Self-optimizing block transfer in web service grids
Dikaiakos, Marios D.
SourceInternational Conference on Information and Knowledge Management, Proceedings
9th Annual ACM International Workshop on Web Information and Data Management, WIDM '07, Co-located with the 16th ACM Conference on Information and Knowledge Management, CIKM '07
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Nowadays, Web Services (WSs) play an increasingly important role in Web data management solutions, since they offer a practical solution for accessing and manipulating data sources spanning administrative domains. Nevertheless, they are notoriously slow and transferring large data volumes across WSs becomes the main bottleneck in such WS-based applications. This paper deals with the problem of minimizing at runtime, in a self-managing way, the datatransfer cost of a WS encapsulating a data source. To reducethe transfer cost, the data volume is typically divided intoblocks. In this case, response time exhibits a quadratic-like, non-linear behavior with regards to the block sizeas such, minimizing the transfer cost entails finding the optimum block size. This situation is encountered in several systems, such as WS Management Systems (WSMSs) for DBMS-like data management over wide area service-based networks, and WSs for accessing and integrating traditional DBMSs. The main challenges in this problem include (i) the unavailability of an analytical model(ii) the presence of noise, which incurs local minima(iii) the volatility of the environment, which results into a moving optimum operating pointand (iv) the requirements for fast convergence to the optimal size of the request from the side of the client rather than of the server, and for low overshooting. This paper presents two novel solutions for detecting the optimum block size during data transmission, thus yielding lower response times. The solutions are inspired by the broader areas of runtime optimization and switching extremum control. They incorporate heuristics to avoid local optimal points, and address all the afore-mentioned challenges. The effectiveness andeffciency of the solutions is verified through empirical evaluation in real cases. Copyright 2007 ACM.
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