Data stashing: energy-efficient information delivery to mobile sinks through trajectory prediction

  • Authors:

  • HyungJune Lee;Martin Wicke;Branislav Kusy;Omprakash Gnawali;Leonidas Guibas

  • Affiliations:

  • Stanford University, Stanford, CA;University of Berkeley, Berkeley, CA;CSIRO ICT Centre, Brisbane, Australia;Stanford University, Stanford, CA;Stanford University, Stanford, CA

  • Venue:
  • Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks
  • Year:
  • 2010

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Abstract

In this paper, we present a routing scheme that exploits knowledge about the behavior of mobile sinks within a network of data sources to minimize energy consumption and network congestion. For delay-tolerant network applications, we propose to route data not to the sink directly, but to send it instead to a relay node along an announced or predicted path of the mobile node that is close to the data source. The relay node will stash the information until the mobile node passes by and picks up the data. We use linear programming to find optimal relay nodes that minimize the number of necessary transmissions while guaranteeing robustness against link and node failures, as well as trajectory uncertainty. We show that this technique can drastically reduce the number of transmissions necessary to deliver data to mobile sinks. We derive mobility and association models from real-world data traces and evaluate our data stashing technique in simulations. We examine the influence of uncertainty in the trajectory prediction on the performance and robustness of the routing scheme.