Please use this identifier to cite or link to this item:
https://doi.org/10.1109/TKDE.2007.190694
DC Field | Value | |
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dc.title | On the design of distributed object placement and load balancing strategies in large-scale networked multimedia storage systems | |
dc.contributor.author | Zeng, Z. | |
dc.contributor.author | Veeravalli, B. | |
dc.date.accessioned | 2014-06-17T02:59:49Z | |
dc.date.available | 2014-06-17T02:59:49Z | |
dc.date.issued | 2008-03 | |
dc.identifier.citation | Zeng, Z., Veeravalli, B. (2008-03). On the design of distributed object placement and load balancing strategies in large-scale networked multimedia storage systems. IEEE Transactions on Knowledge and Data Engineering 20 (3) : 369-382. ScholarBank@NUS Repository. https://doi.org/10.1109/TKDE.2007.190694 | |
dc.identifier.issn | 10414347 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/56889 | |
dc.description.abstract | In a large-scale multimedia storage system (LMSS) where client requests for different multimedia objects may have different demands, the placement and replication of the objects is an important factor, as it may result in an imbalance in server loading across the system. Since replication management and load balancing are all the more crucial issues in multimedia systems, in the literature, these problems are handled by centralized servers. Each object storage server (OSS) responds to the requests that come from the centralized servers independently and has no communication with other OSSs in the system. In this paper, we design a novel distributed load balancing strategy for LMSS, in which OSSs can cooperate to achieve higher performance. Such OSS modeled as an M/G/m system can replicate the objects to and balance the requests among other servers to achieve a near-optimal average waiting time (AWT) of the requests in the system. We validate the performance of the system via rigorous simulations with respect to several Influencing factors and prove that our proposed strategy Is scalable, flexible, and efficient for real-life applications. © 2008 IEEE. | |
dc.description.uri | http://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/TKDE.2007.190694 | |
dc.source | Scopus | |
dc.subject | Average waiting time | |
dc.subject | Distributed system | |
dc.subject | Multimedia storage system | |
dc.subject | Queuing theory | |
dc.subject | Request balancing | |
dc.type | Article | |
dc.contributor.department | ELECTRICAL & COMPUTER ENGINEERING | |
dc.description.doi | 10.1109/TKDE.2007.190694 | |
dc.description.sourcetitle | IEEE Transactions on Knowledge and Data Engineering | |
dc.description.volume | 20 | |
dc.description.issue | 3 | |
dc.description.page | 369-382 | |
dc.description.coden | ITKEE | |
dc.identifier.isiut | 000252408900006 | |
Appears in Collections: | Staff Publications |
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