11,793 research outputs found

    Survey on Data-Centric based Routing Protocols for Wireless Sensor Networks

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    The great concern for energy that grew with the technological advances in the field of networks and especially in sensor network has triggered various approaches and protocols that relate to sensor networks. In this context, the routing protocols were of great interest. The aim of the present paper is to discuss routing protocols for sensor networks. This paper will focus mainly on the discussion of the data-centric approach (COUGAR, rumor, SPIN, flooding and Gossiping), while shedding light on the other approaches occasionally. The functions of the nodes will be discussed as well. The methodology selected for this paper is based on a close description and discussion of the protocol. As a conclusion, open research questions and limitations are proposed to the reader at the end of this paper

    Flexible constrained sampling with guarantees for pattern mining

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    Pattern sampling has been proposed as a potential solution to the infamous pattern explosion. Instead of enumerating all patterns that satisfy the constraints, individual patterns are sampled proportional to a given quality measure. Several sampling algorithms have been proposed, but each of them has its limitations when it comes to 1) flexibility in terms of quality measures and constraints that can be used, and/or 2) guarantees with respect to sampling accuracy. We therefore present Flexics, the first flexible pattern sampler that supports a broad class of quality measures and constraints, while providing strong guarantees regarding sampling accuracy. To achieve this, we leverage the perspective on pattern mining as a constraint satisfaction problem and build upon the latest advances in sampling solutions in SAT as well as existing pattern mining algorithms. Furthermore, the proposed algorithm is applicable to a variety of pattern languages, which allows us to introduce and tackle the novel task of sampling sets of patterns. We introduce and empirically evaluate two variants of Flexics: 1) a generic variant that addresses the well-known itemset sampling task and the novel pattern set sampling task as well as a wide range of expressive constraints within these tasks, and 2) a specialized variant that exploits existing frequent itemset techniques to achieve substantial speed-ups. Experiments show that Flexics is both accurate and efficient, making it a useful tool for pattern-based data exploration.Comment: Accepted for publication in Data Mining & Knowledge Discovery journal (ECML/PKDD 2017 journal track

    Enhanced sharing analysis techniques: a comprehensive evaluation

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    Sharing, an abstract domain developed by D. Jacobs and A. Langen for the analysis of logic programs, derives useful aliasing information. It is well-known that a commonly used core of techniques, such as the integration of Sharing with freeness and linearity information, can significantly improve the precision of the analysis. However, a number of other proposals for refined domain combinations have been circulating for years. One feature that is common to these proposals is that they do not seem to have undergone a thorough experimental evaluation even with respect to the expected precision gains. In this paper we experimentally evaluate: helping Sharing with the definitely ground variables found using Pos, the domain of positive Boolean formulas; the incorporation of explicit structural information; a full implementation of the reduced product of Sharing and Pos; the issue of reordering the bindings in the computation of the abstract mgu; an original proposal for the addition of a new mode recording the set of variables that are deemed to be ground or free; a refined way of using linearity to improve the analysis; the recovery of hidden information in the combination of Sharing with freeness information. Finally, we discuss the issue of whether tracking compoundness allows the computation of more sharing information

    ATM: approximate task memoization in the runtime system

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    Redundant computations appear during the execution of real programs. Multiple factors contribute to these unnecessary computations, such as repetitive inputs and patterns, calling functions with the same parameters or bad programming habits. Compilers minimize non useful code with static analysis. However, redundant execution might be dynamic and there are no current approaches to reduce these inefficiencies. Additionally, many algorithms can be computed with different levels of accuracy. Approximate computing exploits this fact to reduce execution time at the cost of slightly less accurate results. In this case, expert developers determine the desired tradeoff between performance and accuracy for each application. In this paper, we present Approximate Task Memoization (ATM), a novel approach in the runtime system that transparently exploits both dynamic redundancy and approximation at the task granularity of a parallel application. Memoization of previous task executions allows predicting the results of future tasks without having to execute them and without losing accuracy. To further increase performance improvements, the runtime system can memoize similar tasks, which leads to task approximate computing. By defining how to measure task similarity and correctness, we present an adaptive algorithm in the runtime system that automatically decides if task approximation is beneficial or not. When evaluated on a real 8-core processor with applications from different domains (financial analysis, stencil-computation, machine-learning and linear-algebra), ATM achieves a 1.4x average speedup when only applying memoization techniques. When adding task approximation, ATM achieves a 2.5x average speedup with an average 0.7% accuracy loss (maximum of 3.2%).This work has been supported by the RoMoL ERC Advanced Grant (GA 321253), by the Spanish Government (grant SEV2015-0493 of the Severo Ochoa Program), by the Spanish Ministry of Science and Innovation (contracts TIN2015-65316), by Generalitat de Catalunya (contracts 2014-SGR-1051 and 2014-SGR-1272) and the European HiPEAC Network of Excellence. M. Moretó has been partially supported by the Ministry of Economy and Competitiveness under Juan de la Cierva postdoctoral fellowship number JCI-2012-15047. M. Casas is supported by the Secretary for Universities and Research of the Ministry of Economy and Knowledge of the Government of Catalonia and the Cofund programme of the Marie Curie Actions of the 7th R&D Framework Programme of the European Union (Contract 2013 BP B 00243). I. Brumar has been partially supported by the Spanish Ministry of Education, Culture and Sports under grant FPU2015/12849.Peer ReviewedPostprint (author's final draft

    A formally verified compiler back-end

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    This article describes the development and formal verification (proof of semantic preservation) of a compiler back-end from Cminor (a simple imperative intermediate language) to PowerPC assembly code, using the Coq proof assistant both for programming the compiler and for proving its correctness. Such a verified compiler is useful in the context of formal methods applied to the certification of critical software: the verification of the compiler guarantees that the safety properties proved on the source code hold for the executable compiled code as well
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