160 research outputs found
On Efficient Distributed Construction of Near Optimal Routing Schemes
Given a distributed network represented by a weighted undirected graph
on vertices, and a parameter , we devise a distributed
algorithm that computes a routing scheme in
rounds, where is the hop-diameter of the network. The running time matches
the lower bound of rounds (which holds for any
scheme with polynomial stretch), up to lower order terms. The routing tables
are of size , the labels are of size , and
every packet is routed on a path suffering stretch at most . Our
construction nearly matches the state-of-the-art for routing schemes built in a
centralized sequential manner. The previous best algorithms for building
routing tables in a distributed small messages model were by \cite[STOC
2013]{LP13} and \cite[PODC 2015]{LP15}. The former has similar properties but
suffers from substantially larger routing tables of size ,
while the latter has sub-optimal running time of
Distributed Strong Diameter Network Decomposition
For a pair of positive parameters , a partition of the
vertex set of an -vertex graph into disjoint clusters of
diameter at most each is called a network decomposition, if the
supergraph , obtained by contracting each of the clusters
of , can be properly -colored. The decomposition is
said to be strong (resp., weak) if each of the clusters has strong (resp.,
weak) diameter at most , i.e., if for every cluster and
every two vertices , the distance between them in the induced graph
of (resp., in ) is at most .
Network decomposition is a powerful construct, very useful in distributed
computing and beyond. It was shown by Awerbuch \etal \cite{AGLP89} and
Panconesi and Srinivasan \cite{PS92}, that strong network decompositions can be computed in
distributed time. Linial and Saks \cite{LS93} devised an
ingenious randomized algorithm that constructs {\em weak} network decompositions in time. It was however open till now
if {\em strong} network decompositions with both parameters can be constructed in distributed time.
In this paper we answer this long-standing open question in the affirmative,
and show that strong network decompositions can be
computed in time. We also present a tradeoff between parameters
of our network decomposition. Our work is inspired by and relies on the
"shifted shortest path approach", due to Blelloch \etal \cite{BGKMPT11}, and
Miller \etal \cite{MPX13}. These authors developed this approach for PRAM
algorithms for padded partitions. We adapt their approach to network
decompositions in the distributed model of computation
Near Isometric Terminal Embeddings for Doubling Metrics
Given a metric space (X,d), a set of terminals K subseteq X, and a parameter t >= 1, we consider metric structures (e.g., spanners, distance oracles, embedding into normed spaces) that preserve distances for all pairs in K x X up to a factor of t, and have small size (e.g. number of edges for spanners, dimension for embeddings). While such terminal (aka source-wise) metric structures are known to exist in several settings, no terminal spanner or embedding with distortion close to 1, i.e., t=1+epsilon for some small 0<epsilon<1, is currently known.
Here we devise such terminal metric structures for doubling metrics, and show that essentially any metric structure with distortion 1+epsilon and size s(|X|) has its terminal counterpart, with distortion 1+O(epsilon) and size s(|K|)+1. In particular, for any doubling metric on n points, a set of k=o(n) terminals, and constant 0<epsilon<1, there exists
- A spanner with stretch 1+epsilon for pairs in K x X, with n+o(n) edges.
- A labeling scheme with stretch 1+epsilon for pairs in K x X, with label size ~~ log k.
- An embedding into l_infty^d with distortion 1+epsilon for pairs in K x X, where d=O(log k). Moreover, surprisingly, the last two results apply if only K is a doubling metric, while X can be arbitrary
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