&lt;title&gt;Querying and tasking in sensor networks&lt;/title&gt;

Jaikaeo, Chaiporn; Srisathapornphat, C.; Shen, Chien-Chung

doi:10.1117/12.395040

Cited by 43 publications

(30 citation statements)

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“…Although one might be able to construct some distributed applications using the above scheme, by no means the creation and diffusion of distributed proactive applications into the network is supported by its architecture. Finally, extremely relevant is the work that is being conducted in University of Delaware by Jaikaeo et al [17] called SQTL (Sensor Querying and Tasking Language). Having the same goals as our research, but starting from a different point (database-like queries), the researchers end up with the same basic solution as SensorWare, namely a tasking language for sensor networks.…”

Section: Related Workmentioning

confidence: 99%

“…Having the same goals as our research, but starting from a different point (database-like queries), the researchers end up with the same basic solution as SensorWare, namely a tasking language for sensor networks. To lively demonstrate the relevance to our work we are quoting an excerpt from [17] [28]. SINA uses both SQL-like queries as well as SQTL programs.…”

Section: Related Workmentioning

confidence: 99%

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Design and implementation of a framework for efficient and programmable sensor networks

Boulis

Han

Srivastava

2003

Proceedings of the 1st International Conference on Mobile Systems, Applications and Services

226

128

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-Wireless ad hoc sensor networks have emerged as one of the key growth areas for wireless networking and computing technologies. So far these networks/systems have been designed with static and custom architectures for specific tasks, thus providing inflexible operation and interaction capabilities. Our vision is to create sensor networks that are open to multiple transient users with dynamic needs. Working towards this vision, we propose a framework to define and support lightweight and mobile control scripts that allow the computation, communication, and sensing resources at the sensor nodes to be efficiently harnessed in an application-specific fashion. The replication/migration of such scripts in several sensor nodes allows the dynamic deployment of distributed algorithms into the network. Our framework, SensorWare, defines, creates, dynamically deploys, and supports such scripts. Our implementation of SensorWare occupies less than 180Kbytes of code memory and thus easily fits into several sensor node platforms. Extensive delay measurements on our iPAQ-based prototype sensor node platform reveal the small overhead of SensorWare to the algorithms (less than 0.3msec in most high-level operations). In return the programmer of the sensor network receives compactness of code, abstraction services for all of the node's modules, and in-built multi-user support.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Design and implementation of a framework for efficient and programmable sensor networks

Boulis

Han

Srivastava

2003

Proceedings of the 1st International Conference on Mobile Systems, Applications and Services

226

128

View full text Add to dashboard Cite

show abstract

“…The only notable exception is the target-tracking problem, which has drawn attention from several r esearch groups. Otherwise, the applications that have been examined are usually "toy" scenarios used to showcase the abilities of protocols and programming frameworks (e.g., [10]), or very specific applications examined for the sake of some energysaving technique (e.g., [11]). …”

Section: Introductionmentioning

confidence: 99%

Aggregation in sensor networks: an energy–accuracy trade-off

2003

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-Wireless ad hoc sensor networks (WASNs) are in need of the study of useful applications that will help the researchers view them as distributed physically coupled systems, a collective that estimates the physical environment, and not just energylimited ad hoc networks. We develop this perspective using a large and interesting class of WASN applications called aggregation applications. In particular, we consider the challenging periodic aggregation problem where the WASN provides the user with periodic estimates of the environment, as opposed to simpler and previously studied snapshot aggregation problems. In periodic aggregation our approach allows the spatial-temporal correlation among values sensed at the various nodes to be exploited towards energy-efficient estimation of the aggregated value of interest. Our approach also creates a system level energy vs. accuracy knob whereby the more the estimation error that the user can tolerate, the less is the energy consumed. We present a distributed estimation algorithm that can be applied to explore the energy-accuracy subspace for a sub-class of periodic aggregation problems, and present extensive simulation results that validate our approach. The resulting algorithm, apart from being more flexible in the energy-accuracy subspace and more robust, can also bring considerable energy savings for a typical accuracy requirement (five -fold decrease in energy consumption for 5% estimation error) compared to repeated snapshot aggregations.

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“…Most of them rely on some form of SQL-like language in order to recover the data stored in different memories within the sensor node (RAM, EEPROM, and external flash). There exist different data-centric middlewares such as Cougar (Fung et al, 2002), TinyBD (Madden et al, 2005), DSWare (Li et al, 2003) and SINA (Jaikaeo et al, 2000)); some of them are summarized in the following paragraphs.…”

Section: Data-centric Middlewaresmentioning

confidence: 99%