1,721,024 research outputs found
Fast distributed algorithms for (weakly) connected dominating sets and linear-size skeletons
No full textMotivated by routing issues in ad hoc networks, we present polylogarithmic-time distributed algorithms for two problems. Given a network, we first show how to compute connected and weakly connected dominating sets whose size is at most O (log A) times the optimum, A being the maximum degree of the input network. This is best-possible if NP not subset of DTIME[n(O(log log n))] and if the processors are required to run in polynomial-time. We then show how to construct dominating sets that have the above properties, as well as the "low stretch" property that any two adjacent nodes in the network have their dominators at a distance of at most O (log n) in the output network. (Given a dominating set S, a dominator of a vertex u is any nu epsilon S such. that the distance between u and v is at most one.) We also show our time bounds to be essentially optimal. (c) 2005 Elsevier Inc. All rights reserved
Unassailable sensor networks
No full textWe show that massive attacks against sensor networks that use random key pre-distribution schemes cannot be cheap, provided that the parameters are set in the right way. By choosing them appropriately, any adversary whose aim is to compromise a large fraction of the communication links is forced, with overwhelming probability, to capture a large fraction of the nodes. This holds regardless of the information available to the adversary to select the nodes. We consider two important security properties: We say that the network is unassailable if the adversary cannot compromise a linear fraction of the communication links by compromising a sub-linear fraction of the nodes, and that the network is unsplittable if the adversary cannot partition the network into two (or more) linear size fragments. We show how to set the relevant parameters of random key pre-distribution - pool and key ring size - in such a way that the network is not only connected, but also provably unassailable and un-splittable with high probability. Moreover, we also show how to set the parameters in such a way to form a giant component in the network, a connected subgraph including, say, 99% of the sensors. Giant components emerge by using much smaller key rings, are sparse, and, quite remarkably, are provably unassailable and unsplittable as well. All these results are supported by experiments. Copyright 2008 ACM
Topology Dependent Bounds on Rounds and Communication
No full textBased on joint works with Michael Langberg, Shi Li, Jaikumar Radhakrishnan and Atri Rudra.Non UBCUnreviewedAuthor affiliation: Tata Institute of Fundamental ResearchFacult
A fast approximation algorithm for solving the complete set packing problem
No full textWe study the complete set packing problem (CSPP) where the family of feasible subsets may include all possible combinations of objects. This setting arises in applications such as combinatorial auctions (for selecting optimal bids) and cooperative game theory (for finding optimal coalition structures). Although the set packing problem has been well-studied in the literature, where exact and approximation algorithms can solve very large instances with up to hundreds of objects and thousands of feasible subsets, these methods are not extendable to the CSPP since the number of feasible subsets is exponentially large. Formulating the CSPP as an MILP and solving it directly, using CPLEX for example, is impossible for problems with more than 20 objects. We propose a new mathematical formulation for the CSPP that directly leads to an efficient algorithm for finding feasible set packings (upper bounds). We also propose a new formulation for finding tighter lower bounds compared to LP relaxation and develop an efficient method for solving the corresponding large-scale MILP. We test the algorithm with the winner determination problem in spectrum auctions, the coalition structure generation problem in coalitional skill games, and a number of other simulated problems that appear in the literature
Distance-Preserving Subgraphs of Interval Graphs
Full text linkWe consider the problem of finding small distance-preserving subgraphs of undirected, unweighted interval graphs that have k terminal vertices. We show that every interval graph admits a distance-preserving subgraph with O(k log k) branching vertices. We also prove a matching lower bound by exhibiting an interval graph based on bit-reversal permutation matrices. In addition, we show that interval graphs admit subgraphs with O(k) branching vertices that approximate distances up to an additive term of +1
The Zero-Error Randomized Query Complexity of the Pointer Function
Full text linkThe pointer function of Goos, Pitassi and Watson and its variants have recently been used to prove separation results among various measures of complexity such as deterministic, randomized and quantum query complexity, exact and approximate polynomial degree, etc. In particular, Ambainis et al. (STOC 2016) obtained the widest possible (quadratic) separations between deterministic and zero-error randomized query complexity, as well as between bounded-error and zero-error randomized query complexity by considering variants of this pointer function.
