Dependence-based multi-level tracing and replay for wireless sensor networks debugging

  • Authors:

  • Man Wang;Zhiyuan Li;Feng Li;Xiaobing Feng;Saurabh Bagchi;Yung-Hsiang Lu

  • Affiliations:

  • Purdue University, West Lafayette, IN, USA;Purdue University, West Lafayette, IN, USA;Chinese Academy of Sciences, Beijing, China;Chinese Academy of Sciences, Beijing, China;Purdue University, West Lafayette, IN, USA;Purdue University, West Lafayette, IN, USA

  • Venue:
  • Proceedings of the 2011 SIGPLAN/SIGBED conference on Languages, compilers and tools for embedded systems
  • Year:
  • 2011

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Abstract

Due to resource constraints and unreliable communication, wireless sensor network (WSN) programming and debugging remain to be a challenging task. Runtime errors must be constantly monitored, often by checking for violations of certain invariants. Once an error is detected, diagnosis must be performed to identify the origin of the error. Deterministic replay is an error diagnosis method which has long been proposed for distributed systems. However, one of the significant hurdles for applying deterministic replay on WSN is posed by the small program memory on typical sensor nodes. This paper proposes a dependence-based multi-level method for memory-efficient tracing and replay. In the interest of portability across different hardware platforms, the method is implemented as a source-level tracing and replaying tool. To further reduce the code size after tracing instrumentation, a cost model is used for making the decision on which functions to in-line. A prototype for the tool targets C programs is developed on top of the Open64 compiler and is tested using several TinyOS applications running on TelosB motes. Preliminary experimental results show that the test programs, which do not fit the program memory after straightforward instrumentation, can be successfully accommodated in memory using the new method such that the injected errors can be found.