A tree-based algorithm for distributed mutual exclusion
ACM Transactions on Computer Systems (TOCS)
Token management schemes and random walks yield self-stabilizing mutual exclusion
PODC '90 Proceedings of the ninth annual ACM symposium on Principles of distributed computing
A self-stabilizing algorithm for constructing breadth-first trees
Information Processing Letters
A distributed mutual exclusion algorithm
ACM Transactions on Computer Systems (TOCS)
Efficient token-based control in rings
Information Processing Letters
IEEE Transactions on Parallel and Distributed Systems
Distributed Algorithms
Self-Stabilizing Local Mutual Exclusion and Daemon Refinement
DISC '00 Proceedings of the 14th International Conference on Distributed Computing
Service Time Optimal Self-Stabilizing Token Circulation Protocol on Anonymous Unidrectional Rings
SRDS '02 Proceedings of the 21st IEEE Symposium on Reliable Distributed Systems
Self-stabilizing depth-first token circulation in arbitrary rooted networks
Distributed Computing
Self-stabilizing depth-first token circulation on networks
Distributed Computing - Special issue: Self-stabilization
Calibrating embedded protocols on asynchronous systems
Information Sciences: an International Journal
Timer-based composition of fault-containing self-stabilizing protocols
Information Sciences: an International Journal
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This paper presents a new method for request-based self-stabilizing token passing. A token is passed via a dynamic BFS (breadth-first search) tree rooted at a requesting process. When one of the tree edges reaches a process that has a token, the process is aware of the occurrence of a request. Then the token is passed towards the root. Even if multiple tokens stay at distinct roots, it can be shown that they will be merged into a single token. Furthermore, each request-rooted tree continues to grow until the request is serviced. As a result, the tree with a request that has long been neglected grows larger and larger, which makes it easier for the requesting process to get a token. Such advantages can be achieved by using bounded memory. We also evaluate the stabilization time and the efficiency of servicing k requests, called k-covering time, of our method.