Exploiting spatial correlation towards an energy efficient clustered aggregation technique (CAG)

Yoon, SunHee; Shahabi, Cyrus

doi:10.1109/icc.2005.1495034

Cited by 47 publications

(3 citation statements)

References 3 publications

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“…But there is lack of evidence showing the Synopsis Diffusion can support complicate queries. The works closer to our work are seen in [9][10][11][12][13]. In [9], the author analysis the spatial-temporal correlation model to develop a theoretical framework which is able to develop efficient communication protocols.…”

Section: Background and Related Workmentioning

confidence: 94%

“…In [9], the author analysis the spatial-temporal correlation model to develop a theoretical framework which is able to develop efficient communication protocols. CAG (Cluster Aggregation Tecnique) [10] and TiNA [11] use similar mechanism to group serval close values into one specified value. DOC 2 [12] uses the characteristic of Slepian-Wolf coding to exploit spatial correlation from the information entropy aspect.…”

Section: Background and Related Workmentioning

confidence: 99%

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3D-DCT Data Aggregation Technique for Regularly Deployed Wireless Sensor Networks

Bai

Jamalipour

2008

2008 IEEE International Conference on Communications

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Development of data aggregation techniques is thought as an effective way to save energy in order to prolong the lifetime of Wireless Sensor Networks (WSNs). Particular characteristics of data gathered from spatial-temporal domain may represent certain level of correlation among data values. Based on this observation, we start with analyzing the optimal sampling rate in temporal correlation model to find out the best sleep time of sensor nodes. Then we propose an aggregation technique which exploits the spatial-temporal correlation using a Discrete Cosine Transform (DCT). It transfers the spatialtemporal data into uncorrelated frequency domain coefficients. The WSN is split into several clusters. Original data are aggregated at an aggregation point which acts as a cluster head. The 3D-Zigzag sorting algorithm makes sure that the aggregation point transmits the frequency coefficients from lower frequencies which contain the main energy of the original data to higher frequencies. Simulation results show only a few coefficients are enough to recover original data under high correlation model within the user tolerable distortion rate.

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Section: Background and Related Workmentioning

confidence: 94%

Section: Background and Related Workmentioning

confidence: 99%

3D-DCT Data Aggregation Technique for Regularly Deployed Wireless Sensor Networks

Bai

Jamalipour

2008

2008 IEEE International Conference on Communications

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“…Recently, many researchers have tried to efficiently process a query using In-network query processing mechanism. This mechanism is a general way to minimize communication cost by filtering out un-necessary data as in approximated aggregation with quality guarantee [19] and increasing path sharing in Tiny AGgregation(TAG) [20] and Clustered AGgregation(CAG) [21] using tree-based routing and Directed Diffusion [17] using data-centric routing. In our framework, we especially propose In-network spatial query processing mechanism for the spatial issues on sensor networks.…”

Section: Requirements For Telematics Application Frameworkmentioning

confidence: 99%

A Design of Telematics Application Framework on Ubiquitous Sensor Networks

Lee

Kim

Jang

et al. 2005

Web and Wireless Geographical Information Systems

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In this paper, we introduce new types of Telematics services for a convergence of Telematics and USN technology and explain several requirements needed for those services. Then, we propose a Telematics application framework that can satisfy those requirements of a real-time service, a reliable data acquisition, and an efficient query processing. The framework is composed of Telematics sensor nodes, Telematics service station, and Telematics vehicle that can provide users with reliable and real-time traffic safety services. Also, we present important issues and solutions that can be applied to an implementation of the framework; In-network spatial query processing, vehicle location determination, and real-time and reliable routing protocol. It is expected that this framework can be helpful for the future Telematics services as a standard model when ubiquitous computing society is pervasively activated.

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