检索结果-内蒙古大学图书馆

25th IEEE International Conference on parallel and distributed systems (IEEE ICPADS)

作者： Wang, Lin Zhang, Qingyang Li, Youhuizi Zhong, Hong Shi, Weisong Anhui Univ Sch Comp Sci & Technol Hefei 230601 Peoples R China Hangzhou Dianzi Univ Key Lab Complex Syst Modeling & Simulat Hangzhou Peoples R China Wayne State Univ Dept Comp Sci Detroit MI 48202 USA

ISBN: (纸本)9781728125831

As the rapid growth of connected and autonomous vehicles (CAVs) and 5G intensifies, more third-party applications are increasingly being deployed on CAVs. They not only improve user experience but also provide more helpful services, for example, enhancing public safety by recognizing criminals in real-time videos. Current CAVs prefer to process collected data on the vehicle to avoid long transmission latency and extra network cost. However, due to the limitations of the on-board vehicle computing unit (VCU) and increasing use of computing-intensive in-vehicle applications, the burden of on-board VCU has sharply increased, which may affect driving safety. In particular, for existing vehicles on the road, adding more computing devices is a challenge if not impossible due to cost concerns. Inspired by edge computing, we propose a novel platform, MobileEdge, to enhance the computing capability of the unchangeable on-board VCU, which leverages mobile devices as edge nodes, e.g., the passengers' smartphones, by offloading computing tasks to them for collaboratively computing. Moreover, MobileEdge provides the dynamic management of mobile devices, monitoring device status and interfaces for customizable task offloading strategies and eventually achieves optimal task scheduling. We build a prototype to demonstrate the designed platform and evaluate three task offloading strategies which were implemented based on the developed interfaces. The results show that MobileEdge significantly reduces the application response latency. Compared with the baseline which does not employ task offloading, the response latency is almost near real-time when more computing resources are available. In addition, the proposed shortest response latency strategy outperforms the best overall task scheduling among the three strategies.

关键词： edge computing vehicular data analysis distributed computing connected and autonomous vehicles

来源：评论

学校读者我要写书评

暂无评论

Run-time Performance Monitoring, Verification, and Healing of End-to-End Services 5

Run-time Performance Monitoring, Verification, and Healing o...

引用

5th IEEE Conference on Network Softwarization (IEEE NetSoft) / 2nd International workshop on Advances in Slicing for Softwarized Infrastructures (S4SI)

作者： Choi, Nakjung Jagadeesan, Lalita Kim, Young Jin Mohanasamy, Nishok Narasimha Rahman, Muntasir Raihan Sabnani, Krishan Thottan, Marina Nokia Bell Labs Murray Hill NJ 07974 USA

ISBN: (纸本)9781538693766

Softwarization enables tremendous flexibility for networks as the use of software-defined networking (SDN) and programmable data planes (e.g. P4) together support dynamic reconfiguration of networks in real-time, in response to network conditions and new service requests. In such networks, it is imperative to ensure that end-to-end network services continue to satisfy SLAs, especially performance requirements. However, in the presence of unpredictable dynamics due to network reconfigurations, it is not possible to guarantee prior to deployment that a service will meet such SLAs. Run-time verification - in combination with programmable control and data plane monitoring - can provide a basis for detecting potential performance SLA violations, together with identifying and executing appropriate network mitigations. In this paper, we propose a verification transverse based on formal specifications, that spans performance SLAs across the distributed SDN control and programmable data planes, and can coordinate with both planes to execute dynamic reconfiguration that mitigate the detected issues. We demonstrate a proof-of-concept prototype based on an extension of the Aerial run-time verification tool, together with the Inband Network Telemetry (INT) capability, on a network running distributed ONOS controllers together with a P4 data plane.

关键词： Monitoring real-time systems distributed databases Voting Tools Telemetry Streaming media distributed databases Streaming Video Vote real-time systems telemetry plane Network dynamic reconfiguration Wound Healing Network reconfiguration Programmable control runtime performance Verification end-to-end Formal specifications

来源：评论

学校读者我要写书评

暂无评论

real-time testbed for validating distributed antenna scenarios 20

Real-time testbed for validating distributed antenna scenari...

