We present a discrete-event simulation tool to study distributed algorithms and systems whose entities can be modeled using state machines. Our design is focused on the flexibility to simulate different communications...
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We present a discrete-event simulation tool to study distributed algorithms and systems whose entities can be modeled using state machines. Our design is focused on the flexibility to simulate different communications environments and concurrent executions.
Generalized canonical correlation analysis (GCCA) aims at extracting common structure from multiple 'views', i.e., high-dimensional matrices representing the same objects in different feature domains - an exte...
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ISBN:
(纸本)9781509054749
Generalized canonical correlation analysis (GCCA) aims at extracting common structure from multiple 'views', i.e., high-dimensional matrices representing the same objects in different feature domains - an extension of classical two-view CCA. Existing (G)CCA algorithms have serious scalability issues, since they involve square root factorization of the correlation matrices of the views. The memory and computational complexity associated with this step grow as a quadratic and cubic function of the problem dimension (the number of samples / features), respectively. To circumvent such difficulties, we propose a GCCA algorithm whose memory and computational costs scale linearly in the problem dimension and the number of nonzero data elements, respectively. Consequently, the proposed algorithm can easily handle very large sparse views whose sample and feature dimensions both exceed 100,000 - while the current approaches can only handle thousands of features / samples. Our second contribution is a distributed algorithm for GCCA, which computes the canonical components of different views in parallel and thus can further reduce the runtime significantly (by ≥ 30% in experiments) if multiple cores are available. Judiciously designed synthetic and real-data experiments using a multilingual dataset are employed to showcase the effectiveness of the proposed algorithms.
The authors develop two new algorithms for solving a finite constraint satisfaction problem (FCSP) in parallel. In particular, they give a parallel algorithm for the EREW PRAM model and a distributed algorithm for net...
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The authors develop two new algorithms for solving a finite constraint satisfaction problem (FCSP) in parallel. In particular, they give a parallel algorithm for the EREW PRAM model and a distributed algorithm for networks of interconnected processors. If an FCSP can be represented by an acyclic constraint network of size n with width bounded by a constant then: the parallel algorithm takes O(log n) time using O(n) processors and there is a mapping of this problem to a distributed computing network of poly(n) processors which stabilizes in O(log n) time.< >
The broadcast incremental power (BIP) algorithm is a centralized heuristic for the construction of energy-efficient broadcast trees in wireless networks. We discuss the issues associated with the development of distri...
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The broadcast incremental power (BIP) algorithm is a centralized heuristic for the construction of energy-efficient broadcast trees in wireless networks. We discuss the issues associated with the development of distributed algorithms for broadcast tree construction, and develop and evaluate several versions of distributed BIP (Dist-BIP). We compare the performance of these schemes with that of both centralized BIP and minimum-cost spanning tree (MST) algorithm.
In this brief announcement we summarize our results concerning distributed algorithms for LP-type problems in the well-known gossip model. LP-type problems include many important classes of problems such as (integer) ...
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ISBN:
(纸本)9781450361842
In this brief announcement we summarize our results concerning distributed algorithms for LP-type problems in the well-known gossip model. LP-type problems include many important classes of problems such as (integer) linear programming, geometric problems like smallest enclosing ball and polytope distance, and set problems like hitting set and set cover. In the gossip model, a node can only push information to or pull information from nodes chosen uniformly at random. Protocols for the gossip model are usually very practical due to their fast convergence, their simplicity, and their stability under stress and disruptions. Our algorithms are very efficient (logarithmic rounds or better with just polylogarithmic communication work per node per round) whenever the combinatorial dimension of the given LP-type problem is constant, even if the size of the given LP-type problem is polynomially large in the number of nodes.
In a dynamic network topological events can occur at any time, and no stable periods can be assumed. To make designing distributed algorithms easier, we model these latter with a local computation model. The implement...
