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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)
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)
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)
Large amount of monitoring data can be collected from distributed systems as the observables to analyze system behaviors. However, without reasonable models to characterize systems, we can hardly interpret such monitoring data effectively for system management. In this paper, a new concept named flow intensity is introduced to measure the intensity with(More)
Due to their growing complexity, it becomes extremely difficult to detect and isolate faults in complex systems. While large amount of monitoring data can be collected from such systems for fault analysis, one challenge is how to correlate the data effectively across distributed systems and observation time. Much of the internal monitoring data reacts to(More)
This paper develops an online resource provisioning framework for combined power and performance management in a virtualized computing environment serving session-based workloads. We pose this management problem as one of sequential optimization under uncertainty and solve it using limited lookahead control (LLC), a form of model-predictive control. The(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)
Troubleshooting Software-Defined Networks requires a structured approach to detect mistranslations between high-level intent (policy) and low-level forwarding behavior, and a flexible on-demand packet tracing tool is highly desirable on the data plane. In this paper, we introduce a Layer 2 path tracing utility named PathletTracer. PathletTracer offers an(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 onand off-premise infrastructures for hosting Internet-based applications, and the intelligence lies in the explicit segregation of base workload and(More)