Adaptive Coherency Maintenance Techniques for Time-Varying Data

Often, data used in on-line decision making (for example, in determining how to react to changes in process behavior, traffic flow control, etc.) is dynamic in nature and hence the timeliness of the data delivered to the decision making process becomes very important. The delivered data must conform to certain time or value based application specific inconsistency bounds. A system designed to disseminate dynamic data can exploit user-specified coherency requirements by fetching and disseminating only those changes that are of interest to users and ignoring intermediate changes. But, the design of mechanisms for such data delivery is challenging given that dynamic data changes rapidly and unpredictably, the latter making it very hard to use simple prediction techniques. In this paper, we address these challenges. Specifically, we develop mechanisms to obtain timely and consistency-preserving updates for dynamic data by pulling data from the source at strategically chosen points in...

• Type: Conference
• Year: 2003
• Where: RTSS
• Authors: Ratul kr. Majumdar, Kannan M. Moudgalya, Krithi Ramamritham
• Keywords: Applied Computing, Decision Making, Dynamic Data, Dynamic Data Changes, RTSS 2003