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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao https://doi.org/10.1...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
https://doi.org/10.1109/ic2e.2...
Article . 2016 . Peer-reviewed
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Multi-cache: Dynamic, Efficient Partitioning for Multi-tier Caches in Consolidated VM Environments

Authors: Sundaresan Rajasekaran; Shaohua Duan; Wei Zhang 0052; Timothy Wood 0001;

Multi-cache: Dynamic, Efficient Partitioning for Multi-tier Caches in Consolidated VM Environments

Abstract

Every physical machine in today's typical datacenter is backed by storage devices with hundreds of Gigabytes to Terabytes in size. Data center vendors usually use hard disk drives for their back-end storage as it is cheap and reliable. However, the increase in the I/O accesses to the back-end storage from one or many of the VMs hosted on a physical machine can reduce its overall accesses time significantly due to contention. This may not be suitable for interactive applications requiring low latency that might be co-located with other I/O intensive applications. In this paper we present Multi-Cache, a multi-layer cache management system that uses a combination of cache devices of varied speed and cost such as solid state drives, non-volatile memories, etc to mitigate this problem. Multi-Cache partitions each device dynamically at runtime according to the workload of each VM and its priority. We use a heuristic optimization technique that ensures maximum utilization of the caches resulting in a high hit rate. We use a weighted partitioning policy that improves latency by up to 72% for individual workloads, and a overall hit rate increase of up to 31% for host running several workloads together in comparison to standard LRU caching algorithms.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Average
Top 10%
Top 10%
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