Networks and distributed computation: concepts, tools, and algorithms
Networks and distributed computation: concepts, tools, and algorithms
Solvability of the asynchronous ranking problem
Information Processing Letters
Algorithms in C++
Introduction to distributed algorithms
Introduction to distributed algorithms
On the recognition of families of graphs with local computations
Information and Computation
Medians and centres of polyominoes
Information Processing Letters
Local and global properties in networks of processors (Extended Abstract)
STOC '80 Proceedings of the twelfth annual ACM symposium on Theory of computing
Locally guided randomized elections in trees: The totally fair case
Information and Computation
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Election is a classical paradigm in distributed algorithms. This paper aims to design and analyze a distributed algorithm choosing a node in a graph which models a network. In case the graph is a tree, a simple schema of algorithm acts as follows: it removes leaves until the graph is reduced to a single vertex; the elected one. In Metivier et al. (2003) [7], the authors studied a randomized variant of this schema which gives the same probability of being elected to each node of the tree. They conjectured that the expected election duration of this algorithm is O(ln(n)) where n denotes the size of the tree, and asked whether it is possible to use the same algorithm to obtain a fair election in other classes of graphs. In this paper, we prove their conjecture. We then introduce a new structure called polyominoid graphs. We show how a spanning tree for these graphs can be computed locally so that our algorithm, applied to this spanning tree, gives a uniform election algorithm on polyominoids.