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An enormous number of apps have been developed for Android in recent years, making it one of the most popular mobile operating systems. However, the quality of the booming apps can be a concern [4]. Poorly engineered apps may contain security vulnerabilities that can severally undermine users' security and privacy. In this paper, we study a general category(More)
There is growing incentive to reduce the power consumed by large-scale data centers that host online services such as banking, retail commerce, and gaming. Virtualization is a promising approach to consolidating multiple online services onto a smaller number of computing resources. A virtualized server environment allows computing resources to be shared(More)
In this article, we formalize the concept of tracking in a sensor network and develop a quantitative theory of <i>trackability</i> of <i>weak models</i> that investigates the rate of growth of the number of consistent tracks given a temporal sequence of observations made by the sensor network. The phenomenon being tracked is modelled by a nondeterministic(More)
In this paper we measured and analyzed the workload on Yahoo! Video, the 2nd largest U.S. video sharing site, to understand its nature and the impact on online video data center design. We discovered interesting statistical properties on both static and temporal dimensions of the workload including file duration and popularity distributions, arrival rate(More)
Flow-based programmable networks must continuously monitor performance metrics, such as link utilization, in order to quickly adapt forwarding rules in response to changes in workload. However, existing monitoring solutions either require special instrumentation of the network or impose significant measurement overhead. In this paper, we propose a(More)
In this paper, we undertake the problem of server consolidation in virtualized data centers from the perspective of approximation algorithms. We formulate server consolidation as a stochastic bin packing problem, where the server capacity and an allowed server overflow probability p are given, and the objective is to assign VMs to as few physical servers as(More)
—We present an intelligent workload factoring service for enterprise customers to make the best use of public cloud services along with their privately-owned (legacy) data centers. It enables federation between on-and off-premise infrastructures for hosting Internet-based applications, and the intelligence lies in the explicit segregation of base workload(More)
With the prevalence of Internet services and the increase of their complexity, there is a growing need to improve their operational reliability and availability. While a large amount of monitoring data can be collected from systems for fault analysis, it is hard to correlate this data effectively across distributed systems and observation time. In this(More)
We introduce FlowComb, a network management framework that helps Big Data processing applications, such as Hadoop, achieve high utilization and low data processing times. FlowComb predicts application network transfers, sometimes before they start, by using software agents installed on application servers and while remaining completely transparent to the(More)