P
Prashant Shenoy
Researcher at University of Massachusetts Amherst
Publications - 407
Citations - 19912
Prashant Shenoy is an academic researcher from University of Massachusetts Amherst. The author has contributed to research in topics: Cloud computing & Server. The author has an hindex of 71, co-authored 365 publications receiving 18664 citations. Previous affiliations of Prashant Shenoy include University of Southern California & University of Oklahoma.
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Proceedings Article
Black-box and gray-box strategies for virtual machine migration
TL;DR: This work presents Sandpiper, a system that automates the task of monitoring and detecting hotspots, determining a new mapping of physical to virtual resources and initiating the necessary migrations, and implements a black- box approach that is fully OS- and application-agnostic and a gray-box approach that exploits OS-and- application-level statistics.
Proceedings ArticleDOI
An analytical model for multi-tier internet services and its applications
TL;DR: This paper presents a model based on a network of queues, where the queues represent different tiers of the application, sufficiently general to capture the behavior of tiers with significantly different performance characteristics and application idiosyncrasies such as session-based workloads, concurrency limits, and caching at intermediate tiers.
Journal ArticleDOI
Agile dynamic provisioning of multi-tier Internet applications
TL;DR: A novel dynamic provisioning technique for multi-tier Internet applications that employs a flexible queuing model to determine how much of the resources to allocate to each tier of the application, and a combination of predictive and reactive methods that determine when to provision these resources, both at large and small time scales is proposed.
Proceedings ArticleDOI
Private memoirs of a smart meter
TL;DR: It is shown that even without a priori knowledge of household activities or prior training, it is possible to extract complex usage patterns from smart meter data using off-the-shelf statistical methods.
Journal ArticleDOI
Resource overbooking and application profiling in shared hosting platforms
TL;DR: By overbooking cluster resources in a controlled fashion, this platform can provide performance guarantees to applications even when overbooked, and combine these techniques with commonly used QoS resource allocation mechanisms to provide application isolation and performance guarantees at run-time.