引用

20th International ITG workshop on Smart Antennas, WSA 2016

作者： Peethala, Sundar Daniel V. Kreul, Theo Kaiser, Thomas Institut für Digitale Signalverarbeitung Universität Duisburg-Essen Duisburg47057 Germany

ISBN: (纸本)9783800741779

distributed Antenna systems (DAS) promise to deliver solutions for the future wireless challenges using multiple remote radio heads (RRHs) in a distributed architecture, thereby supporting high frequency re-use, increased coverage, decreasing interference and latency. DAS architecture consists of multiple RRHs connected to a centralized base station via an optical fiber network. This work explains different DAS deployment techniques on a real-time LTE system. It focuses on the implementation details of LTE PHY on a TI (Texas Instruments) DSP and corresponding processing blocks that need to be adapted to support the functionality of DAS. Different DAS use case scenarios of deployment, their advantages and key performance indicators, are analyzed. This work also includes the measurement results of deploying antenna selection scenario to investigate and validate DAS on a real-time LTE system. © VDE VERLAG GMBH · Berlin · Offenbach, Germany.

关键词： Digital signal processing

来源：评论

学校读者我要写书评

暂无评论

Multi-Stage distributed Computing for Big Data: Evaluating Connective Topologies

Multi-Stage Distributed Computing for Big Data: Evaluating C...

引用

IEEE Annual Computing and Communication workshop and Conference (CCWC)

作者： Rasha S. Gargees Grant J. Scott University of Missouri Columbia Mo USA

ISBN: (数字)9781728137834

ISBN: (纸本)9781728137841

With the increase in computation and data intensive needs along with the real-time requirements in the big data era, a distributed framework that can handle parallel processing at various levels becomes a necessity. In this paper, we propose a multi-stage framework that leverages distributed computational agents to handle large-scaled data in parallel. The computational agents are distributed both in breadth (parallelism) and depth (various stages) to pursue the scalability, parallelism, and heterogeneity of modern computational big data workflows. Additionally, the proposed framework allows the interleaving of computation among the stages to speed up the processing. This high throughput computing (HTC) framework is resource efficient, depth and breadth scalable, and supports both distributed agents and centralized analytics. Herein, three computational agent sequential-stage connection topologies are investigated: fully connected, partition, and mesh connectivity. To evaluate the performance of the proposed framework, a large-scale, remote sensing imagery data deep feature extraction and clustering application has been adapted as a use case. Various experiments show that the internal performances of the framework based on the queue size varies according to the type of the topology. While the total time of the experiments are affected mostly by the number of agents in each stage as expected. Additionally, it has been observed that the setup of the partition topology affects the time as well. The system is shown to maintain its resource efficient HTC performance under all the connection topologies, wherein measurement metrics, such as the average CPU usage and average memory usage, reveal nearly the same performance for all the topologies except the partitioning topology.

关键词： Topology Computer architecture Feature extraction Metadata Big Data Task analysis distributed databases

来源：评论

学校读者我要写书评

暂无评论

Efficient Data Placement and Replication for QoS-Aware Approximate Query Evaluation of Big Data Analytics

引用

IEEE TRANSACTIONS ON parallel AND distributed systems 2019年第12期30卷 2677-2691页

作者： Xia, Qiufen Xu, Zichuan Liang, Weifa Yu, Shui Guo, Song Zomaya, Albert Y. Dalian Univ Technol Key Lab Ubiquitous Network & Serv Software Liaoni Int Sch Informat Sci & Engn Dalian 116024 Liaoning Peoples R China Dalian Univ Technol Sch Software Dalian 116024 Liaoning Peoples R China Australian Natl Univ Res Sch Comp Sci Canberra ACT 2601 Australia Univ Technol Sydney Sch Software Ultimo NSW 2007 Australia Hong Kong Polytech Univ Dept Comp Hung Hom Hong Kong Peoples R China Univ Sydney Sch Comp Sci Camperdown NSW 2006 Australia

