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IEEE International Conference on Advanced Information Networking and Applications

作者： Jia-Chun Lin Fang-Yie Leu Ying-ping Chen Waqaas Munawar Department of Computer Science National Chiao Tung University Taiwan Department of Computer Science TungHai University Taiwan Department of Informatics Karlsruhe Institute of Technology Karlsruhe Germany

ISBN: (纸本)9781479936311

MapReduce has been a worldwide accepted framework for solving data-intensive applications. To prevent MapReduce jobs from being interrupted by node failures which occur frequently in a large-scale MapReduce cluster, current MapReduce implementations, e.g., Hadoop, employ a task reexecution policy (TR policy for short) for MapReduce jobs, i.e., when a map/reduce task of a job fails due to node failure, this policy reperforms the task on another node. However, the impact of the TR policy on job completion reliability and job completion time have not been studied from a theoretical viewpoint, especially when the job is given different characteristics, e.g., different input data sizes, different numbers of reduce tasks, and different intermediate data sizes. In this study, we derive the job completion reliability (JCR for short) of a MapReduce job based on Poisson distributions and analyze the expected job completion time (JCT for short) based on the universal generation function. We use nine settings of task re-execution factor (TR factor for short) to explore the impact of the TR policy on the JCR and JCT of jobs. The results show that the TR policy can effectively improve JCR without significantly prolonging JCT. But there is no single TR factor with which all jobs can achieve a high JCR.

关键词： MapReduce job completion reliability job completion time Poisson distribution universal generation function

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Recognition of Body Movements Patterns for Immersive Virtual Reality System Interface

Recognition of Body Movements Patterns for Immersive Virtual...

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International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC)

作者： Tomasz Hachaj Marek R. Ogiela Pedagogical University of Krakow Institute of Computer Science and Computer Methods Krakow Poland AGH University of Science and Technology Cryptography and Cognitive Informatics Research Group Krakow Poland

Our motivation for writing this paper was to present application of Gesture Description Language (GDL) methodology in the role of natural user interface (NUI) for immersive virtual reality (VR) environment. In order to do so we have adapted an existing so called voxel-engine framework by adding essential components. In order to apply NUI in VR environment we have implemented two types of interactions with the system: mouse - like two-dimensional point and click interface and movements commands that are used to travel through VR. The validation of our method was performed on group of twelve students of both sexes. Our experiment might be easily repeated by using our software modules.

关键词： Legged locomotion Pattern recognition Turning Games Virtual environments computers

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Segmental Mapping and Distance for Rooted Labeled Ordered Trees

Segmental Mapping and Distance for Rooted Labeled Ordered Tr...

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作者： Kan, Tomohiro Higuchi, Shoichi Hirata, Kouichi Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Kawazu 680-4 Iizuka820-8502 Japan Department of Artificial Intelligence and Biomedical Informatics RandD Center Kyushu Institute of Technology Kawazu 680-4 Iizuka820-8502 Japan Kyushu Electric Power Co. Inc. Japan Honest Kyushu Co. Ltd. Japan

In this paper, as variations of a Tai mapping between rooted labeled ordered trees (trees, for short), we introduce a segmental mapping to preserve the parent-children relationship as possible, and also top-down segmengal and bottom-up segmental mappings as the segmental mappings that contain the pair of the roots and the pair of the leaves, respectively. Then, we show that these mappings provide a new hierarchy for the variations of the Tai mapping in addition to a well-known one, in particular, the top-down segmental mapping coincides with a top-down mapping. Also we show that both segmental and bottom-up segmental distances as the minimum costs of segmental and bottom-up segmental mappings are metrics. Next, we design algorithms to compute the segmental and the bottom-up segmental distances in quadratic time and space. Finally, we give experimental results for the segmental distance.