However, as Ambainis et al. pointed out in their work, the precise zero-error complexity of the original pointer function was
not known. We show a lower bound of ~Omega(n^{3/4}) on the zero-error randomized query complexity of the pointer function on Theta(n * log(n)) bits; since an ~O(n^{3/4}) upper bound was already shown by Mukhopadhyay and Sanyal (FSTTCS 2015), our lower bound is optimal up to polylog factors. We, in fact, consider a generalization of the original function and obtain lower bounds for it that are optimal up to polylog factors
Tight Bounds for Communication-Assisted Agreement Distillation
Full text linkSuppose Alice holds a uniformly random string X in {0,1}^N and Bob holds a noisy version Y of X where each bit of X is flipped independently with probability epsilon in [0,1/2]. Alice and Bob would like to extract a common random string of min-entropy at least k. In this work, we establish the communication versus success probability trade-off for this problem by giving a protocol and a matching lower bound (under the restriction that the string to be agreed upon is determined by Alice's input X). Specifically, we prove that in order for Alice and Bob to agree on a common string with probability 2^{-gamma k} (gamma k >= 1), the optimal communication (up to o(k) terms, and achievable for large N) is precisely (C *(1-gamma) - 2 * sqrt{ C * (1-C) gamma}) * k, where C := 4 * epsilon * (1-epsilon). In particular, the optimal communication to achieve Omega(1) agreement probability approaches 4 * epsilon * (1-epsilon) * k.
We also consider the case when Y is the output of the binary erasure channel on X, where each bit of Y equals the corresponding bit of X with probability 1-epsilon and is otherwise erased (that is, replaced by a "?"). In this case, the communication required becomes (epsilon * (1-gamma) - 2 * sqrt{ epsilon * (1-epsilon) * gamma}) * k. In particular, the optimal communication to achieve Omega(1) agreement probability approaches epsilon * k, and with no communication the optimal agreement probability approaches 2^{- (1-sqrt{1-epsilon})/(1+sqrt{1-epsilon}) * k}.
Our protocols are based on covering codes and extend the approach of (Bogdanov and Mossel, 2011) for the zero-communication case. Our lower bounds rely on hypercontractive inequalities. For the model of bit-flips, our argument extends the approach of (Bogdanov and Mossel, 2011) by allowing communication; for the erasure model, to the best of our knowledge the needed hypercontractivity statement was not studied before, and it was established (given our application) by (Nair and Wang 2015). We also obtain information complexity lower bounds for these tasks, and together with our protocol, they shed light on the recently popular "most informative Boolean function" conjecture of Courtade and Kumar
Set Membership with Non-Adaptive Bit Probes
Full text linkWe consider the non-adaptive bit-probe complexity of the set membership problem, where a set S of size at most n from a universe of size m is to be represented as a short bit vector in order to answer membership queries of the form "Is x in S?" by non-adaptively probing the bit vector at t places. Let s_N(m,n,t) be the minimum number of bits of storage needed for such a scheme. In this work, we show existence of non-adaptive and adaptive schemes for a range of t that improves an upper bound of Buhrman, Miltersen, Radhakrishnan and Srinivasan (2002) on s_N(m,n,t). For three non-adaptive probes, we improve the previous best lower bound on s_N(m,n,3) by Alon and Feige (2009)
Property B: Two-Coloring Non-Uniform Hypergraphs
Full text linkThe following is a classical question of Erdős (Nordisk Matematisk Tidskrift, 1963) and of Erdős and Lovász (Colloquia Mathematica Societatis János Bolyai, vol. 10, 1975). Given a hypergraph ℱ with minimum edge-size k, what is the largest function g(k) such that if the expected number of monochromatic edges in ℱ is at most g(k) when the vertices of ℱ are colored red and blue randomly and independently, then we are guaranteed that ℱ is two-colorable? Duraj, Gutowski and Kozik (ICALP 2018) have shown that g(k) ≥ Ω(log k). On the other hand, if ℱ is k-uniform, the lower bound on g(k) is much higher: g(k) ≥ Ω(√{k / log k}) (Radhakrishnan and Srinivasan, Rand. Struct. Alg., 2000). In order to bridge this gap, we define a family of locally-almost-uniform hypergraphs, for which we show, via the randomized algorithm of Cherkashin and Kozik (Rand. Struct. Alg., 2015), that g(k) can be much higher than Ω(log k), e.g., 2^Ω(√{log k}) under suitable conditions
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