Data warehousing and OLAP for decision support
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
The cougar approach to in-network query processing in sensor networks
ACM SIGMOD Record
Design, Implementation, and Performance of the LHAM Log-Structured History Data Access Method
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
TAG: a Tiny AGgregation service for Ad-Hoc sensor networks
OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
TinyDB: an acquisitional query processing system for sensor networks
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
Remembrance of streams past: overload-sensitive management of archived streams
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
SStreaMWare: a service oriented middleware for heterogeneous sensor data management
Proceedings of the 5th international conference on Pervasive services
Octopus: monitoring, visualization, and control of sensor networks
Wireless Communications & Mobile Computing
A balance storage nodes assignment for wireless sensor networks
WASA'13 Proceedings of the 8th international conference on Wireless Algorithms, Systems, and Applications
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Wireless sensor networks are rapidly finding their way through a plethora of new applications like precision farming and forestry, with increasing network scale, system complexity, and data rate. While scalable MAC and routing protocols for sensor networks have been well addressed in recent years, the scalability of the back-end storage architecture has been largely overlooked. As a result, current storage and retrieval architectures usually lead to an excessive I/O cost when it comes to improving the scalability and responsiveness of the system. In this paper, we present a scalable backend storage and retrieval architecture to support very large volumes of real-time measurements from wireless sensor networks. In particular, our contribution provides: (i) a database partitioning and structuring scheme coupled with a double-buffering technique to reduce the end-to-end delay while minimizing the processing power, and (ii) an optimized historical measurement data query format tailored for superior performance in terms of data retrieval responsiveness. Through a realistic emulator for large scale sensor network, we evaluate this storage and retrieval system to illustrates its delay and I/O benefits in both high and low traffic rate scenarios. The evaluation guides our design of an adaptive design, that applies batch insert method for smaller deployments to reduce insertion delay, and double-buffering for larger deployments to reduce I/O cost and avoid saturation, at the cost of higher delay.