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SKYPEER: Efficient Subspace Skyline Computation over distributed Data

SKYPEER: Efficient Subspace Skyline Computation over Distrib...

引用

international conference on Data Engineering

作者： Akrivi Vlachou Christos Doulkeridis Yannis Kotidis Michalis Vazirgiannis Department of Informatics Athens University of Economics and Business Athens Greece Gemo Team INRIA-FUTURS France

ISBN: (纸本)1424408024

Skyline query processing has received considerable attention in the recent past. Mainly, the skyline query is used to find a set of non dominated data points in a multidimensional dataset. While most previous work has assumed a centralized setting, in this paper we address the efficient computation of subspace skyline queries in large-scale peer-to-peer (P2P) networks, where the dataset is horizontally distributed across the peers. Relying on a super-peer architecture we propose a threshold based algorithm, called SKYPEER, which forwards the skyline query requests among peers, in such a way that the amount of transferred data is significantly reduced. For efficient subspace skyline processing, we extend the notion of domination by defining the extended skyline set, which contains all data elements that are necessary to answer a skyline query in any arbitrary subspace. We prove that our algorithm provides the exact answers and we present optimization techniques to reduce communication cost and execution time. Finally, we provide an extensive experimental evaluation showing that SKYPEER performs efficiently and provides a viable solution when a large degree of distribution is required.

关键词： distributed computing Computer networks Peer to peer computing Computer architecture File servers Information systems Network servers Power system modeling Large-scale systems Informatics

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Real-Time Traffic Sign Detection for Self-Driving and Energy-Saving Driving Based on YOLOv4 Neural Network

Real-Time Traffic Sign Detection for Self-Driving and Energy...

引用

ACIS international conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/distributed computing (SNPD)

作者： Chi-Chun Chen Yuan-Hong Guan Nabila Rizqia Novianda Chung-Chen Teng Meng-Hua Yen Dept. of Electronic Engineering National Chin-Yi University of Technology Taichung Taiwan Master of Electronic Engineering National Chin-Yi University of Technology Taichung Taiwan

With the booming development of autonomous vehicles (AV) in recent years, a vehicle needs to have the ability to detect changes in the environment in real-time. If the vehicle can be decelerated in advance according to the traffic signs, it can effectively reduce fuel consumption and improve overall comfort. This paper uses the Kaggle data set for training based on marking the common traffic signs in foreign countries, adds the local data set in Taiwan to the testing data set, and uses the You Only Look Once v4 (YOLOv4) neural network to detect the traffic signs in real time. The experimental results show that YOLOv4 still has a good generalization ability in the case of slight differences in different national sign types, and the mean Average Precision (mAP) can reach more than 87.6%.

关键词： Training Neural networks Real-time systems Fuels Artificial intelligence Autonomous vehicles Testing

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The Glasgow Raspberry Pi Cloud: A Scale Model for Cloud computing Infrastructures

The Glasgow Raspberry Pi Cloud: A Scale Model for Cloud Comp...

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international conference on distributed computing systems Workshop

作者： Fung Po Tso David R. White Simon Jouet Jeremy Singer Dimitrios P. Pezaros School of Computing Science University of Glasgow UK

Data Centers (DC) used to support Cloud services often consist of tens of thousands of networked machines under a single roof. The significant capital outlay required to replicate such infrastructures constitutes a major obstacle to practical implementation and evaluation of research in this domain. Currently, most research into Cloud computing relies on either limited software simulation, or the use of a testbed environments with a handful of machines. The recent introduction of the Raspberry Pi, a low-cost, low-power single-board computer, has made the construction of a miniature Cloud DCs more affordable. In this paper, we present the Glasgow Raspberry Pi Cloud (PiCloud), a scale model of a DC composed of clusters of Raspberry Pi devices. The PiCloud emulates every layer of a Cloud stack, ranging from resource virtualisation to network behaviour, providing a full-featured Cloud computing research and educational environment.

关键词： Computational modeling Cloud computing Servers Containers Computer architecture Linux

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Multimedia Streams Retrieval in distributed systems Using Learning Automata

Multimedia Streams Retrieval in Distributed Systems Using Le...

