* Exclusion: At most one process executes its critical section at any time.

) James H. Anderson and Mark Moir Department of Computer Science The University of North Carolina at Chapel Hill Chapel Hill, North Carolina 27599-3175, USA Abstract We present a methodology for the implementation of resilient shared objects that allows the desired level of resiliency to be selected based on performance concerns. This methodology is based on the k-exclusion and renaming problems. To make this methodology practical, we present a number of fast k-exclusion algorithms that employ "local spin" techniques to minimize the impact of the processor-to-memory bottleneck. We also present a new "long-lived" renaming algorithm. Our k- exclusion algorithms are based on commonly-available synchronization primitives, are fast in the absence of contention, and have scalable performance when contention exceeds expected thresholds. By contrast, all prior k-exclusion algorithms either require unrealistic atomic operations or perform badly. Our k-exclusion algorithms are also the first ...

The rst self-stabilizing algorithm published by Dijkstra in 1973 assumed the existence of a central daemon, that activates one processor at time to change state as a function of its own state and the state of a neighbor. Subsequent research has reconsidered this algorithm without the assumption of a central daemon, and under dierent forms of communication, such as the model of link registers. In all of these investigations, one common feature is the atomicity of communication, whether by shared variables or read/write registers. This paper weakens the atomicity assumptions for the communication model, proposing versions of Dijkstra's algorithm that tolerate various weaker forms of atomicity, including cases of regular and safe registers. The paper also presents an implementation of Dijkstra's algorithm based on registers that have probabilistically correct behavior, which requires a notion of weak stabilization, where Markov chains are used to evaluate the probability to be in a safe con guration.

Recent decentralised event-based systems have focused on providing event delivery which scales with increasing number of processes. While the main focus of research has been on ensuring that processes maintain only a small amount of information on maintaining membership and routing, an important factor in achieving scalability for event-based peer-to-peer dissemination system is the number of events disseminated at the same time. This work presents a dynamic and fault tolerant cluster management method which can be used to coordinate concurrent access to resources in a peer-to-peer system. In the context of event-based dissemination systems the cluster management can be used to control the number of concurrently disseminated events. We present and analyse an algorithm implementing the proposed cluster management model in a faulttolerant and decentralised way. The algorithm provides for each cluster a limited set of tickets. A process which has obtained a ticket may send events corresponding to the resources of the cluster. The algorithm guarantees that no two processes ever issue an event corresponding to the same ticket at the same time. The cluster management model on its own has interesting properties which can be useful for many peer-to-peer applications.

A self-stabilizing algorithm, regardless of the initial system state, converges in nite time to