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

8 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 1月 15

All Science Journal Classification (ASJC) codes

  • 理論電腦科學
  • 軟體
  • 控制與系統工程
  • 電腦科學應用
  • 資訊系統與管理
  • 人工智慧


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