Abstract

In a fault-tolerant distributed system, different non-faulty processes may arrive at different values for a given system parameter. To resolve this disagreement, processes must exchange and vote upon their respective local values. Faulty processes may attempt to inhibit agreement by acting in a malicious or "Byzantine" manner. Approximate agreement defines one form of agreement in which the voted values obtained by the non-faulty processes need not be identical. Instead, they need only agree to within a predefined tolerance. Approximate agreement can be achieved by a sequence of convergent voting rounds, in which the range of values held by non-faulty processes is reduced in each round. Historically, each new convergent voting algorithm has been accompanied by ad-hoc proofs of its convergence rate and fault-tolerance, using an overly conservative fault model in which all faults exhibit worst-case Byzantine behavior. This paper presents a general method to quickly determine convergence rate and fault-tolerance for any member of a broad family of convergent voting algorithms. This method is developed under a realistic mixed-mode fault model comprised of asymmetric, symmetric, and benign fault modes. These results are employed to more accurately analyze the properties of several existing voting algorithms, to derive a sub-family of optimal mixed-mode voting algorithms, and to quickly determine the properties of proposed new voting algorithms.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.