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On convergence of a distributed cooperative spectrum sensing procedure in cognitive radio networks 1

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11th international conference on Cognitive Radio Oriented Wireless Networks, CROWNCOM 2016

作者： Ermolova, Natalia Y. Tirkkonen, Olav Aalto University Aalto00076 Finland

ISBN: (数字)9783319403526

ISBN: (纸本)9783319403519

In this work, we analyze a distributed cooperative spectrum sensing scheme where N secondary users (SUs) of a cognitive wireless network try to agree about the primary user presence (absence) by iterative interchanging individual opinions (states) over an unreliable wireless propagation medium. It is assumed that the SUs update their personal states based on the "K-out-of-N" rule, and the interchange session fails, if the consensus has not been reached within a fixed number of iterations. the problem of forming a joint opinion becomes challenging because a SU makes its personal decision based on local observations distorted by a wireless propagation medium. this fact may cause a disorder. In this paper, we formulate sufficient conditions of reaching the agreement on the basis of local observations. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2016.

关键词： Wireless networks

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Supr: Adaptive Byzantine Fault-Tolerant Replication 11th

Supr: Adaptive Byzantine Fault-Tolerant Replication

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11th international conference on Dependability and Complex Systems (DepCoS-RELCOMEX)

作者： Zbierski, Maciej Warsaw Univ Technol Inst Comp Sci Warsaw Poland

ISBN: (纸本)9783319396392;9783319396385

In the last decade, numerous Byzantine fault-tolerant (BFT) replication protocols have been proposed in the literature. However, practically all of these solutions were designed and optimized only for certain, typically very limited set of environment conditions. Despite previous efforts, no existing BFT replication protocol can guarantee stable and reasonable performance in both correct and faulty environments. In this article we attempt to address this problem by introducing Supr, a novel method for effortlessly combining multiple replication protocols into adaptive BFT solutions, which accommodate to a much wider spectrum of environment conditions than the existing BFT systems. Unlike previous approaches, Supr uses a fine-grained mechanism to monitor the parameters of the execution environment, which enables detecting and counteracting arbitrary faults exhibited in the system. To demonstrate its potential, we use Supr to create a sample BFT solution combining three existing replication protocols, each optimized for different conditions. the performed experiments demonstrate that our approach not only significantly outperforms existing solutions in varying environment conditions, but also does not introduce an observable overhead in stable environments.

关键词： Byzantine fault tolerance State machine replication Adaptive BFT distributed systems Dependability

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RBAS: A real-Time user behavior analysis system for Internet TV in cloud computing 16

RBAS: A real-Time user behavior analysis system for Internet...

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11th international conference on Future Internet Technologies, CFI 2016

作者： Zhu, Chengang Cheng, Guang Guo, Xiaojun Wang, Yuxiang School of Computer Science and Engineering Key Laboratory of Computer Network and Information Integration Ministry of Education Southeast University Nanjing211189 China

ISBN: (纸本)9781450341813

the characteristic of Internet TV user behavior is quite essential for designers to optimize resource schedule and improve user experience. With the rapid development of Internet, both Internet TV users and STB (set top boxes) models are booming. this brings a large amount of behavior data which requires matching computing and storage resource to process. therefore, scalable Internet TV user behavior analysis becomes more difficult. As a solution, cloud computing framework such as Hive is emerged. But limited by performance, it's not an appropriate choice for interactive analysis or real-Time data exploration. In this paper, we present a real-Time Internet TV user behavior analysis system with advantages of high concurrency, low latency and good transportability. Firstly, we design an event capture scheme, consisted of agents embedded in STBs and capture server clusters, to capture every manipulation performed by users. Secondly, we develop a SQL-on-Hadoop engine with distributed transactional management to decrease the response time. the engine has excellent query performance and ability to interactively query various data sources in different Hadoop formats. Lastly, we evaluate RBAS in a commercial Internet TV platform of 16 million registered users. the results show that, with a 32-node cluster, the system can effectively process 10.2 TB of behavior data every day, which is about 40x faster than original Hive-based system. © Copyright 2016 ACM.

关键词： Cloud computing

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the Performance Evaluation of the Java Implementation of Graph500 11th

The Performance Evaluation of the Java Implementation of Gra...

