Disens: scalable distributed sensor network simulation

  • Authors:

  • Ye Wen;Rich Wolski;Gregory Moore

  • Affiliations:

  • University of California, Santa Barbara, CA;University of California, Santa Barbara, CA;University of California, Santa Barbara, CA

  • Venue:
  • Proceedings of the 12th ACM SIGPLAN symposium on Principles and practice of parallel programming
  • Year:
  • 2007

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Abstract

Simulation is widely used for developing, evaluating and analyzing sensor network applications, especially when deploying a large scale sensor network remains expensive and labor intensive. However, due to its computation intensive nature, existent simulation tools have to make trade-offs between fidelity and scalability and thus offer limited capabilities as design and analysis tools. In this paper, we introduce DiSenS (DIstributed SENsor network Simulation) -- a highly scalable distributed simulation system for sensor networks. DiSenS does not only faithfully emulates an extensive set of sensor hardware and supports extensible radio/power models, so that sensor network applications can be simulated transparently with high fidelity, but also employs distributed-memory parallel cluster system to attack the complex simulation problem. Combining an efficient distributed synchronization protocol and a sophisticated node partitioning algorithm (based on existent research), DiSenS achieves greater scalability than even many discrete event simulators. On a small to medium size cluster (16-64 nodes), DiSenS is able to simulate hundreds of motes in realtime speed and scale to thousands in sub-realtime speed. To our knowledge, DiSenS is the first full-system sensor network simulator with such scalability.