An efficient mechanism for processing similarity search queries in sensor networks

Yu Chi Chung, I. Fang Su, Chiang Lee

研究成果: Article同行評審

14 引文 斯高帕斯(Scopus)


The similarity search problem has received considerable attention in database research community. In sensor network applications, this problem is even more important due to the imprecision of the sensor hardware, and variation of environmental parameters. Traditional similarity search mechanisms are both improper and inefficient for these highly energy-constrained sensors. A difficulty is that it is hard to predict which sensor has the most similar (or closest) data item such that many or even all sensors need to send their data to the query node for further comparison. In this paper, we propose a similarity search algorithm (SSA), which is a novel framework based on the concept of Hilbert curve over a data-centric storage structure, for efficiently processing similarity search queries in sensor networks. SSA successfully avoids the need of collecting data from all sensors in the network in searching for the most similar data item. The performance study reveals that this mechanism is highly efficient and significantly outperforms previous approaches in processing similarity search queries.

頁(從 - 到)284-307
期刊Information sciences
出版狀態Published - 2011 一月 15

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Theoretical Computer Science
  • Software
  • Computer Science Applications
  • Information Systems and Management
  • Artificial Intelligence

指紋 深入研究「An efficient mechanism for processing similarity search queries in sensor networks」主題。共同形成了獨特的指紋。