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11th international conference on Parallel Processing and Applied Mathematics (PPAM)

作者： Ryczkowska, Magdalena Nowicki, Marek Bala, Piotr Nicolaus Copernicus Univ Fac Math & Comp Sci Chopina 12-18 PL-87100 Torun Poland Univ Warsaw Interdisciplinary Ctr Math & Computat Modeling Pawinskiego 5a PL-02106 Warsaw Poland

ISBN: (纸本)9783319321523;9783319321516

Graph-based computations are used in many applications. Increasing size of analyzed data and its complexity make graph analysis a challenging task. In this paper we present performance evaluation of Java implementation of Graph500 benchmark. It has been developed with the help of the PCJ (Parallel Computations in Java) library for parallel and distributed computations in Java. PCJ is based on a PGAS (Partitioned Global Address Space) programming paradigm, where all communication details such as threads or network programming are hidden. In this paper, we present Java implementation details of first and second kernel from Graph500 benchmark. the results are compared with the existing MPI implementations of Graph500 benchmark, showing good scalability of PCJ library.

关键词： High performance computing Graph processing PGAS Parallel and distributed computation Performance evaluation Parallel graph algorithms Java

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Soft cache hits and the impact of alternative content recommendations on mobile edge caching 11

Soft cache hits and the impact of alternative content recomm...

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11th ACM Workshop on Challenged Networks, CHANTS 2016

作者： Spyropoulos, thrasyvoulos Sermpezis, Pavlos Dept. Mobile Communications EURECOM France Institute of Computer Science FORTH Greece

ISBN: (纸本)9781450342568

Caching popular content at the edge of future mobile networks has been widely considered in order to alleviate the impact of the data tsunami on both the access and backhaul networks. A number of interesting techniques have been proposed, including femto-caching and "delayed" or opportunistic cache access. Nevertheless, the majority of these approaches suffer from the rather limited storage capacity of the edge caches, compared to the tremendous and rapidly increasing size of the Internet content catalog. We propose to depart from the assumption of hard cache misses, common in most existing works, and consider "soft" cache misses, where if the original content is not available, an alternative content that is locally cached can be recommended. Given that Internet content consumption is increasingly entertainment-oriented, we believe that a related content could often lead to complete or at least partial user satisfaction, without the need to retrieve the original content over expensive links. In this paper, we formulate the problem of optimal edge caching with soft cache hits, in the context of delayed access, and analyze the expected gains. We then show using synthetic and real datasets of related video contents that promising caching gains could be achieved in practice. © 2016 ACM.

关键词： Mobile edge computing

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Sentiment Analysis Based on Support Vector Machine and Big Data 39

Sentiment Analysis Based on Support Vector Machine and Big D...

引用

39th international conference on Telecommunications and Signal Processing (TSP)

作者： Povoda, Lukas Burget, Radim Dutta, Malay Kishore Brno Univ Technol Dept Telecommun Brno Czech Republic Amity Univ Amity Sch Engn & Technol Noida Uttar Pradesh India

ISBN: (纸本)9781509012886

this paper deals with sentiment analysis in text documents, especially text valence detection. the proposed solution is based on Support Vector Machines classifier. this classifier was trained with huge amount of data and complex word combinations were analysed. For this purpose distributed learning on 112 processors was used. Datasets used for training and testing were automatically obtained from real user feedback on products from different web pages (and different product segments). the proposed solution has been evaluated with different languages - English, German, Czech and Spanish. this paper improves accuracy achieved with the Big Data approach about 11%. the best accuracy achieved in this work was 95.31% for recognition of positive and negative text valence. the described learning is fully automatic, can be applied to any language and no complicated preprocessing is needed.

关键词： text valence classification emotion recognition text mining cluster computing

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Parallelization and Optimization of a CAD Model Processing Tool from the Automotive Industry to distributed Memory Parallel Computers 11th

Parallelization and Optimization of a CAD Model Processing T...

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11th international conference on Parallel Processing and Applied Mathematics (PPAM)

作者： Ayuso, Luis Durillo, Juan J. Kornberger, Bernhard Schifko, Martin Fahringer, thomas Univ Innsbruck Inst Comp Sci Innsbruck Austria Geom Softwareentwicklung Graz Austria ESS Engn Software Steyr GmbH Munich Germany

ISBN: (纸本)9783319321493;9783319321486

In the early phases of an automotive industry development, design time can be substantially improved by using automated tools that assist engineers to perform repetitive and time consuming tasks, speeding up automotive products development and providing quality guarantees over otherwise error-prone processes. MERGE is such a tool from industry that prepares CAD models for electrophoretic deposition simulation. In this paper we describe the parallelization and optimization of MERGE for distributed memory parallel architectures. For this purpose we create a dynamic tree of tasks at runtime, analyze its load behavior and execute it through a master-worker compute paradigm based on different scheduling policies. Our implementation is based on a hybrid MPI-OpenMP version which results in a considerable improvement of both resource utilization and performance. Empirical performance results are presented for our new approach which achieve a speedup of up to 18 on an SMP cluster architecture.

