Application Performance Management in Virtualized Server Environments

By G. Khanna, Kirk A. Beaty, G. Kar, Andrzej Kochut. 2006 IEEE/IFIP Network Operations and Management Symposium NOMS 2006, 2006

358 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/468c9ed488f1a0271de916a52ba1b40a5941d04f

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Citations in the corpus

Shares and utilities based power consolidation in virtualized server environments (2009, methodology): “In the researc h community as well, there are many proposed techniques [2], [3], [4] that analyze utilizations of physical servers and o utput a consolidation plan describing which combinations of phys ical servers can be virtualized into Virtual Machines (VMs) andplaced on each virtualized server.”
A multi-objective ant colony system algorithm for virtual machine placement in cloud computing (2013, methodology): “A simple process for VM placement is as follows [25].”
Energy-Aware Ant Colony Based Workload Placement in Clouds (2011, neutral): “Therefore, a probabilistic decision rule has to be deﬁned which will be used by the al-gorithm to guide the ants choice towards the optimal solution.”
Power and performance management of virtualized computing environments via lookahead control (2008, methodology): “The placement algorithm in [12] also does not save power by switching off unneeded hosts.”
Entropy: a consolidation manager for clusters (2009, methodology): “Previous approaches to achieving a viable, configuration have used heuristics in which a locally optimal placement is chosen for each VM according to some strategy [3, 7, 11, 17].”
Efficient Autoscaling in the Cloud Using Predictive Models for Workload Forecasting (2011, methodology): “Although the utilization model given in [10] maps resource utilization to application utility, ﬁnding such a mapping is difﬁcult [11].”