Adaptive Stabilization of Reactive Protocols

Abstract. A self-stabilizing distributed protocol can recover from any state-corrupting fault. A self-stabilizing protocol is called adaptive if its recovery time is proportional to the number of processors hit by the fault. General adaptive protocols are known for the special case of function computations: these are tasks that map static distributed inputs to static distributed outputs. In reactive distributed systems, input values at each node change on-line, and dynamic distributed outputs are to be generated in response in an on-line fashion. To date, only some specific reactive tasks have had an adaptive implementation. In this paper we outline the first proof that all reactive tasks admit adaptive protocols. The key ingredient of the proof is an algorithm for distributing input values in an adaptive fashion. Our algorithm is optimal, up to a constant factor, in its fault resilience, response time, and recovery time.

EFFICIENT COUNTING WITH OPTIMAL RESILIENCE

Consider a complete communication network of n nodes, where the nodes receive a common clock pulse. We study the synchronous c-counting problem: given any starting state and up to f faulty nodes with arbitrary behavior, the task is to eventually have all correct nodes labeling the pulses with increasing values modulo c in agreement. Thus, we are considering algorithms that are self-stabilizing despite Byzantine failures. In this work, we give new algorithms for the synchronous counting problem that (1) are deterministic, (2) have optimal resilience, (3) have a linear stabilization time in f (asymptotically optimal), (4) use a small number of states, and, consequently, (5) communicate a small number of bits per round. Prior algorithms either resort to randomization, use a large number of states and need high communication bandwidth, or have suboptimal resilience. In particular, we achieve an exponential improvement in both state complexity and message size for deterministic algorithms. Moreover, we present two complementary approaches for reducing the number of bits communicated during and after stabilization.Peer reviewe