Enterprise users at different geographic locations generate large-volume data that is stored at different geographic datacenters. These users may also perform big data analytics on the stored data to identify valuable information in order to make strategic decisions. However, it is well known that performing big data analytics on data in geographical-located datacenters usually is time-consuming and costly. In some delay-sensitive applications, the query result may become useless if answering a query takes too long time. Instead, sometimes users may only be interested in timely approximate rather than exact query results. When such approximate query evaluation is the case, applications must sacrifice timeliness to get more accurate evaluation results or tolerate evaluation result with a guaranteed error bound obtained from analyzing the samples of the data to meet their stringent timeline. In this paper, we study quality-of-service (QoS)-aware data replication and placement for approximate query evaluation of big data analytics in a distributed cloud, where the original (source) data of a query is distributed at different geo-distributed datacenters. We focus on the problems of placing data samples of the source data at some strategic datacenters to meet stringent query delay requirements of users, by exploring a non-trivial trade-off between the cost of query evaluation and the error bound of the evaluation result. We first propose an approximation algorithm with a provable approximation ratio for a single approximate query. We then develop an efficient heuristic algorithm for evaluating a set of approximate queries with the aim to minimize the evaluation cost while meeting the delay requirements of these queries. We finally demonstrate the effectiveness and efficiency of the proposed algorithms through both experimental simulations and implementations in a real test-bed, real datasets are employed. Experimental results show that the proposed algorithms are promisi

关键词： Big Data Query processing Delays Approximation algorithms Quality of service distributed databases Software Data replication and placement big data analytics approximate query evaluation approximation algorithms algorithm analysis

来源：评论

学校读者我要写书评

暂无评论

9th International workshop on Business Intelligence for the real-time Enterprise, BIRTE 2015, 10th International workshop on Enabling real-time Business Intelligence, BIRTE 2016 and 11th International workshop on real-time Business Intelligence and Analytics, BIRTE 2017 held in conjunction with the International Conference on Very Large Data Bases, VLDB 2017

9th International Workshop on Business Intelligence for the ...

引用

9th International workshop on Business Intelligence for the real-time Enterprise, BIRTE 2015, 10th International workshop on Enabling real-time Business Intelligence, BIRTE 2016 and 11th International workshop on real-time Business Intelligence and Analytics, BIRTE 2017 held in conjunction with the International Conference on Very Large Data Bases, VLDB 2017

ISBN: (纸本)9783030241230

The proceedings contain 13 papers. The special focus in this conference is on International workshop on Business Intelligence for the real-time Enterprise, International workshop on Enabling real-time Business Intelligence, and International workshop on real-time Business Intelligence and Analytics, held in conjunction with the International Conference on Very Large Data Bases. The topics include: Towards Interactive Data Exploration;DCS: A Policy Framework for the Detection of Correlated Data Streams;towards Dynamic Data Placement for Polystore Ingestion;a Federated In-memory Database System for Life Sciences;an Integrated Architecture for real-time and Historical Analytics in Financial Services;processing of Aggregate Continuous Queries in a distributed Environment;high-Availability at Massive Scale: Building Google’s Data Infrastructure for Ads;past and Future Steps for Adaptive Storage Data systems: From Shallow to Deep Adaptivity;polyRecs: Improving Page–View Rates Using real-time Data Analysis;Enabling real time Analytics over Raw XML Data;Multi-engine Analytics with IReS.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Large-scale stochastic topology optimization using adaptive mesh refinement and coarsening through a two-level parallelization scheme

引用

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 2019年 343卷 186-206页

作者： Baiges, Joan Martinez-Frutos, Jesus Herrero-Perez, David Otero, Fermin Ferrer, Alex Univ Politecn Cataluna Jordi Girona 1-3Edif C1 ES-08034 Barcelona Spain Tech Univ Cartagena Computat Mech & Sci Comp Grp Campus Muralla del Mar Murcia 30202 Spain INEGI Rua Dr Roberto Frias 400 P-4200465 Porto Portugal CIMNE Edif C1Campus Nord UPC C Gran Capita S-N Barcelona 08034 Spain

Topology optimization under uncertainty of large-scale continuum structures is a computational challenge due to the combination of large finite element models and uncertainty propagation methods. The former aims to address the ever-increasing complexity of more and more realistic models, whereas the latter is required to estimate the statistical metrics of the formulation. In this work, the computational burden of the problem is addressed using a sparse grid stochastic collocation method, to calculate the statistical metrics of the topology optimization under uncertainty formulation, and a parallel adaptive mesh refinement method, to efficiently solve each of the stochastic collocation nodes. A two-level parallel processing scheme (TOUU-PS2) is proposed to profit from parallel computation on distributed memory systems: the stochastic nodes are distributed through the distributed memory system, and the efficient computation of each stochastic node is performed partitioning the problem using a domain decomposition strategy and solving each subdomain using an adaptive mesh refinement method. A dynamic load-balancing strategy is used to balance the workload between subdomains, and thus increasing the parallel performance by reducing processor idle time. The topology optimization problem is addressed using the topological derivative concept in combination with a level-set method. The performance and scalability of the proposed methodology are evaluated using several numerical benchmarks and real-world applications, showing good performance and scalability up to thousands of processors. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Adaptive mesh refinement Large scale parallel computing Robust topology optimization Topological derivative Sparse grid

