Abstract
This paper presents a self-stabilizing failure detector, asynchronous consensus and replicated state-machine algorithm suite, the components of which can be started in an arbitrary state and converge to act as a virtual state-machine.
Self-stabilizing algorithms can cope with transient faults. Transient faults can alter the system state to an arbitrary state and hence, cause a temporary violation of the safety property of the consensus. New requirements for consensus that fit the on-going nature of self-stabilizing algorithms are presented. The wait-free consensus (and the replicated state-machine) algorithm presented is a classic combination of a failure detector and a (memory bounded) rotating coordinator consensus that satisfy both eventual safety and eventual liveness.
Several new techniques and paradigms are introduced. The bounded memory failure detector abstracts away synchronization assumptions using bounded heartbeat counters combined with a balance-unbalance mechanism. The practically infinite paradigm is introduced in the scope of self-stabilization, where an execution of, say, 264 sequential steps is regarded as (practically) infinite. Finally, we present the first self-stabilizing wait-free reset mechanism that ensures eventual safety and can be used in other scopes.
Partially supported by the Israeli Ministry of Science, the Lynn and William Frankel Center for Computer Sciences, and the Rita Altura Trust Chair in Computer Sciences.
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Dolev, S., Kat, R.I., Schiller, E.M. (2006). When Consensus Meets Self-stabilization. In: Shvartsman, M.M.A.A. (eds) Principles of Distributed Systems. OPODIS 2006. Lecture Notes in Computer Science, vol 4305. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11945529_5
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