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3rd international conference on Networked Digital Technologies (NDT 2011)

作者： Ghasemi, Safiye Rahmani, Amir Masoud Islamic Azad Univ Dept Comp Sepidan Branch Sepidan Iran Islamic Azad Univ Sci & Res Branch Tehran Iran

ISBN: (纸本)9783642221842

Current academic Internet environment has enabled fast transfers of huge amounts of data, and has made high quality multimedia and collaborative applications a reality. This article describes a model for distributed multimedia retrieval which performs the retrieval of different multimedia to a variety of clients using learning automata algorithm named LAGridMSS. LAGridMSS allocates a proportion of bandwidth of each node for sending a specified file, and then applies learning automata to allocate packets of files to each node that contains the context. The files' popularity and the remainder bandwidth of nodes are two main factors here for allocating packets to each node. Simulation results show improvements in proposed model. LAGridMSS, in some QoS factors such as delay, jitter, and reliability compared to previous multimedia retrieval system such as GridMSS and GridMedia.

关键词： Grid computing Environment Streaming Files Learning Automata Quality of Service

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Workflow Technology for Drug Discovery

Workflow Technology for Drug Discovery

引用

international conference on Grid and Pervasive computing workshops, GPC

作者： Liangying Luo Ruisheng Zhang Chunyan Zhang Xiaoliang Fan Lian Li Engineering Research Center of Open Source Software and Real-time Systems Ministry of Education Department of Information Science and Engineering Lanzhou University Lanzhou Gansu China

Grid computing can integrate huge services and resources across distributed, heterogeneous, dynamic virtual organizations, and provide tremendous computing power in parallel. Workflow technology enables the user to compose complex Grid applications on distributed heterogeneous and unreliable hardware resources without taking care of lower level details. The drug discovery process almost comprises a number of sub processes, in which various software to be invoked, complex computing and huge amounts of data analyze are involved. Scientific workflow is the process of combining data and processes into a configurable, structured set of steps that implement semi-automated. distributed processing and parallel computing capacity can improve the Computational efficiency. Therefore, the problems in drug discovery can be solved using the workflow technology. This paper discusses the problem on drug discovery process and presents how to utilize workflow in our eSOC System to resolve the three most important issues in drug discovery.

关键词： Pharmaceutical technology Drugs Grid computing Concurrent computing distributed computing Application software Hardware Data analysis distributed processing Parallel processing

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Optimizing State-Intensive Non-Blocking Queries Using Run-time Adaptation

Optimizing State-Intensive Non-Blocking Queries Using Run-ti...

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international conference on Data Engineering workshops

作者： Bin Liu Mariana Jbantova Elke A. Rundensteiner Worcester Polytechnic Institute Worcester MA USA

Main memory is a critical resource when processing non-blocking queries with state intensive operators that require real-time responses. While partitioned parallel processing can alleviate the stringent memory demands in some cases, in general even in a distributed system main memory remains bounded. In this work, we thus investigate the integration of two run-time adaptation techniques, namely, state spill to disk and state relocation to an alternate machine, to handle this memory shortage problem. We analyze the tradeoffs regarding key factors affecting these two run-lime operator state adaptation techniques in a modern compute-cluster environment. Two strategics, lazy-disk and active-disk, are then proposed that integrate both state spill and state relocation adaptations with different emphasis on local versus global decision making. Extensive experiments of the proposed query processing system conducted on a compute-cluster (not merely a simulation) confirm the effectiveness of these strategies.

关键词： Exchange rates Query processing Real time systems Decision support systems Remote monitoring Parallel processing Runtime environment Decision making Computational modeling Intrusion detection

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An Edge-Focused Model for distributed Streaming Data Applications

An Edge-Focused Model for Distributed Streaming Data Applica...

引用

IEEE international conference on Pervasive computing and Communications

作者： V. K. Cody Bumgardner Caylin Hickey Victor W. Marek Department of Pathology and Laboratory Medicine University of Kentucky Lexington Kentucky USA Department of Computer Science University of Kentucky Lexington Lexington Kentucky USA

ISBN: (纸本)9781538632284

This paper presents techniques for the description and management of distributed streaming data applications. The proposed solution provides an abstract description language and operational graph model for supporting collections of autonomous components functioning as distributed systems. Using our approach, applications supporting millions of devices can be easily modeled using abstract configurations. Through our models applications can implemented and managed through socalled server-less application orchestration.

关键词： Pipelines Data models Big Data applications Cloud computing Computational modeling conferences Program processors Program processors data models pipeline Computational modeling Cloud computing Big data applications piping Streaming language description Graphical models distributed systems

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FedQL: A framework for federated queries processing on rdF stream and relational data 23rd

FedQL: A framework for federated queries processing on RDF s...

