On network connectivity of wireless sensor networks for sandstorm monitoring

  • Authors:
  • Pu Wang;Zhi Sun;Mehmet C. Vuran;Mznah A. Al-Rodhaan;Abdullah M. Al-Dhelaan;Ian F. Akyildiz

  • Affiliations:
  • Broadband Wireless Networking Laboratory, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, United States;Broadband Wireless Networking Laboratory, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, United States;Cyber-Physical Networking Laboratory, Department of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588, United States;College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia;College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia;Broadband Wireless Networking Laboratory, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, United States

  • Venue:
  • Computer Networks: The International Journal of Computer and Telecommunications Networking
  • Year:
  • 2011

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Abstract

As serious natural disasters, sandstorms have caused massive damages to the natural environment, national economy, and human health in the Middle East, Northern Africa, and Northern China. To avoid such damages, wireless sensor networks (WSNs) can be deployed in the regions where sandstorms generally originate so that sensor nodes can collaboratively monitor the origin and development of sandstorms. Despite the potential advantages, the deployment of WSNs in the vicinity of sandstorms faces many unique challenges, such as the temporally buried sensors and increased path loss during sandstorms. Consequently, the WSNs may experience frequent disconnections during the sandstorms. In this paper, the connectivity issue of WSNs for sandstorm monitoring is studied. First, four types of channels a sensor can utilize during sandstorms are analyzed, which include air-to-air channel, air-to-sand channel, sand-to-air channel, and sand-to-sand channel. Based on these analytical results, the percolation-based connectivity analysis is performed. It is shown that if the sensors are buried in shallow depth, allowing sensor to use multiple types of channels improves network connectivity. Accordingly, much smaller sensor density is required compared to the case, where only terrestrial air channels are used. Through this connectivity analysis, a WSN architecture can be established for efficient and effective sandstorm monitoring.