Quality of service: delivering QoS on the Internet and in corporate networks
Quality of service: delivering QoS on the Internet and in corporate networks
An optimal algorithm for approximate nearest neighbor searching fixed dimensions
Journal of the ACM (JACM)
QoS and traffic management in IP and ATM networks
QoS and traffic management in IP and ATM networks
Processing complex aggregate queries over data streams
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Surfing Wavelets on Streams: One-Pass Summaries for Approximate Aggregate Queries
Proceedings of the 27th International Conference on Very Large Data Bases
Approximate join processing over data streams
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Chain: operator scheduling for memory minimization in data stream systems
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Processing set expressions over continuous update streams
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Aurora: a data stream management system
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
A learning-based approach to estimate statistics of operators in continuous queries: a case study
DMKD '03 Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
Monitoring streams: a new class of data management applications
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Load shedding in a data stream manager
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
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For many applications, it is important to evaluate trigger conditions on time series streams. In a resource constrained environment, users' needs should ultimately decide how the evaluation system balances the competing factors such as evaluation speed, result precision, and load shedding level. This paper presents a basic framework for evaluation algorithms that takes user-specified quality requirements into consideration. Three optimization algorithms, each under a different set of quality requirements, are developed in the framework: (1) minimize the response time given accuracy requirements and without load shedding; (2) minimize the load shedding given a response time limit and accuracy requirements; and (3) minimize one type of accuracy errors given a response time limit and without load shedding. Experiments show that these optimization algorithms effectively achieve their optimization goals while satisfying the corresponding user-specified quality requirements.