Self-optimizing block transfer in web service grids

Abstract

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 data transfer cost of a WS encapsulating a data source. To reduce the transfer cost, the data volume is typically divided into blocks. In this case, response time exhibits a quadratic-like, non-linear behavior with regards to the block size; as 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 point; and (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 and efficiency of the solutions is verified through empirical evaluation in real cases.