Distributed Computing: A Locality-Sensitive Approach
Presents the locality-sensitive approach to distributed network algorithms-the utilization of locality to simplify control structures and algorithms and reduce their costs. The author begins with an introductory exposition of distributed network algorithms focusing on topics that illustrate the role of locality in distributed algorithmic techniques. He then introduces locality-preserving network representations and describes sequential and distributed techniques for their construction. Finally, the applicability of the locality-sensitive approach is demonstrated through several applications. Gives a thorough exposition of network spanners and other locality-preserving network representations such as sparse covers and partitions. The book is useful for computer scientists interested in distributed computing, electrical engineers interested in network architectures and protocols, and for discrete mathematicians and graph theorists.
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ACM Symp applies arbitrary asynchronous model average stretch BFS tree bits buffer Chapter chordal graphs cluster coarsening collection coloring communication complete graph Consider convergecast Corollary cost deﬁned deﬁnition denote Depth(T described deterministic discussed distance distributed algorithm Distributed Computing distributed setting execution exists Figure ﬁrst ﬁxed fragment given global graph G I greedy algorithm hence hypercube identiﬁers induced subgraph input integer intercluster edges iteration layer Lemma logn lower bound matroid maximal independent set maximum memory requirements message complexity neighborhoods neighbors network G Note number of edges O(log optimal output p-regional matching parameter partial partition Peleg performed phase planar graphs polylogarithmic problem Proc Procedure processor Proof properties protocol prove pulse queries radius representations resource unit resulting root routing scheme satisﬁes Section shortest path shortest path tree spanner spanning tree sparse Speciﬁcally stored structure synchronizer topology trade-off tree cover unweighted upcast update vertex vertices weighted graph