4.5 Article

Multiresolution Spatial and Temporal Coding in a Wireless Sensor Network for Long-Term Monitoring Applications

期刊

IEEE TRANSACTIONS ON COMPUTERS
卷 58, 期 6, 页码 827-838

出版社

IEEE COMPUTER SOC
DOI: 10.1109/TC.2009.20

关键词

Coding; data compression; sensor data aggregation; sensor data management; wireless sensor networks

资金

  1. NSC [95-2221-E-009-058-MY3, 96-2218-E-009-004, 962219-E-007-008, 97-3114-E-009-001, 97-2221-E-009-142-MY3, 97-2218-E-009-026]
  2. MOEA [94-EC-17-A04-S1-044]
  3. ITRI, Taiwan

向作者/读者索取更多资源

In many WSN (wireless sensor network) applications, such as [1], [2], [3], the targets are to provide long-term monitoring of environments. In such applications, energy is a primary concern because sensor nodes have to regularly report data to the sink and need to continuously work for a very long time so that users may periodically request a rough overview of the monitored environment. On the other hand, users may occasionally query more in-depth data of certain areas to analyze abnormal events. These requirements motivate us to propose a multiresolution compression and query (MRCQ) framework to support in-network data compression and data storage in WSNs from both space and time domains. Our MRCQ framework can organize sensor nodes hierarchically and establish multiresolution summaries of sensing data inside the network, through spatial and temporal compressions. In the space domain, only lower resolution summaries are sent to the sink; the other higher resolution summaries are stored in the network and can be obtained via queries. In the time domain, historical data stored in sensor nodes exhibit a finer resolution for more recent data, and a coarser resolution for older data. Our methods consider the hardware limitations of sensor nodes. So, the result is expected to save sensors' energy significantly, and thus, can support long-term monitoring WSN applications. A prototyping system is developed to verify its feasibility. Simulation results also show the efficiency of MRCQ compared to existing work.

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