关键词： Mapping

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Combined l1 and greedy l0 penalized least squares for linear model selection

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2015年第1期16卷

作者： Piotr Pokarowski Jan Mielniczuk Faculty of Mathematics Informatics and Mechanics University of Warsaw Warsaw Poland Faculty of Mathematics and Information Science Warsaw University of Technology Warsaw Poland and Institute of Computer Science Polish Academy of Sciences Warsaw Poland

We introduce a computationally effective algorithm for a linear model selection consisting of three steps: screening-ordering-selection (SOS). Screening of predictors is based on the thresholded Lasso that is l1 penalized least squares. The screened predictors are then fitted using least squares (LS) and ordered with respect to their |t| statistics. Finally, a model is selected using greedy generalized information criterion (GIC) that is l0 penalized LS in a nested family induced by the ordering. We give non-asymptotic upper bounds on error probability of each step of the SOS algorithm in terms of both penalties. Then we obtain selection consistency for different (n, p) scenarios under conditions which are needed for screening consistency of the Lasso. Our error bounds and numerical experiments show that SOS is worth considering alternative for multi-stage convex relaxation, the latest quasiconvex penalized LS. For the traditional setting (n > p) we give Sanov-type bounds on the error probabilities of the ordering-selection algorithm. It is surprising consequence of our bounds that the selection error of greedy GIC is asymptotically not larger than of exhaustive GIC.

关键词： generalized information criterion greedy search lasso linear model selection multi-stage convex relaxation penalized least squares

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A state level policy framework for integrating DFaaS with E-Governance

A state level policy framework for integrating DFaaS with E-...

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International Conference on Parallel Distributed and Grid Computing (PDGC)

作者： Saibal Sarkar Suvrojit Das West Bengal State Centre National Informatics Centre Kolkata India Department of Computer Application National Institute of Technology Durgapur India

This paper prescribes a digital forensic policy framework for a State to introduce Digital Forensics as a Service (DFaaS) as an integral part of e-Government services. DFaaS constitutes of investigating services for crimes committed upon and using electronic media. The policy framework proposes to establish a Centralized Digital Forensic Facility (CDFF) for enabling digital forensic services across all digital forensic units of a State. The basic objective of CDFF is to standardize, disseminate knowledge and reduce duplication of works related to DFaaS maintaining Confidentiality, Integrity and Authenticity of information. The core of the Policy aims to impose a few cost effective security mechanism on top of any infrastructure, be it a data centre or be it a cloud computing environment. Such mechanism enforces State specific forensic agents to be executed at specified levels of any public or private Infrastructure to facilitate forensic activities on the Infrastructure on demand and as per convenience.

关键词： Digital forensics Government Security Adaptation models Digital signal processing Grid computing

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Linear-Time FPT Algorithms via Network Flow 14

Linear-Time FPT Algorithms via Network Flow

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Annual ACM-Society for Industrial and Applied Mathmatics Symposium on Discrete Algorithms

作者： Yoichi Iwata Keigo Oka Yuichi Yoshida Department of Computer Science Graduate School of Information Science and Technology The University of Tokyo National Institute of Informatics and Preferred Infrastructure Inc.

ISBN: (纸本)9781611973389

In the area of parameterized complexity, to cope with NPHard problems, we introduce a parameter k besides the input size n, and we aim to design algorithms (called FPT algorithms) that run in O(f(k)n~d) time for some function f(k) and constant d. Though FPT algorithms have been successfully designed for many problems, typically they are not sufficiently fast because of huge f(k) and d. In this paper, we give FPT algorithms with small f(k) and d for many important problems including Odd Cycle Transversal and Almost 2-SAT. More specifically, we can choose f(k) as a single exponential (4k) and d as one, that is, linear in the input size. To the best of our knowledge, our algorithms achieve linear time complexity for the first time for these problems. To obtain our algorithms for these problems, we consider a large class of integer programs, called BIP2. Then we show that, in linear time, we can reduce BIP2 to Vertex Cover Above LP preserving the parameter k, and we can compute an optimal LP solution for Vertex Cover Above LP using network flow. Then, we perform an exhaustive search by fixing half-integral values in the optimal LP solution for Vertex Cover Above LP. A bottleneck here is that we need to recomputed an LP optimal solution after branching. To address this issue, we exploit network flow to update the optimal LP solution in linear time.

关键词： network flow foreign key algorithms optimal solution complexity classes vertex head corners

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A bi-objective optimization framework for heterogeneous CPU/GPU query plans

A bi-objective optimization framework for heterogeneous CPU/...

