Shared-memory vs. message-passing in an asynchronous distributed environment
Proceedings of the eighth annual ACM Symposium on Principles of distributed computing
Sharing memory robustly in message-passing systems
PODC '90 Proceedings of the ninth annual ACM symposium on Principles of distributed computing
Sequential consistency versus linearizability
ACM Transactions on Computer Systems (TOCS)
Resource Bounds for Self-Stabilizing Message-Driven Protocols
SIAM Journal on Computing
Self-stabilization
Distributed computing: fundamentals, simulations and advanced topics
Distributed computing: fundamentals, simulations and advanced topics
Self-stabilizing systems in spite of distributed control
Communications of the ACM
Distributed Algorithms
Efficient and Robust Sharing of Memory in Message-Passing Systems (Extended Abstract)
WDAG '96 Proceedings of the 10th International Workshop on Distributed Algorithms
Transformations of Self-Stabilizing Algorithms
DISC '02 Proceedings of the 16th International Conference on Distributed Computing
Forward and Backward Simulations for Timing-Based Systems
Proceedings of the Real-Time: Theory in Practice, REX Workshop
Self-stabilization of dynamic systems assuming only read/write atomicity
Distributed Computing - Special issue: Self-stabilization
Self-stabilizing extensions for message-passing systems
Distributed Computing - Special issue: Self-stabilization
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In this paper, we are interested in transformations of self-stabilizing algorithms from one model to another that preserve stabilization. We propose an easy technique for proving correctness of a natural class of transformations of self-stabilizing algorithms from any model to any other. We present a new transformation of self-stabilizing algorithms from a message passing model to a shared memory model with a finite number of registers of bounded size and processors of bounded memory and prove it correct using our technique. This transformation is not wait-free, but we prove that no such transformation can be wait-free. For our transformation, we use a new self-stabilizing token-passing algorithm for the shared memory model. This algorithm stabilizes in O(nlog 2n) rounds, which improves existing algorithms.