Portland State University. Department of Computer Science
Date of Award
Doctor of Philosophy (Ph.D.) in Computer Science
1 online resource (xiii, 203 p.) : ill. (some col.)
Database management, Querying (Computer science), Event processing (Computer science)
Data Stream Management Systems (DSMSs) provide support for continuous query evaluation over data streams. Data streams provide processing challenges due to their unbounded nature and varying characteristics, such as rate and density fluctuations. DSMSs need to adapt stream processing to these changes within certain constraints, such as available computational resources and minimum latency requirements in producing results. The proposed research develops an inter-operator feedback framework, where opportunities for run-time adaptation of stream processing are expressed in terms of descriptions of substreams and actions applicable to the substreams, called feedback punctuations. Both the discovery of adaptation opportunities and the exploitation of these opportunities are performed in the query operators. DSMSs are also concerned with state management, in particular, state derived from tuple processing. The proposed research also introduces the Contracts Framework, which provides execution guarantees about state purging in continuous query evaluation for systems with and without inter-operator feedback. This research provides both theoretical and design contributions. The research also includes an implementation and evaluation of the feedback techniques in the NiagaraST DSMS, and a reference implementation of the Contracts Framework.
Fernández Moctezuma, Rafael J., "A Data-Descriptive Feedback Framework for Data Stream Management Systems" (2012). Dissertations and Theses. Paper 116.