 (2 self) - Add to MetaCart
Abstract—Dynamic consolidation of Virtual Machines (VMs) is an effective way to improve the utilization of resources and energy efficiency in Cloud data centers. Determining when it is best to reallocate VMs from an overloaded host is an aspect of dynamic VM consolidation that directly influences

Whom You Know Matters: Venture Capital Networks and Investment Performance,

by Yael Hochberg , Alexander Ljungqvist , Yang Lu , Steve Drucker , Jan Eberly , Eric Green , Yaniv Grinstein , Josh Lerner , Laura Lindsey , Max Maksimovic , Roni Michaely , Maureen O'hara , Ludo Phalippou Mitch Petersen , Jesper Sorensen , Per Strömberg Morten Sorensen , Yael Hochberg , Johnson - Journal of Finance , 2007
"... Abstract Many financial markets are characterized by strong relationships and networks, rather than arm's-length, spot-market transactions. We examine the performance consequences of this organizational choice in the context of relationships established when VCs syndicate portfolio company inv ..."
Abstract - Cited by 138 (8 self) - Add to MetaCart
of information, contacts, and resources among VCs (Bygrave (1988)), for instance by expanding the range of strategic alliance partners and launch customers for their portfolio companies. No less importantly, strong relationships with other VCs likely improve the chances of securing follow-on VC funding

Dynamic resource allocation and power management in virtualized data centers

by Rahul Urgaonkar, Ulas C. Kozat, Ken Igarashi, Michael J. Neely - in Network Operations and Management Symposium (NOMS), 2010 IEEE , 2010
"... Abstract—We investigate optimal resource allocation and power management in virtualized data centers with time-varying workloads and heterogeneous applications. Prior work in this area uses prediction based approaches for resource provisioning. In this work, we take an alternate approach that makes ..."
Abstract - Cited by 29 (0 self) - Add to MetaCart
maximizes a joint utility of the average application throughput and energy costs of the data center. Our approach is adaptive to unpredictable changes in the workload and does not require estimation and prediction of its statistics. Index Terms—Data Center Automation, Cloud Computing, Virtualization

Longer-term effects of Head Start

by Eliana Garces , Duncan Thomas , Janet Currie Ucla , Nber - American Economic Review , 2002
"... Abstract Public early intervention programs like Head Start are often justified as investments in children. Yet nothing is known about the long-term effects of Head Start. This paper draws on unique data from the Panel Study of Income Dynamics to provide new evidence on the effects of Head Start on ..."
Abstract - Cited by 131 (5 self) - Add to MetaCart
our analysis of these non-experimental data as an important complement to experimental sources and a first step towards establishing whether Head Start confers long-term benefits on participants. For reasons spelled out in detail below, our methods likely provide lower bound estimates of any positive

Self-adaptive and self-configured CPU resource provisioning for virtualized servers using Kalman filters

by Evangelia Kalyvianaki, Steven Hand - in 2009 ICAC
"... Data center virtualization allows cost-effective server consol-idation which can increase system throughput and reduce power consumption. Resource management of virtualized servers is an important and challenging task, especially when dealing with fluctuating workloads and complex multi-tier server ..."
Abstract - Cited by 46 (3 self) - Add to MetaCart
Data center virtualization allows cost-effective server consol-idation which can increase system throughput and reduce power consumption. Resource management of virtualized servers is an important and challenging task, especially when dealing with fluctuating workloads and complex multi-tier server

A Cost Model for Adaptive Resource Management in Data Stream Systems

by Michael Cammert, Bernhard Seeger, Sonny Vaupel
"... Data stream management systems need to control their resources adaptively since stream characteristics as well as query workload vary over time. In this paper we investigate an approach to adaptive resource management for continuous sliding window queries that adjusts window sizes and time granulari ..."
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Data stream management systems need to control their resources adaptively since stream characteristics as well as query workload vary over time. In this paper we investigate an approach to adaptive resource management for continuous sliding window queries that adjusts window sizes and time

Hyperloglog: The analysis of a near-optimal cardinality estimation algorithm

by Philippe Flajolet, Éric Fusy, Olivier Gandouet, et al. - IN AOFA ’07: PROCEEDINGS OF THE 2007 INTERNATIONAL CONFERENCE ON ANALYSIS OF ALGORITHMS , 2007
"... This extended abstract describes and analyses a near-optimal probabilistic algorithm, HYPERLOGLOG, dedicated to estimating the number of distinct elements (the cardinality) of very large data ensembles. Using an auxiliary memory of m units (typically, “short bytes”), HYPERLOGLOG performs a single pa ..."
Abstract - Cited by 50 (1 self) - Add to MetaCart
. For instance, the new algorithm makes it possible to estimate cardinalities well beyond 10 9 with a typical accuracy of 2 % while using a memory of only 1.5 kilobytes. The algorithm parallelizes optimally and adapts to the sliding window model.

Efficient resource provisioning in compute clouds via vm multiplexing,”

by Xiaoqiao Meng , Canturk Isci , Jeffrey Kephart , Li Zhang , Eric Bouillet , Dimitrios Pendarakis - in The 7th IEEE/ACM International Conference on Autonomic Computing and Communications, , 2010
"... ABSTRACT Resource provisioning in compute clouds often requires an estimate of the capacity needs of Virtual Machines (VMs). The estimated VM size is the basis for allocating resources commensurate with demand. In contrast to the traditional practice of estimating the size of VMs individually, we p ..."
Abstract - Cited by 54 (2 self) - Add to MetaCart
from about 16 thousand VMs in commercial data centers. The results demonstrate more than 45% improvements in terms of the overall resource utilization.
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