Analysis of a Class of Recovery Procedures
IEEE Transactions on Computers
A watchdog processor based general rollback technique with multiple retries
IEEE Transactions on Software Engineering
On switching policies for modular redundancy fault-tolerant computing systems
IEEE Transactions on Computers
Optimal checkpointing of real-time tasks
IEEE Transactions on Computers
Embedding triple-modular redundancy into a hypercube architecture
C3P Proceedings of the third conference on Hypercube concurrent computers and applications: Architecture, software, computer systems, and general issues - Volume 1
A RAM Architecture for Concurrent Access and on Chip Testing
IEEE Transactions on Computers
An Optimal Retry Policy Based on Fault Classification
IEEE Transactions on Computers
Design and Analysis of an Optimal Instruction-Retry Policy for TMR Controller Computers
IEEE Transactions on Computers
Sequencing Tasks to Minimize the Effects of Near-Coincident Faults in TMR Controller Computers
IEEE Transactions on Computers
A Replication Technique Based on a Functional and Attribute Grammar Computation Model
ISSRE '96 Proceedings of the The Seventh International Symposium on Software Reliability Engineering
Self-Checking Voter for High Speed TMR Systems
Journal of Electronic Testing: Theory and Applications
Energy-efficient soft error-tolerant digital signal processing
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Time separations of cyclic event rule systems with min-max timing constraints
Theoretical Computer Science
Energy efficient configuration for qos in reliable parallel servers
EDCC'05 Proceedings of the 5th European conference on Dependable Computing
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Failure to establish a majority among the processing modules in a triple modular redundant (TMR) system, called a TMR failure, is detected by using two voters and a disagreement detector. Assuming that no more than one module becomes permanently faulty during the execution of a task, Re-execution of the task on the Same HardWare (RSHW) upon detection of a TMR failure becomes a cost-effective recovery method, because 1) the TMR system can mask the effects of one faulty module while RSHW can recover from nonpermanent faults, and 2) system reconfiguration-Replace the faulty HardWare, reload, and Restart (RHWR)-is expensive both in time and hardware. We propose an adaptive recovery method for TMR failures by "optimally" choosing either RSHW or RHWR based on the estimation of the costs involved. We apply the Bayes theorem to update the likelihoods of all possible states in the TMR system with each voting result. Upon detection of a TMR failure, the expected cost of RSHW is derived with these likelihoods and then compared with that of RHWR. RSHW will continue either until it recovers from the TMR failure or until the expected cost of RSHW becomes larger than that of RHWR. As the number of unsuccessful RSHW's increases, the probability of permanent fault(s) having caused the TMR failure will increase, which will, in turn, increase the cost of RSHW. Our simulation results show that the proposed method outperforms the conventional reconfiguration method using only RHWR under various conditions.