
AbstractOne of the fundamental problems in distributed computing is how to efficiently perform routing in a faulty network in which each link fails with some probability. This article investigates how big the failure probability can be, before the capability to efficiently find a path in the network is lost. Our main results show tight upper and lower bounds for the failure probability, which permits routing both for the hypercube and for thed‐dimensional mesh. We use tools from percolation theory to show that in thed‐dimensional mesh, once a giant component appears—efficient routing is possible. A different behavior is observed when the hypercube is considered. In the hypercube there is a range of failure probabilities in which short paths exist with high probability, yet finding them must involve querying essentially the entire network. Thus the routing complexity of the hypercube shows an asymptotic phase transition. The critical probability with respect to routing complexity lies in a different location than that of the critical probability with respect to connectivity. Finally we show that an oracle access to links (as opposed to local routing) may reduce significantly the complexity of the routing problem. We demonstrate this fact by providing tight upper and lower bounds for the complexity of routing in the random graphGn,p. © 2007 Wiley Periodicals, Inc. Random Struct. Alg., 2008
Network design and communication in computer systems, Probability (math.PR), Reliability, testing and fault tolerance of networks and computer systems, hypercube, percolation, phase transition, Graph theory (including graph drawing) in computer science, Communication networks in operations research, FOS: Mathematics, Mathematics - Combinatorics, Combinatorics (math.CO), lower bound, Mathematics - Probability
Network design and communication in computer systems, Probability (math.PR), Reliability, testing and fault tolerance of networks and computer systems, hypercube, percolation, phase transition, Graph theory (including graph drawing) in computer science, Communication networks in operations research, FOS: Mathematics, Mathematics - Combinatorics, Combinatorics (math.CO), lower bound, Mathematics - Probability
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 8 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
