• DocumentCode
    1090027
  • Title

    Construction of check sets for algorithm-based fault tolerance

  • Author

    Gu, Dechang ; Rosenkrantz, Daniel J. ; Ravi, S.S.

  • Author_Institution
    Dept. of Comput. Sci. Sch. of Eng., North Carolina A&T State Univ., Greensboro, NC, USA
  • Volume
    43
  • Issue
    6
  • fYear
    1994
  • fDate
    6/1/1994 12:00:00 AM
  • Firstpage
    641
  • Lastpage
    650
  • Abstract
    Algorithm-based fault tolerance (ABFT) is a popular approach to achieve fault and error detection in multiprocessor systems. The design problem for ABFT is concerned with the construction of a check set of minimum cardinality that detects a specified number of errors or faults. Previous work on this problem has assumed an a priori bound on the size of a check. We motivate and carry out an investigation of the problem without the bounded check size assumption. We establish upper and lower bounds on the number of checks needed to detect a given number of errors. The upper bounds are obtained through new schemes which are easy to implement, and the lower bounds are established using new types of arguments. These bounds are sharply different from those previously established under the bounded check size model. We also show that unlike error detection, the design problem for fault detection is NP-hard even for detecting only one fault
  • Keywords
    computational complexity; error detection; fault tolerant computing; multiprocessing systems; ABFT; NP-hard; algorithm-based fault tolerance; bounded check size assumption; bounded check size model; check set; check sets; design problem; error detection; fault detection; minimum cardinality; multiprocessor systems; Arithmetic; Computer science; Fault detection; Fault tolerance; Fault tolerant systems; Hardware; NASA; Parallel algorithms; Polynomials; Upper bound;
  • fLanguage
    English
  • Journal_Title
    Computers, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9340
  • Type

    jour

  • DOI
    10.1109/12.286298
  • Filename
    286298