Memory overflow protection for embedded systems using run-time checks, reuse and compression

  • Authors:

  • Surupa Biswas;Matthew Simpson;Rajeev Barua

  • Affiliations:

  • Univ. of MD, College Park, MD;Clemson University;Univ. of MD, College Park, MD

  • Venue:
  • Proceedings of the 2004 international conference on Compilers, architecture, and synthesis for embedded systems
  • Year:
  • 2004

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Abstract

Out-of-memory errors are a serious source of unreliability in most embedded systems. Applications run out of main memory because of the frequent difficulty of estimating the memory requirement before deployment, either because it depends on input data, or because certain language features prevent estimation. The typical lack of disks and virtual memory in embedded systems has two serious consequences when an out-of-memory error occurs. First, there is no swap space for the application to grow into, and the system crashes. Second, since protection from virtual memory is usually absent, the fact that a segment has exceeded its bounds is not even detected and hence no pre-crash remedial action is possible.This work improves system reliability in two ways. First it proposes a low-overhead system of run-time checks by which the out-of-memory errors are detected just before they will happen, by using carefully optimized compiler-inserted run-time check code. Such error detection enables the designer to incorporate system-specific remedial action, such as transfer to manual control, shutting down of non-critical tasks, or other actions. Second, this work proposes five related techniques that can grow the stack or heap segment after it is out of memory, into previously un-utilized space such as dead variables and space freed by compressed live variables. These techniques can avoid the out-of-memory error if the extra space recovered is enough to complete execution.Results from our benchmarks show that the overheads from the system of run-time checks for detecting memory overflow are extremely low: the run-time and code-size overheads are 1.1% and 0.09% on average. When the reuse functionality is included, the run-time and code-size overheads increase to only 3.2%and 2.33%, but the method is able to grow the stack or heap beyond its overflow by an amount that ranges from 0.7% to 93.5% of the combined stack and heap size.