来源：评论

学校读者我要写书评

暂无评论

distributed Processing of Electrical Meters Surveying

Distributed Processing of Electrical Meters Surveying

引用

Moscow workshop on Electronic and Networking Technologies (MWENT)

作者： Anton Ivaschenko Arkadiy Krivosheev Computing Department Samara State Technical University Samara Russia

ISBN: (数字)9781728125725

ISBN: (纸本)9781728125732

distributed processing of measurement results in a complex system is concerned with increasing computational load and challenges of reliable data fixation and association. In this paper there is proposed an intelligent system intended to collect, transfer, store, and process the data series gathered by distributed devices based on Big Data technologies. The example is given for stream processing of photo images produced by a number of distributed cameras. The introduced solution was implemented to process and analyze the results of electrical meters that are manually monitored by a group of patrol personnel inspectors using hand held devices. This example illustrates a necessity to provide autonomous preprocessing of photo images by an intelligent mobile application.

关键词： Meters Monitoring Neural networks Liquid crystal displays real-time systems Cameras Data processing

来源：评论

学校读者我要写书评

暂无评论

SFDDM: A Secure distributed Database Management in Combined Fog-to-Cloud systems 24

SFDDM: A Secure Distributed Database Management in Combined ...

引用

24th IEEE International workshop on Computer Aided Modeling and Design of Communication Links and Networks (IEEE CAMAD)

作者： Sengupta, Souvik Kahvazadeh, Sarang Masip-Bruin, Xavi Garcia, Jordi UPC BarcelonaTech CRAAX Lab Dept Comp Architecture DAC Vilanova I La Geltru Spain

ISBN: (纸本)9781728110165

Technological revolutions have greatly increased the use of IoT devices for our daily life. Driving the fact that everything surrounding us is getting connected what turns into an unstoppable increase in the amount of data produced. This data represents the state of diverse environmental events and helps to control a large set of distinct activities. So, accurate and secure management of this data is essential for any computing platform. Moreover, in order to provide real-time services in a distributed system (i.e., smart city), the data should be properly and securely managed. It is well known that shifting these tasks to the edge (i.e., near to the end users), highly facilitates these two objectives. The recently proposed Fog-to-Cloud (F2C) model is intended to enable data processing near to the edge, which helps to get better latency-sensitive services. However, some challenges remain to accurately and securely manage this data over the system, mainly due to the distributed F2C nature. Thus, considering these facts and challenges, in this paper we propose an architectural solution aimed at building a secure distributed database for F2C systems. Then, considering a real-case scenario, we perform some tests to measure the performance of our proposing schema. Finally, by comparing the performance between traditional cloud, fog/edge based execution model and our proposing SFDDM, we validate the effectiveness of our proposing schema.

关键词： Fog-to-Cloud (F2C) distributed Database Internet-of-Thing (IoT) Security and Privacy

来源：评论

学校读者我要写书评

暂无评论

Towards a distributed reality: A multi-video approach to xR 11

Towards a distributed reality: A multi-video approach to xR

引用

11th ACM SIGMM workshop on Immersive Mixed and Virtual Environment systems, MMVE 2019

作者： Villegas, Alvaro Pérez, Pablo González-Sosa, Ester Nokia Bell Labs Madrid Spain

ISBN: (纸本)9781450362993

In this article we define the concept of distributed reality, a new form of immersive media based on the combination of captured realities (e.g a remote and a local one), hence with a strong focus on video. While Virtual reality fully substitutes the real surrounding with a simulation and all existing variations of Mixed reality just provide additional synthetic elements into our visual field, our proposal is to capture and segment different scenes (one of them being the local one) in real time and merge the resulting elements dynamically, to create a completely new reality in front of the user senses. We compare this concept with prior art in the field and describe a taxonomy in which it fits. © 2019 Association for Computing Machinery.

关键词： Mixed reality

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：