Focs 2011 — List of Accepted
نویسندگان
چکیده
A central theme in distributed network algorithms concerns understanding and coping with the issue of locality. Despite considerable progress, research efforts in this direction have not yet resulted in a solid basis in the form of a fundamental computational complexity theory for locality. Inspired by sequential complexity theory, we focus on a complexity theory for distributed decision problems. In the context of locality, solving a decision problem requires the processors to independently inspect their local neighborhoods and then collectively decide whether a given global input instance belongs to some specified language. We consider the standard $\cal{LOCAL}$ model of computation and define $LD(t)$ (for local decision) as the class of decision problems that can be solved in $t$ communication rounds. We first study the intriguing question of whether randomization helps in local distributed computing, and to what extent. Specifically, we define the corresponding randomized class $BPLD(t,p,q)$, containing all languages for which there exists a randomized algorithm that runs in $t$ rounds, accepts correct instances with probability at least $p$ and rejects incorrect ones with probability at least $q$. We show that $p^2+q = 1$ is a threshold for the containment of $LD(t)$ in $BPLD(t,p,q)$. More precisely, we show that there exists a language that does not belong to $LD(t)$ for any $t=o(n)$ but does belong to $BPLD(0,p,q)$ for any $p,q\in (0,1]$ such that $p^2+q\leq 1$. On the other hand, we show that, restricted to hereditary languages, $BPLD(t,p,q)=LD(O(t))$, for any function $t$ and any $p,q\in (0,1]$ such that $p^2+q> 1$. In addition, we investigate the impact of non-determinism on local decision, and establish some structural results inspired by classical computational complexity theory. Specifically, we show that non-determinism does help, but that this help is limited, as there exist languages that cannot be decided non-deterministically. Perhaps surprisingly, it turns out that it is the combination of randomization with non-determinism that enables to decide all languages in constant time. Finally, we introduce the notion of local reduction, and establish some completeness results.
منابع مشابه
Local List Recovery of High-Rate Tensor Codes & Applications
In this work, we give the first construction of high-rate locally list-recoverable codes. Listrecovery has been an extremely useful building block in coding theory, and our motivation is to use these codes as such a building block. In particular, our construction gives the first capacity-achieving locally list-decodable codes (over constant-sized alphabet); the first capacity achieving globally...
متن کاملThe Bayesian Learner is Optimal for Noisy Binary Search (and Pretty Good for Quantum as Well)
We use a Bayesian approach to optimally solve problems in noisy binary search. We deal with two variants: • Each comparison is erroneous with independent probability 1− p. • At each stage k comparisons can be performed in parallel and a noisy answer is returned. We present a (classical) algorithm which solves both variants optimally (with respect to p and k), up to an additive term of O(loglog ...
متن کاملOn the List and Bounded Distance Decodibility of the Reed-Solomon Codes (Extended Abstract)
For an error-correcting code and a distance bound, the list decoding problem is to compute all the codewords within the given distance to a received message. The bounded distance decoding problem, on the other hand, is to find one codeword if there exists one or more codewords within the given distance, or to output the empty set if there does not. Obviously the bounded distance decoding proble...
متن کاملA Better Lower Bound for Quantum Algorithms Searching an Ordered List
We show that any quantum algorithm searching an ordered list of n elements needs to examine at least log2 n 12 − O(1) of them. Classically, log2 n queries are both necessary and sufficient. This shows that quantum algorithms can achieve only a constant speedup for this problem. Our result improves lower bounds of Buhrman and de Wolf(quant-ph/9811046) and Farhi, Goldstone, Gutmann and Sipser (qu...
متن کاملList randomization for sensitive behavior: An application for measuring use of loan proceeds
21 22 23 24 25 26 27 28 29 Article history: Received 28 January 2010 Received in revised form 26 August 2011 Accepted 30 August 2011 Available online xxxx
متن کاملApproximate Local Decoding of Cubic Reed-Muller Codes Beyond the List Decoding Radius
We consider the question of decoding Reed-Muller codes over Fn 2 beyond their listdecoding radius. Since, by definition, in this regime one cannot demand an efficient exact list-decoder, we seek an approximate decoder: Given a word F and radii r′ > r > 0, the goal is to output a codeword within radius r′ of F, if there exists a codeword within distance r. As opposed to the list decoding problem...
متن کامل