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作者： Przymus, Piotr Kaczmarski, Krzysztof Stencel, Krzysztof Faculty of Mathematics and Computer Science Nicolaus Copernicus University Chopina 12/18 Torun Poland Faculty of Mathematics and Information Science Warsaw University of Technology Koszykowa 75 Warszawa00-662 Poland Institute of Informatics Warsaw University Banacha 2 Warszawa02-097 Poland

Graphics Processing Units (GPU) have significantly more applications than just rendering images. They are also used in general-purpose computing to solve problems that can benefit from massive parallel processing. However, there are tasks that either hardly suit GPU or fit GPU only partially. The latter class is the focus of this paper. We elaborate on hybrid CPU/GPU computation and build optimization methods that seek the equilibrium between these two computation platforms. The method is based on heuristic search for bi-objective Pareto optimal execution plans in presence of multiple concurrent queries. The underlying model mimics the commodity market where devices are producers and queries are consumers. The value of resources of computing devices is controlled by supply-and-demand laws. Our model of the optimization criteria allows finding solutions of problems not yet addressed in heterogeneous query processing. Furthermore, it also offers lower time complexity and higher accuracy than other methods.

关键词： Graphics processing unit

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A nature-inspired hybrid Fuzzy C-means algorithm for better clustering of biological data sets

A nature-inspired hybrid Fuzzy C-means algorithm for better ...

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International Conference on Data Science & Engineering (ICDSE)

作者： T A Arunanand K A Abdul Nazeer Mathew J Palakal Meeta Pradhan Department of Computer Science and Engineering National Institute of Technology Calicut INDIA National Institute of Technology Calicut Calicut Kerala IN School of Informatics and Computing Indiana University Purdue University Indianapolis USA

Clustering is one of the widely used unsupervised methods to interpret and analyze huge amount of data in the field of Bioinformatics. One of the major issues involved in clustering is to address the growing data so that the cluster quality does not decrease with increase in the size of the data. In this work, we compare the promising clustering algorithms on various cancer domains and suggest improvements to them, with the help of a optimization techniques viz. Harmony Search (HS) algorithm. This paper discusses comparison of these techniques, various steps taken to achieve the target, and finally suggests an improved method that combines the merits of Fuzzy C-means algorithm and HS optimization technique.

关键词： Clustering algorithms Algorithm design and analysis Cancer Iris Linear programming Optimization Data mining

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Optimal signal processing method in UWB radar for hidden human detection

Optimal signal processing method in UWB radar for hidden hum...

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作者： Karamzadeh, Saeid Kartal, Mesut Kent, Sedef Ashtiyani, A. Abed Informatics Institute Department of Advanced Technology Satellite Communication and Remote Sensing Program Istanbul Technical University Turkey Department of Electronics and Communications Faculty of Electrical and Electronic Engineering Istanbul Technical University Turkey Faculty of Electric and Computer University of Tabriz Iran

Today, human detection and tracking is important challenge for many aims. In this study, we are used Ultra Wide Band (UWB) radar for human respiratory detection behind a wall. The modulated system to get the breathing signal is introduced. The results of simulation part of the established system are presented. Suitable antenna for using as a transmitter and receiver is being discussed. Different signal processing methods are debated and optimal method is introduced for various environments. © VDE VERLAG GMBH · Berlin · Offenbach, Germany.

关键词： Antennas

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Joint mode selection, MCS assignment, resource allocation and power control for D2D communication underlaying cellular networks

Joint mode selection, MCS assignment, resource allocation an...

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IEEE Conference on Wireless Communications and Networking

作者： Hao Zhou Yusheng Ji Jie Li Baohua Zhao School of Computer Science Univ. of Science and Technology of China Hefei Anhui China National Institute of Informatics Tokyo Japan School of Computer and Information Hefei Univ. of Technology Hefei Anhui China

ISBN: (纸本)9781479930845

Device-to-device (D2D) communication underlaying a cellular infrastructure has been proposed as a means of facilitating rich local services and offloading the base station traffic. However, D2D communication presents a challenge in radio resource management due to the potential interference it may cause to the cellular network. In this paper, the joint optimization problem of D2D mode selection, modulation and coding schemes (MCSs) assignment, radio resources and power allocation is formulated to minimize the overall power consumption under minimum required rate guarantee. The problem is decoupled into two sub-problems which are solved by Lagrangian relaxation and tabu search methods, respectively. Simulation results show its performance superiority over other schemes, especially in the scenarios with high required rate and limited resources.

关键词： Resource management Power demand Interference Algorithm design and analysis Power control Signal to noise ratio Downlink

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