Deadline Scheduling for Real-Time Systems: Edf and Related Algorithms
Deadline Scheduling for Real-Time Systems: Edf and Related Algorithms
Dynamic Pipeline Scheduling for Improving Interactive Query Performance
Proceedings of the 27th International Conference on Very Large Data Bases
Chain: operator scheduling for memory minimization in data stream systems
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Exploiting k-constraints to reduce memory overhead in continuous queries over data streams
ACM Transactions on Database Systems (TODS)
Efficient scheduling of heterogeneous continuous queries
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Window-Oblivious Join: A Data-Driven Memory Management Scheme for Stream Join
SSDBM '07 Proceedings of the 19th International Conference on Scientific and Statistical Database Management
Operator scheduling in a data stream manager
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Multi-query scheduling for time-critical data stream applications
Proceedings of the 25th International Conference on Scientific and Statistical Database Management
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Existing query scheduling strategies over data streams mainly focus on metrics in terms of system performance, such as processing time or memory overhead. However, for commercial stream applications, what actually matters most is the users' satisfaction about the Quality of Service (QoS) they perceive. Unfortunately, a system-oriented optimization strategy does not necessarily lead to a high degree of QoS. Motivated by this, we study QoS-oriented query scheduling in this paper. One important contribution of this work is that we correlate the operator scheduling problem with the classical job scheduling problem. This not only offers a new angle in viewing the issue but also allows techniques for the well studied job scheduling problems to be adapted in this new context. We show how these two problems can be related and propose a novel operator scheduling strategy inspired by job scheduling algorithms. The performance study demonstrates a promising result for our proposed strategy.