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https://www.um.edu.mt/library/oar/handle/123456789/16625
Title: | An FPGA implementation of an adaptive data reduction technique for wireless sensor networks |
Authors: | Borg, Nicholas Paul Debono, Carl James |
Keywords: | Wireless sensor networks Field programmable gate arrays Energy consumption Adaptive filters |
Issue Date: | 2008-11 |
Publisher: | University of Malta |
Citation: | Borg, N. P., & Debono, C. J. (2008). An FPGA implementation of an adaptive data reduction technique for wireless sensor networks. Workshop in Information and Communication Technology, Malta. 1-7. |
Abstract: | Wireless sensor networking (WSN) is an emerging technology that has a wide range of potential applications including environment monitoring, surveillance, medical systems, and robotic exploration. These networks consist of large numbers of distributed nodes that organize themselves into a multihop wireless network. Each node is equipped with one or more sensors, embedded processors, and low- power radios, and is normally battery operated. Reporting constant measurement updates incurs high communication costs for each individual node, resulting in a significant communication overhead and energy consumption. A solution to reduce power requirements is to select, among all data produced by the sensor network, a subset of sensor readings that is relayed to the user such that the original observation data can be reconstructed within some user-defined accuracy. This paper describes the implementation of an adaptive data reduction algorithm for WSN, on a Xilinx Spartan-3E FPGA. A feasibility study is carried out to determine the benefits of this solution. |
URI: | https://www.um.edu.mt/library/oar//handle/123456789/16625 |
Appears in Collections: | Scholarly Works - FacICTCCE |
Files in This Item:
File | Description | Size | Format | |
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OA Conference Paper - The Implementation of an Adaptive Data Reduction Technique for Wireless Sensor Networks.2-8.pdf | An FPGA implementation of an adaptive data reduction technique for wireless sensor networks | 596.89 kB | Adobe PDF | View/Open |
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