(redirected from Cache Hit Ratio)
Category filter:
CHRCafé Hôtel Restaurant (French: Cafe Hotel Restaurant)
CHRChars (FAO fish species code)
CHRCommission on Human Rights (United Nations)
CHRCentre Hospitalier Régional (French: Regional Hospital Center; France and Belgium)
CHRContemporary Hit Radio
CHRCalgary Health Region
CHRCenter for Hospitality Research (Cornell University; Ithaca, NY)
CHRCentre for Human Rights (South Africa)
CHRCommunity Health Record (various locations)
CHRCharacter File
CHRConstraint Handling Rules (programming languages)
CHRCourt of Human Rights
CHRCommittee on Human Research
CHRCommunity Health Representative(s)
CHRChristian Hit Radio
CHRCenter for Human Reproduction
CHRChinook Health Region
CHRChild Health Research
CHRCache Hit Ratio
CHRCall History Record
CHRCommunity Housing Resource, Inc. (Provincetown, MA)
CHRCenter for Hydrogen Research (Washington Savannah River Company LLC)
CHRCommunication History Report
CHRCapitalsource Healthcare Reit
CHRChateauroux France (airport code)
CHRComplete Healthcare Resources (Dresher, PA)
CHRChromate Resistance
CHRCerebrohepatorenal Syndrome
CHRCommission Internationale de l'Hydrologie du Bassin du Rhin (International Commission for the Hydrology of the Rhine Basin)
CHRComité d'Histoire Régionale (French: Regional History Committee)
CHRChestnut Ridge Railway Company
CHRCooper-Harper Rating
CHRCenter for Human Radiobiology
CHRNational Center for Human Reproduction
CHRCursive Handwritten Recognition (Recogniform Technologies SpA)
CHRConfinement Heat Removal
CHRCumulative Hazard Rate
CHRCorrelated High-Rank
CHRConsumer Healthcare Retail
Copyright 1988-2018, All rights reserved.
References in periodicals archive ?
Considering that the cache value is measured by multiple factors, we propose a caching value assessment algorithm based on analytic hierarchy process to optimize the caching strategy and increase users' cache hit ratio. Our simulation results show that our approach can improve the cache hit ratio while ensuring ICPs' satisfaction.
(2) We also optimize the caching strategy which takes both the user's access result and cache hit ratio into account.
Existing methods aimed at enhancing the cache hit ratio [25-27] effectively reduce the likelihood of exposing queries to the LBS server while conserving the communication cost and computation load of the anonymizer.
Compared with the result of [25] regarding the number of queries submitted by a single user to generate an obfuscation area, our cache hit ratio was 0, indicating that, without using the cache, four users or more are required to simultaneously transmit a query to meet the privacy requirements with a reduced number of pseudoqueries sent by the anonymizer to the LBS server.
These algorithms mostly combine LFU and LRU to get better results in the cache hit ratio.
As for mentioned hybrid caching replacement policies, the combination of LRU and LFU increases the cache hit ratio. For the combination of these caching policies, we will compute the priority of LRU and LFU-SS for each file in the cache.
The results we obtained for the cache hit ratio under different cache sizes are displayed in Figures 2, 3 and 4.
However, this ignores the fact that the cooperative cache may reduce the size of the local caches, and therefore the local cache hit ratios. Determining the exact effect of cooperative caching on the local cache hit rate is difficult; instead, we made the assumption that each forward to the cooperative cache of a client replaced a local cache block, decreasing the size of the local cache.
For example, when the cache size is 250 GB, the proposed cache achieves hit ratio of 0.66 percent while random and MPV policies achieves cache hit ratios of 0.5 and 3.5 respectively.
Cache sizes and class cache hit ratio percents 8k: 18% 16k: 37% 32k: 50% 64k: 54% Note: Table made from line graph.
As shown in Figure 5b, the cache hit ratio reduces due to client disconnections.
3 plots the cache hit ratio as a function of the Zipf parameter for different cache placement policies: HCCP, FIX (P), and ALWAYS.