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Nam, Beomseok
Data Intensive Computing Lab
Research Interests
  • Distributed and parallel computing, high performance computing, database systems, OS and storage systems

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EM-KDE: A locality-aware job scheduling policy with distributed semantic caches

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dc.contributor.author Eom, Youngmoon ko
dc.contributor.author Hwang, Deukyeon ko
dc.contributor.author Lee, Junyong ko
dc.contributor.author Moon, Jonghwan ko
dc.contributor.author Shin, Minho ko
dc.contributor.author Nam, Beomseok ko
dc.date.available 2015-09-01T06:19:40Z -
dc.date.created 2015-09-01 ko
dc.date.issued 2015-09 ko
dc.identifier.citation JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, v.83, pp.119 - 132 ko
dc.identifier.issn 0743-7315 ko
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/16428 -
dc.description.abstract In modern query processing systems, the caching facilities are distributed and scale with the number of servers. To maximize the overall system throughput, the distributed system should balance the query loads among servers and also leverage cached results. In particular, leveraging distributed cached data is becoming more important as many systems are being built by connecting many small heterogeneous machines rather than relying on a few high-performance workstations. Although many query scheduling policies exist such as round-robin and load-monitoring, they are not sophisticated enough to both balance the load and leverage cached results. In this paper, we propose distributed query scheduling policies that take into account the dynamic contents of distributed caching infrastructure and employ statistical prediction methods into query scheduling policy. We employ the kernel density estimation derived from recent queries and the well-known exponential moving average (EMA) in order to predict the query distribution in a multi-dimensional problem space that dynamically changes. Based on the estimated query distribution, the front-end scheduler assigns incoming queries so that query workloads are balanced and cached results are reused. Our experiments show that the proposed query scheduling policy outperforms existing policies in terms of both load balancing and cache hit ratio. (C) 2015 Elsevier Inc. All rights reserved ko
dc.description.statementofresponsibility close -
dc.language 영어 ko
dc.publisher ACADEMIC PRESS INC ELSEVIER SCIENCE ko
dc.title EM-KDE: A locality-aware job scheduling policy with distributed semantic caches ko
dc.type ARTICLE ko
dc.identifier.scopusid 2-s2.0-84934963746 ko
dc.identifier.wosid 000358755700009 ko
dc.type.rims ART ko
dc.description.wostc 0 *
dc.description.scopustc 0 *
dc.date.tcdate 2015-12-28 *
dc.date.scptcdate 2015-11-04 *
dc.identifier.doi 10.1016/j.jpdc.2015.06.002 ko
dc.identifier.url http://www.sciencedirect.com/science/article/pii/S0743731515001008# ko
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