Adaptive memory-aware chunk sizing techniques for data-intensive queries over web services

Modern applications of Web Services (WSs) that involve the processing of large amounts of data tend to transmit data in chunks. Several performance control techniques have been proposed to dynamically select the appropriate chunk size with a view to minimize the communication cost. However, when the data consumer is slower than the data producer, the consumer applications may suffer from memory shortage if high volumes of data arrive in the incoming buffers. To this end, we propose a specific approach to coupling performance control with congestion control features, in order to consider both performance and memory overflow issues in an integrated manner. The performance results with real data show that we can combine these controllers effectively and efficiently, so that no memory overflow occurs at the expense of negligible performance degradation.