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ISBN:
(纸本)9781509004799
In a dynamic network topological events can occur at any time, and no stable periods can be assumed. To make designing distributed algorithms easier, we model these latter with a local computation model. The implementation of a local computation model using message passing communication model has given rise to various problems. Among these we can mention the use of a great amount of communication and computation resources. In order to solve these problems, we propose another implementation of rewriting systems using mobile agents. We present then, using local computations, a framework for describing distributed algorithms for mobile agents in a dynamic network. We make use of the high level encoding of these algorithms as transition rules. The main advantage of this uniform and formal approach is the proof correctness of distributed algorithms. We illustrate this approach by giving an example of distributed computation of a hierarchical spanning tree by mobile agents in a dynamic network.
A k-dominating set in a graph G = (V, E) is a set U subset of V such that every vertex of G is either in U or has at least k neighbors in U. In this paper we give simple distributed approximation algorithms in the sta...
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A k-dominating set in a graph G = (V, E) is a set U subset of V such that every vertex of G is either in U or has at least k neighbors in U. In this paper we give simple distributed approximation algorithms in the standard Local model of computations for the minimum k-dominating set problem for k >= 2 in graphs with no K-3,K-h-minor for some h is an element of Z(+) and graphs with no K-4,K-4-minor. In particular, this gives fast distributed approximations for graphs of bounded genus and linklessly embeddable graphs. The algorithms give a constant approximation ratio and run in a constant number of rounds. In addition, we will give a (1 + epsilon)-approximation for an arbitrary fixed epsilon > 0 which runs in 0 (log* n) rounds where n is the order of a graph. (C) 2020 Elsevier B.V. All rights reserved.
Viral marketing is becoming important due to the popularity of online social networks (OSNs). Companies may provide incentives (e. g., via free samples of a product) to a small group of users in an OSN, and these user...
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Viral marketing is becoming important due to the popularity of online social networks (OSNs). Companies may provide incentives (e. g., via free samples of a product) to a small group of users in an OSN, and these users provide recommendations to their friends, which eventually increases the overall sales of a given product. Nevertheless, this also opens a door for malicious behaviors: dishonest users may intentionally give misleading recommendations to their friends so as to distort the normal sales distribution. In this paper, we propose a detection framework to identify dishonest users in the OSNs. In particular, we present a set of fully distributed and randomized algorithms, and also quantify the performance of the algorithms by deriving probability of false positive, probability of false negative, and the distribution of number of detection rounds. Extensive simulations are also carried out to illustrate the impact of misleading recommendations and the effectiveness of our detection algorithms. The methodology we present here will enhance the security level of viral marketing in the OSNs.
The design and the proof of distributed algorithms are difficult tasks due to the lack of knowledge of the global state and the non determinism in the execution of the processes. Formal methods can guarantee that thes...
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ISBN:
(纸本)9781479904051
The design and the proof of distributed algorithms are difficult tasks due to the lack of knowledge of the global state and the non determinism in the execution of the processes. Formal methods can guarantee that these algorithms run as designed. In this paper, we show that the proof of complex distributed algorithms can be simplified by combining already proved sub-algorithms. To do so, we use a high level encoding of distributed algorithms in form of graph relabeling systems and we propose a formal proof methodology. The proposed methodology combines refinement and decomposition techniques and relies on the correct-by-construction paradigm used by the Event-B method.
We argue that high-level Petri nets are well suited for the representation of distributed algorithms as well as for correctness proofs. To this end, we provide a simple definition of high-level Petri nets, a way to fo...
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We argue that high-level Petri nets are well suited for the representation of distributed algorithms as well as for correctness proofs. To this end, we provide a simple definition of high-level Petri nets, a way to formulate message passing algorithms in this notion, a temporal logic style language for the formulation of properties, and a proof technique which combines techniques from Petri net theory and from temporal logic. As a nontrivial case study we present a variant of Raymond's (1989) message passing mutual exclusion algorithm that works on arbitrary connected networks.
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