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23rd international conference on Database systems for Advanced Applications, DASFAA 2018

作者： Rao, Guozheng Zhao, Bo Zhang, Xiaowang Feng, Zhiyong School of Computer Science and Technology Tianjin University Tianjin300350 China School of Computer Software Tianjin University Tianjin300350 China Tianjin Key Laboratory of Cognitive Computing and Application Tianjin300350 China

ISBN: (纸本)9783319914541

In this paper, we present a framework (FedQL) for processing rdF stream and relational data in a federal way. Firstly, we introduce a formalization of our federated query language by conjunction of continuous queries and SQL queries. Secondly, we present a white-box-based framework to separate query processing from query executing. The framework mainly includes three modules, namely, Query processor, Data transformer, and SPARQL query execution. Finally, we implement FedQL built on C-SPARQL and MySQL by employing three centralized SPARQL engines (e.g. Jena, rdF-3X, and gStore) and one distributed SPARQL engine (e.g. TriAD) in an adaptive way and evaluate FedQL on a real-world dataset. The experimental results show that FedQL is efficient and effective in processing rdF stream and relational data in a federal way. © Springer international Publishing AG, part of Springer Nature 2018.

关键词： Engines

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IP Operations and Management 1

引用

丛书名： Lecture Notes in Computer Science

1000年

ISBN: (数字)9783540758532

ISBN: (纸本)9783540758525

On behalf of the IEEE Communications Society, the Technical Committee on Network Operations and Management (CNOM), the Manweek 2007 Organizing Committee, and the members of the IPOM Technical Program Committee, it is our pleasure to present the proceedings of the Seventh IEEE Workshop on IP Operations and Management (IPOM2007), held as part of Manweek 2007 during October 31-November 2, 2007. With the widespread deployment of IP-based networks, their operations and management have become increasingly important in terms of understanding emerging technical and scientific problems; lessons from such understanding are particularly important for future Internet design and management. Like the previous IPOM workshops, IPOM 2007 was co-located with several related events as part of the 3rd international Week on Management of Networks and Services (Manweek 2007). The other events were the 10th IFIP/IEEE international conference on Management of Multimedia and Mobile Networks and Services (MMNS 2007), the 18th IFIP/IEEE international Workshop on distributed systems: Operations and Management (DSOM 2007), the 2ndIEEE international Workshop on Modeling Autonomic Communications Environments (MACE 2007), and the 1st IEEE/IFIP international Workshop on End-to-End Virtualization and Grid Management (EVGM 2007). Co-locating those events provided the opportunity for an exchange of ideas between research communities that work on related topics, allowing participants to forge links and exploit synergies.

关键词： Computer Communication Networks Information systems Applications (incl. Internet) Management of computing and Information systems Multimedia Information systems Information Storage and Retrieval Communications Engineering, Networks

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Regional Congestion Control in Datacenter Networks

Regional Congestion Control in Datacenter Networks

引用

international conference on Parallel and distributed systems (ICPADS)

作者： Fan Yang Zhan Wang Xiaoli Liu Zheng Cao Guojun Yuan Xuejun An Universiry of Chinese Academy of Sciences Beijing China Institute of Computing Technology Chinese Academy of Sciences

ISBN: (纸本)9781538632086

The rapid deployment of cloud computing and online services poses great challenges for data center networks, and congestion control is one of the top concerns. Although numbers of proposals in different network layers have been put forward to alleviate the negative impact of congestion, the short-lived flows, which are latency-sensitive and constitute the majority of total traffic in data centers, still suffer severe performance degradation. Since the existing congestion control methods all rely on end hosts to perceive congestion and then adjust their network sending rate, the response time is relatively long when compared with the duration of short-lived flows, which increases latency significantly. In this paper, we propose RCC, a regional congestion control mechanism, which aims to respond to congestion more quickly and eliminate the mismatch mentioned above. Different from host-based mechanisms, RCC is implemented in the switch, which detects the congestion state and schedule the traffic around the congestion point locally, without sending feedback to the distal host. Evaluation has shown that, compared with the host-based mechanism, our method achieves better performance for short-lived flows and maintains stable buffer occupancy of the switch. In addition, mixed long- and short-lived flows which contend for the same bottleneck link can share the bandwidth more fairly.

关键词： conferences

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