Simple, fast, and practical non-blocking and blocking concurrent queue algorithms
PODC '96 Proceedings of the fifteenth annual ACM symposium on Principles of distributed computing
Models and issues in data stream systems
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Continuously adaptive continuous queries over streams
Proceedings of the 2002 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
Aurora: a new model and architecture for data stream management
The VLDB Journal — The International Journal on Very Large Data Bases
Operator scheduling in data stream systems
The VLDB Journal — The International Journal on Very Large Data Bases
Nile-PDT: a phenomenon detection and tracking framework for data stream management systems
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Punctuated data streams
Optimization of operator partitions in stream data warehouse
Proceedings of the ACM 14th international workshop on Data Warehousing and OLAP
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Quality of Service (QoS) in stream databases is strongly connected with the chosen scheduler algorithm and the architecture of Data Stream Management System (DSMS). In order to achieve better efficiency, those systems work in concurrent and distributed environments. Main difficulties in such systems are caused by a high number of messages exchanged between stream database modules. In consequence, it is hard to create a scalable stream database because the communication cost substantially reduces the benefits of the computation in concurrent environment. Therefore, in the paper, we analyze and evaluate architectures of DSMS. Especially, we focus on cooperation between stream buffers, physical operators and schedulers so as to reduce the role of synchronization in DSMS overhead. Finally, we have created a stream database architecture which substantially improves query result latencies and, besides, this architecture is easy to develop.