Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.datak.2004.03.002
DC FieldValue
dc.titleA hash-based collaborative transcoding proxy system
dc.contributor.authorWu, X.
dc.contributor.authorTan, K.-L.
dc.date.accessioned2013-07-04T07:49:32Z
dc.date.available2013-07-04T07:49:32Z
dc.date.issued2004
dc.identifier.citationWu, X., Tan, K.-L. (2004). A hash-based collaborative transcoding proxy system. Data and Knowledge Engineering 51 (2) : 161-188. ScholarBank@NUS Repository. https://doi.org/10.1016/j.datak.2004.03.002
dc.identifier.issn0169023X
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/39786
dc.description.abstractWith the ever increasing wireless client population, the Internet client devices have become highly heterogeneous. Transcoding is used to adapt web objects to suit diverse devices. In this paper, a hash-based collaborative transcoding proxy system is proposed, which aims to improve the system performance in two aspects, caching efficiency and workload balancing. This system employs a hashed-based object caching strategy, which optimizes the cache storage utilization by removing redundant objects scattering in different locations of the overall system cache. In addition, a cache replacement algorithm deployed at the transcoding proxy is examined. A simple hash-based workload distribution strategy is also proposed to share the expensive transcoding load among the various proxies. This strategy performs well with balanced hash function. With unbalanced hash function, satisfactory load sharing is achieved by an optimized strategy, which allows the overloaded proxy to alleviate its load by outsourcing some excessive transcoding tasks to its less overloaded neighbors. An event-driven simulation is conducted to evaluate the system performance, and our results show that the proposed system outperforms existing methods in terms of throughput and response time. © 2004 Elsevier B.V. All rights reserved.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/j.datak.2004.03.002
dc.sourceScopus
dc.subjectHash function
dc.subjectSystem performance
dc.subjectTranscoding
dc.typeArticle
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1016/j.datak.2004.03.002
dc.description.sourcetitleData and Knowledge Engineering
dc.description.volume51
dc.description.issue2
dc.description.page161-188
dc.description.codenDKENE
dc.identifier.isiut000223970000002
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