Exploring In-Situ sensing irregularity in wireless sensor networks

Joengmin Hwang, Tian He, Yongdae Kim

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


The circular sensing model has been widely used to estimate performance of sensing applications in existing analyses and simulations. While this model provides valuable high-level guidelines, the quantitative results obtained may not reflect the true performance of these applications, due to the sensing irregularity introduced by existence of obstacles in real deployment areas and insufficient hardware calibration. In this paper, we design and implement two Sensing Area Modeling (SAM) techniques useful in the real world. They complement each other in the design space. Physical Sensing Area Modeling (P-SAM) provides accurate physical sensing area for individual nodes using controlled or monitored events, while Virtual Sensing Area Modeling (V-SAM) provides continuous sensing similarity between nodes using natural events in an environment. With these two models, we pioneer an investigation of the impact of sensing irregularity on application performance, such as coverage scheduling. We evaluate SAM extensively in real-world settings, using testbeds consisting of 14 XSM motes. To study the performance at scale, we also provide an extensive 1,400-node simulation. Evaluation results reveal several serious issues concerning circular models and demonstrate significant improvements in several applications when SAM is used instead.

Original languageEnglish (US)
Article number5072208
Pages (from-to)547-561
Number of pages15
JournalIEEE Transactions on Parallel and Distributed Systems
Issue number4
StatePublished - Apr 2010

Bibliographical note

Funding Information:
This work was supported by the University of Minnesota McKnight-Land Grant Professorship award, and US National Science Foundation (NSF) grants CNS-0626614, CNS-0615063, and CNS-0626609.


  • Coverage
  • Event
  • Irregularity
  • Model
  • Scheduling
  • Sensing
  • Similarity


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