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• Improved distributed approximation for Steiner tree. • Approximation algorithms for Steiner tree in the CONGEST model of distributed computing. • Steiner tree problem in network optimization. In this paper we present two deterministic distributed algorithms for the Steiner tree (ST) problem in the CONGEST model. The first algorithm computes a 2 (1 − 1 / ℓ) -approximate ST using O (S + n log ⁎ ⁡ n) rounds and O (m S + n 3 / 2) messages for a graph of n nodes and m edges, where S is the shortest path diameter of the graph and ℓ is the number of leaf nodes in the optimal ST. It improves the round complexity of the best distributed ST algorithm known so far, which is O ˜ (S + min { S t , n }) [34] , where t is the number of terminal nodes. The second algorithm improves the message complexity of the first one by dropping the additive term of O (n 3 / 2) at the expense of a logarithmic multiplicative factor in the round complexity. We also show that for graphs with S = O (log ⁡ n) , a 2 (1 − 1 / ℓ) -approximate ST can be deterministically computed using O ˜ (n) rounds and O ˜ (m) messages and these complexities almost coincide with the results of some of the singularly-optimal minimum spanning tree (MST) algorithms proposed in [15,22,37]. [ABSTRACT FROM AUTHOR]

Routing protocols are at the core of distributed systems performances, especially in the presence of faults. A classical approach to this problem is to build a spanning tree of the distributed system. Numerous spanning tree construction algorithms depending on the optimized metric exist (total weight, height, distance with respect to a particular process, …) both in fault-free and faulty environments. In this paper, we aim at optimizing the diameter of the spanning tree by constructing a minimum diameter spanning tree. We target environments subject to transient faults ( i.e. faults of finite duration). Hence, we present a self-stabilizing algorithm for the minimum diameter spanning tree construction problem in the state model. Our protocol has the following attractive features. It is the first algorithm for this problem that operates under the unfair and distributed adversary (or daemon ). In other words, no restriction is made on the asynchronous behavior of the system. Second, our algorithm needs only O ( log n ) bits of memory per process (where n is the number of processes), that improves the previous result by a factor n . These features are not achieved to the detriment of the convergence time, which stays polynomial. [ABSTRACT FROM AUTHOR]