Self-Expressive Management of Business-Critical Workloads in Virtualized Datacenters

Journal article (2015)

Authors

V.S. van Beek ASP4ALL Bitbrains
T.M. Hegeman Data-Intensive Systems - EEMCS
S. Hugtenburg Student
A. Iosup Data-Intensive Systems - EEMCS
Research Group
Data-Intensive Systems (EEMCS) (TU Delft)
More Info
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Published Date

2015

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Software Technology

Research Group

Data-Intensive Systems

Abstract

The Mnemos resource management and scheduling architecture uses portfolio scheduling, topology-aware virtual-resource management, and state information to self-adapt to significant workload changes and to analyze risks. Simulations with real-world workload traces reveal the potential for significant cost savings.