Adaptive load sharing for clustered digital library servers (1998) [22 citations — 6 self]
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@INPROCEEDINGS{Zhu98adaptiveload,author = {Huican Zhu and Tao Yang and Qi Zheng and David Watson and Oscar H. Ibarra and Terence Smith},
title = {Adaptive load sharing for clustered digital library servers},
booktitle = {Procecedings of the Seventh High Performance Distributed Computing},
year = {1998},
pages = {235--242}
}
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Abstract:
This paper investigates load balancing strategies for clustered Alexandria digital library (ADL) servers. The ADL system, which provides on-line information searching and browsing of spatially-referenced materials through the World Wide Web, involves intensive database I/O and heterogeneous CPU activities. Clustering servers can improve the scalability of the ADL system in response to a large number of simultaneous access requests. One difficulty addressed is that clustered workstation nodes may be non-uniform in terms of CPU and I/O speeds. An optimization scheme is proposed in this paper to dynamically monitor the resource availability, use a low-cost communication strategy for updating load information among nodes, and schedule requests based on both I/O and computation load indices. Since the accurate cost estimation for processing database-searching requests is difficult, a sampling and prediction scheme is used to identify the relative efficiency of nodes for satisfying I/O and CPU demands of these requests. A set of experiments using the ADL traces have been conducted to verify the effectiveness of the proposed strategies. 1
