Data Salmon: A Greedy Mobile Basestation Protocol for Efficient Data Collection in Wireless Sensor Networks

Our work addresses the spatiotemporally varying nature of data traffic in environmental monitoring and surveillance applications. By employing a network-controlled mobile basestation (MB), we present a simple energy-efficient data collection protocol for wireless sensor net- works (WSNs). In contrast to the existing MB-based solutions where WSN nodes buffer data passively until visited by an MB, our protocol maintains an always-on multihop connectivity to the MB by means of an efficient distributed tracking mechanism. This allows the nodes to for- ward their data in a timely fashion, avoiding latencies due to long-term buffering. Our protocol progressively relocates the MB closer to the re- gions that produce higher data rates and reduces the average weighted multihop traffic, enabling energy savings. Using the convexity of the cost function, we prove that our local and greedy protocol is in fact optimal.

For more details see our technical report.
You can download the simulator source code from here:


  • Doctoral Student Murat Ali Bayir graduated, Congratulations Murat! May 2010.
  • Crowd-Sourced Sensing and Collaboration Project got Google Research Award! Click here for details, March 2010.
  • Asst. Prof. Dr. Demirbas got NSF Project Grant! Click here for details, September 2009.
  • Doctoral Student Xuming Lu graduated, Congratulations Xuming! May 2009.
  • Asst. Prof. Dr. Demirbas got Office of Naval Research Grant! Click here for details, April 2009.
  • Two papers accepted to WOWMOM 2009 from Ubicomp Lab!, Click here for details, December 2008.
  • Asst. Prof. Dr. Demirbas awarded NSF Career Award! Click here for details, January 2008.

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