Efficient wireless reprogramming through reduced bandwidth usage and opportunistic sleeping

  • Authors:
  • Rajesh Krishna Panta;Saurabh Bagchi;Issa M. Khalil

  • Affiliations:
  • Dependable Computing Systems Lab, School of Electrical and Computer Engineering, Purdue University, 465 Northwestern Avenue, West Lafayette, IN 47907, United States;Dependable Computing Systems Lab, School of Electrical and Computer Engineering, Purdue University, 465 Northwestern Avenue, West Lafayette, IN 47907, United States;College of Information Technology, United Arab Emirates University, United Arab Emirates

  • Venue:
  • Ad Hoc Networks
  • Year:
  • 2009

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Abstract

Wireless reprogramming of a sensor network is useful for uploading new code or for changing the functionality of existing code. Reprogramming may be done multiple times during a node's lifetime and therefore a node has to remain receptive to future code updates. Existing reprogramming protocols, including Deluge, achieve this by bundling the reprogramming protocol and the application as one code image which is transferred through the network. The reprogramming protocol being complex, the overall size of the program image that needs to be transferred over the wireless medium increases, thereby increasing the time and energy required for reprogramming a network. We present a protocol called Stream that significantly reduces this bloat by using the facility of having multiple code images on the node. It pre-installs the reprogramming protocol as one image and equips the application program with the ability to listen to new code updates and switch to this image. For a sample application, the increase in size of the application image is 1 page (48 packets of 36bytes each) for Stream and 11 pages for Deluge. Additionally, we design an opportunistic sleeping scheme whereby nodes can sleep during the period when reprogramming has been initiated but has not yet reached the neighborhood of the node. The savings become significant for large networks and for frequent reprogramming. We implement Stream on Mica2 motes and conduct testbed and simulation experiments to compare delay and energy consumption for different network sizes with respect to the state-of-the-art Deluge protocol.