关键词： distributed memory architecture MPI-OpenMP CAD Intree precedence Task scheduling

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Aggregate interference in random CSMA/CA networks 1

引用

11th international conference on Cognitive Radio Oriented Wireless Networks, CROWNCOM 2016

作者： Hwang, June Choi, Jinho Jäntti, Riku Kim, Seong-Lyun Samsung Electronics Mobile Communications Business Suwon Korea Republic of Department of Electrical and Electronic Engineering Yonsei University 50 Yonsei-Ro Seoul Korea Republic of Department of Communications and Networking School of Electrical Engineering Aalto University Aalto00076 Finland

ISBN: (数字)9783319403526

ISBN: (纸本)9783319403519

In this paper, we investigate the cumulative distribution function (CDF) of the aggregate interference in CSMA/CA networks measured at an arbitrary time and position. We assume that nodes are deployed in an infinite two-dimensional plane by the Poisson point process (PPP). To find the effective active node density we analyze the distributed coordinate function (DCF) dynamics in a common sensing area and obtain the steady-state power distribution. the results of a massive simulation using Network Simulator-2 (NS-2) show a high correlation with the derived CDF. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2016.

关键词： Distribution functions

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Biomimicry of plant root foraging for distributed optimization: Models and emergent behaviors 11th

Biomimicry of plant root foraging for distributed optimizati...

引用

11th international conference on Bio-inspired computing – theories and Applications, BIC-TA 2016

作者： Chen, Hanning Liang, Xiaodan He, Maowei Su, Weixing Tianjin Polytechnic University Tianjin300160 China

ISBN: (纸本)9789811036132

Terrestrial plants have evolved remarkable adaptability that enables them to sense environmental stimuli and use this information as a basis for governing their growth orientation and root system development. In this paper, we explain the foraging behaviors of plant root and develop simulation models based on the principles of adaptation processes that view root growing as optimization. this provides us with novel models of plant root foraging behavior and with new methods for global optimization. this model is instantiated as a novel bio-inspired optimization model, which adopts the root foraging, memory and communication, and auxin-regulated mechanisms of the root *** perform comprehensive simulation to demonstrate that the proposed model exhibit the property identified by natural plant root system. that is, in order to be able to climb noisy gradients in nutrients in soil, the foraging behaviors of root system is social and cooperative that is analogous to animal foraging behaviors. © Springer Nature Singapore Pte Ltd. 2016.

关键词： Global optimization

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iGEMS: A Cloud Green Energy Management System in Data Center 11th

iGEMS: A Cloud Green Energy Management System in Data Center

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11th international conference on Green, Pervasive and Cloud computing (GPC)

作者： Yang, Chao-Tung Yan, Yin-Zhen Chen, Shuo-Tsung Liu, Ren-Hao Ou, Jean-Huei Chen, Kun-Liang Tunghai Univ Dept Comp Sci Taichung 40704 Taiwan Tunghai Univ Ctr Comp Taichung 40704 Taiwan

ISBN: (纸本)9783319390772;9783319390765

Today the growing demand for reducing the power is not limited to household electricity saving. For businesses, it is the more important issue to effectively reduce the cost of electricity and the excess consumption under the huge electricity. In order to achieve energy saving and energy requires, the development of energy monitoring systems to obtain information related to consumption is necessary. Accordingly, this work proposes a cloud green energy management system. Because of the data size and the computational efficiency of data analysis, we add the big data technology and cloud computing to upgrade the system performance. By building cloud infrastructure and distributed storage cluster, we adopt the open source, Hadoop, to implement the two main functions: storage and computation. Based on these two functions, the proposed system speeds up the analysis and processing of big data by using Hadoop MapReduce to access HBase. the systemic risk is thus reduced too. Both real-time data and historical data are analyzed to obtain electricity consumption behavior for real-time warning and early warning. Moreover, carbon reduction and environmental protection are also considered in the analysis. Finally, a virtualized user-interface is designed to show the proposed system functions and analysis results. the experimental results indicate the performance of the proposed system.

关键词： Cloud computing Power management Energy saving Big Data Hadoop MapReduce

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