Loading...
Please wait, while we are loading the content...
Similar Documents
Evaluation of Event-Aware Environmental Data Compression Schemes for Wireless Sensor Networks
| Content Provider | Semantic Scholar |
|---|---|
| Author | Moss, Mark B. |
| Abstract | Wireless Sensor Networks offer scientists new ways to measure the environment by utilising remote sensors to record important events or variables in an area of interest. Sensor nodes transmit their readings across the network back to a base station where they can then be processed for further analysis. Transmission is a costly operation for sensor nodes due to its relatively high consumption of the sensors’ limited energy source. This raises the question, “Can we reduce the number of transmissions by a sensor without losing any data quality?” Reducing transmission costs will prolong network existence resulting in data collection over a longer period. One solution to this problem is the use of data compression techniques to reduce the number of transmitted readings and thus conserve a sensor’s power. Piecewise linear representation and Haar wavelets are two data compression methods that can be implemented on a sensor node; their effectiveness is evaluated in this paper. Both algorithms were simulated using data collected from field experiments and results find piecewise linear approximation to be superior. The piecewise linear approximation algorithm evaluated in this dissertation is proven as a solution for controlling transmission costs. However, it operates by compressing data in a non-discriminatory fashion. When monitoring particular environmental phenomena, periods exist where measurement parameters, like the compression threshold, need to be adjusted. This is especially relevant during important events where a sensor should modify its measurement process to record data with maximum accuracy. To achieve this functionality, an adaptive algorithm is developed for soil moisture data sets that extends piecewise representation by incorporating a level of event awareness during measurement. Results show the adaptive measurement technique records critical events at an improved resolution, without significantly reducing the energy savings associated with the standard compression process. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://teaching.csse.uwa.edu.au/year4/Current/Students/Files/2005/MarkMoss/CorrectedDissertation.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
