Efficient and extensible algorithms for multi query optimization
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Eddies: continuously adaptive query processing
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
Continuously adaptive continuous queries over streams
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
The cougar approach to in-network query processing in sensor networks
ACM SIGMOD Record
Query Scheduling in Multi Query Optimization
IDEAS '01 Proceedings of the International Database Engineering & Applications Symposium
The design of an acquisitional query processor for sensor networks
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Fjording the Stream: An Architecture for Queries Over Streaming Sensor Data
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Resilient and Coherence Preserving Dissemination of Dynamic Data Using Cooperating Peers
IEEE Transactions on Knowledge and Data Engineering
StreamGlobe: adaptive query processing and optimization in streaming P2P environments
DMSN '04 Proceeedings of the 1st international workshop on Data management for sensor networks: in conjunction with VLDB 2004
StreamGlobe: processing and sharing data streams in grid-based P2P infrastructures
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Network-Aware Operator Placement for Stream-Processing Systems
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Streaming queries over streaming data
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Monitoring streams: a new class of data management applications
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
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Stream grids are wide-area grid computing environments that are fed by a set of stream data sources, and Queries arrive at the grid from users and applications external to the system. The kind of queries considered in this work is long-running continuous LRC queries, which are neither short-lived nor infinitely long lived. The queries are "open" from the grid perspective as the grid cannot control or predict the arrival of a query with time, location, required data and query revocations. Query optimization in such an environment has two major challenges, i.e., optimizing in a multi-query environment and continuous optimization, due to new query arrivals and revocations. As generating a globally optimal query plan is an intractable problem, this work explores the idea of emergent optimization where globally optimal query plans emerge as a result of local autonomous decisions taken by the grid nodes. Drawing concepts from evolutionary game theory, grid nodes are modeled as autonomous agents that seek to maximize a self-interest function using one of a set of different strategies. Grid nodes change strategies in response to variations in query arrival and revocation patterns, which is also autonomously decided by each grid node.