Continuous multi-way joins over distributed hash tables
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
End-to-end support for joins in large-scale publish/subscribe systems
Proceedings of the VLDB Endowment
PEJA: progressive energy-efficient join processing for sensor networks
Journal of Computer Science and Technology
Performance improvement of join queries through algebraic signatures
International Journal of Intelligent Information and Database Systems
In-Network join processing for sensor networks
APWeb'06 Proceedings of the 8th Asia-Pacific Web conference on Frontiers of WWW Research and Development
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We pose the question: how do we efficiently evaluate a join operator, distributed over a heterogeneous network? Our objective here is to optimize the delay of output tuples. We discuss key challenges involved in the distribution, namely how to partition the join operator, how to place the resulting partitions on the network, and how to route inputs values from sources to our operators. Our model revolves on one simple concept - exploiting locality. We consider data locality in the distributions of input data values, and network locality in the distribution of network distances between sites. We sketch strategies to partition the input data space, and instantiate a structured topology, consisting of operator replicas to whom to route tuples for processing. Finally, we briefly discuss implementation issues that require addressing to enable the networked join proposed here.