Deduplication has been commonly used in both enterprise storage systems and cloud storage. To overcome the performance challenge for the selective restore operations of deduplication systems, solid-state-drive-based ...
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Deduplication has been commonly used in both enterprise storage systems and cloud storage. To overcome the performance challenge for the selective restore operations of deduplication systems, solid-state-drive-based （i.e., SSD-based） re^d cache cm, be deployed for speeding up by caching popular restore contents dynamically. Unfortunately, frequent data updates induced by classical cache schemes （e.g., LRU and LFU） significantly shorten SSDs＇ lifetime while slowing down I/O processes in SSDs. To address this problem, we propose a new solution -- LOP-Cache to greatly improve tile write durability of SSDs as well as I/O performance by enlarging the proportion of long-term popular （LOP） data among data written into SSD-based cache. LOP-Cache keeps LOP data in the SSD cache for a long time period to decrease the number of cache replacements. Furthermore, it prevents unpopular or unnecessary data in deduplication containers from being written into the SSD cache. We implemented LOP-Cache in a prototype deduplication system to evaluate its pertbrmance. Our experimental results indicate that LOP-Cache shortens the latency of selective restore by an average of 37.3% at the cost of a small SSD-based cache with only 5.56% capacity of the deduplicated data. Importantly, LOP-Cache improves SSDs＇ lifetime by a factor of 9.77. The evidence shows that LOP-Cache offers a cost-efficient SSD-based read cache solution to boost performance of selective restore for deduplication systems.
As the volume data grows exponentially, more and more big data handling approaches are also applied in the linked data cloud. Thus, semantic triplets which are nucleus of the Resource Description Framework (RDF) must ...
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The main objective of the Offshore Code Comparison Collaboration Continuation, with Correlation (OC5) project, is validation of aero-hydro-servo-elastic simulation tools for offshore wind turbines (OWTs) through compa...
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Big Data Analytics is an emerging field since massive storage and computing capabilities have been made available by advanced *** and Environmental sciences are likely to benefit from Big Data Analytics techniques sup...
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Big Data Analytics is an emerging field since massive storage and computing capabilities have been made available by advanced *** and Environmental sciences are likely to benefit from Big Data Analytics techniques supporting the processing of the large number of Earth Observation datasets currently acquired and generated through observations and ***,Earth Science data and applications present specificities in terms of relevance of the geospatial information,wide heterogeneity of data models and formats,and complexity of ***,Big Earth Data Analytics requires specifically tailored techniques and *** EarthServer Big Earth Data Analytics engine offers a solution for coverage-type datasets,built around a high performance array database technology,and the adoption and enhancement of standards for service interaction(OGC WCS and WCPS).The EarthServer solution,led by the collection of requirements from scientific communities and international initiatives,provides a holistic approach that ranges from query languages and scalability up to mobile access and *** result is demonstrated and validated through the development of lighthouse applications in the Marine,Geology,Atmospheric,Planetary and Cryospheric science domains.
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