A modular network layer for sensorsets
OSDI '06 Proceedings of the 7th symposium on Operating systems design and implementation
The design and implementation of a declarative sensor network system
Proceedings of the 5th international conference on Embedded networked sensor systems
Automating rendezvous and proxy selection in sensornets
IPSN '09 Proceedings of the 2009 International Conference on Information Processing in Sensor Networks
An adaptive rendezvous data dissemination for irregular sensor networks with multiple sinks
Computer Communications
Double rulings for information brokerage in sensor networks
IEEE/ACM Transactions on Networking (TON)
Detecting proximity events in sensor networks
Information Systems
Making data-centric storage adaptive and cost-optimal
Computer Networks: The International Journal of Computer and Telecommunications Networking
STARR-DCS: Spatio-temporal adaptation of random replication for data-centric storage
ACM Transactions on Sensor Networks (TOSN)
CTP: An efficient, robust, and reliable collection tree protocol for wireless sensor networks
ACM Transactions on Sensor Networks (TOSN)
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Most data retrieval mechanisms in wireless sensor networks adopt a data-centric approach, in which data is identified directly by name rather than through the location of the node on which it is stored. Initial data-centric methods, such as directed diffusion and TinyDB/TAG, focused on the conveyance of data. One of the advantages of these algorithms is that they do not require point-to-point routing, which has proved to be difficult and costly to implement in wireless sensor networks, and instead require only the simpler and more robust tree-construction primitives. Some recent data retrieval proposals have extended the data-centric paradigm to storage. Data-centric storage uses in-network placement of data to increase the efficiency of data retrieval in certain circumstances. Unfortunately, all such proposals have been based on point-to-point routing, and therefore have faced a significant deployment barrier. In this paper we hope to make data-centric storage more practical by removing the need for point-to-point routing. To that end, we propose pathDCS, an approach to data-centric storage that requires only standard tree construction algorithms, a primitive already available in many real-world deployments. We describe the design and implementation of pathDCS and evaluate its performance through both high-level and packet-level simulations, as well as through experiments on a sensor testbed.