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Practical issues in the use of ABFT and a new failure model

机译:使用ABFT的实际问题和新的故障模型

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We study the behavior of algorithm based fault tolerance (ABFT) techniques under faults injected according to a quite general fault model. Besides the problem of roundoff error in floating point arithmetic we identify two further weakpoints, namely lack of protection of data during input and output, and incorrect execution of the correctness checks. We propose the robust ABFT technique to handle those weakpoints. We then generalize it to programs that use assertions, where similar problems arise, leading to the technique of robust assertions, whose effectiveness is shown by fault injection experiments on a realistic control application. With this technique a system follows a new failure model, that we call fail-bounded, where with high probability all results produced are either correct or, if wrong, they are within a certain bound of the correct value, whose exact value depends on the output assertions used. We claim that this failure model is very useful to describe the behavior of many low redundancy systems.
机译:我们研究了在根据相当普通的故障模型注入的故障下基于算法的容错(ABFT)技术的行为。除了浮点运算中的舍入误差问题外,我们还确定了另外两个弱点,即输入和输出期间缺乏数据保护,以及正确性检查的执行不正确。我们提出了健壮的ABFT技术来处理这些弱点。然后,我们将其推广到使用断言的程序,其中会出现类似的问题,从而导致健壮断言的技术,其有效性通过在实际控制应用程序上的故障注入实验得到证明。采用这种技术,系统遵循新的故障模型,我们称之为故障边界模型,其中产生的所有结果很有可能是正确的,或者如果错误,则它们都在正确值的一定范围内,而正确值取决于正确值。使用的输出断言。我们声称此故障模型对于描述许多低冗余系统的行为非常有用。

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