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检索条件"任意字段=8th International Conference on Distributed Computing and Networking"

共 2982 条记录，以下是741-750 订阅

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Latency and Quality Perception in Mobile Touchscreen Interactions Research in the Field of Human Centered computing 8

Latency and Quality Perception in Mobile Touchscreen Interac...

引用

8th international conference Confluence on Cloud computing, Data Science and Engineering, Confluence 2018

作者： Singh, Ankit Jake Hightower Clarence Hwang India

Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record. ... 详细信息

ISBN: (纸本)9781538617182

关键词： Visualization Presses Pressing distributed databases Cloud computing Data science Human factors"

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Cymbalo: An Efficient Graph Processing Framework for Machine Learning 16

Cymbalo: An Efficient Graph Processing Framework for Machine...

引用

16th IEEE ISPA / 17th IEEE IUCC / 8th IEEE BDCloud / 11th IEEE SocialCom / 8th IEEE SustainCom

作者： Tian, Xinhui Xie, Biwei Zhan, Jianfeng Chinese Acad Sci Inst Comp Technol State Key Lab Comp Architecture Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China

ISBN: (纸本)9781728111414

Due to the growth of data scale, distributed machine learning has become more important than ever. Some recent work, like TuX(2), show promising prospect in dealing with distributed machine learning by leveraging the power of graph computation, but still leave some key problems unsolved. In this paper, we propose Cymbalo, a new distributed graph processing framework for large-scale machine learning algorithms. To satisfy the specific characteristics of machine learning, Cymbalo employs a heterogeneity-aware data model, a hybrid computing model and a vector-aware programming model, to ensure small memory footprint, good computation efficiency and expressiveness. the experiment results show that Cymbalo outperforms Spark by 2.4x-3.2x, and PowerGraph by up to 5.8x. Moreover, Cymbalo can also outperform Angel, a recent parameter server system, by 1.6x-2.1x.

关键词： Large-scale machine learning Graph computation distributed processing Spark

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Blockchain provisioning over private cloud computing environments: Availability modeling and cost requirements

Blockchain provisioning over private cloud computing environ...

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IEEE international conference on Cloud networking (CLOUDNET)

作者： Carlos Melo Jamilson Dantas Ronierison Maciel Paulo Pereira Eder Quesado Paulo Maciel Informatics Center Federal University of Pernambuco Recife Brazil

ISBN: (数字)9781728148328

ISBN: (纸本)9781728148335

this paper proposes and evaluates availability models for blockchain provisioning over cloud computing infrastructures as well as their respective deployment expenses in order to establish a cost × benefit relationship. To demonstrate these models' feasibility, we provide two case studies considering blockchain provisioning over a baseline architecture, and three other alternative redundant environments.

关键词： Computer architecture Cloud computing Peer-to-peer computing Computational modeling Redundancy Organizations

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Radix: Enabling High-throughput Georeferencing for Phenotype Monitoring over Voluminous Observational Data 16

Radix: Enabling High-throughput Georeferencing for Phenotype...

引用

16th IEEE ISPA / 17th IEEE IUCC / 8th IEEE BDCloud / 11th IEEE SocialCom / 8th IEEE SustainCom

作者： Roselius, Maxwell Pallickara, Sangmi Lee Colorado State Univ Dept Comp Sci Ft Collins CO 80523 USA

ISBN: (纸本)9781728111414

Remote sensing of plant traits and their environment facilitates non-invasive, high-throughput monitoring of the plant's physiological characteristics. Effective ingestion of these sensing data into a storage subsystem while georeferencing phenotyping setups is key to providing timely access to scientists and modelers. In this study, we propose RADIX, a high-throughput distributed data ingestion framework with support for fine-grained georeferencing. Our methodology includes a novel spatial indexing scheme, the nested hash grid, for fine-grained georeferencing of data while conserving memory footprints and ensuring acceptable latency. We include empirical evaluations performed on a commodity machine cluster with up to 1TB of data. Our benchmarks demonstrate the efficacy of our approach.

关键词： high-throughput georeferencing distributed analytics High-throughput phenotyping. data ingestion sensor data

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Asynchronous group-based ADMM algorithm under efficient communication structure 16

Asynchronous group-based ADMM algorithm under efficient comm...

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16th IEEE ISPA / 17th IEEE IUCC / 8th IEEE BDCloud / 11th IEEE SocialCom / 8th IEEE SustainCom

作者： Zhou, Jianhui Lei, Yongmei Shanghai Univ Sch Comp Engn & Sci Shanghai Peoples R China

ISBN: (纸本)9781728111414

Alternating direction method of multipliers (ADMM) has been recognized as an efficient approach for solving many large-scale machine learning problems. However, the ADMM under master-slave mode suffers from several limitations, e.g., can't make full use of multi-core cluster environment and single master load is too heavy, resulting in huge time overhead. In this paper, we propose a hierarchical communication structure. Since intra-node communications mostly use shared memory, we divide the processes of the same node into one group, the processes within the group synchronize communication, and each group communicate asynchronously with the master. Combining this structure with the ADMM algorithm, a hierarchical asynchronous group-based ADMM algorithm (HAG-ADMM) is proposed. theoretical analysis and experiments show that the hierarchical communication structure can improve the communication efficiency of the algorithm and has no effect on the convergence.

关键词： distributed optimization ADMM asynchronous hierarchical communication structure group-based ADMM parallel computing

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Acinonyx: Dynamic Flow Scheduling for Virtual Machine Migration in SDN-enabled Clouds 16

Acinonyx: Dynamic Flow Scheduling for Virtual Machine Migrat...

引用

16th IEEE ISPA / 17th IEEE IUCC / 8th IEEE BDCloud / 11th IEEE SocialCom / 8th IEEE SustainCom

作者： Toosi, Adel Nadjaran Buyya, Rajkumar Monash Univ Fac Informat Technol Clayton Vic Australia Univ Melbourne Sch Comp & Informat Syst Parkville Vic Australia

ISBN: (纸本)9781728111414

Cloud providers rely on virtualization technology for efficient data center management and service delivery. Live Virtual Machine (VM) Migration is one of the critical features of this technology enabling cloud providers to relocate VMs between servers without disrupting applications currently running on it. One of the key challenges of VM live migration is that it creates elephant flows over the network links connecting the source to destination servers due to the transfer of the entire memory and possibly disks of the VM. In this paper, we leverage software -defined networking (SDN) and propose a dynamic flow scheduling approach called Acinonyx. Our solution is designed to minimize the negative impact of live VM migration on data center network traffic and reduce migration time in cloud data centers with multiple network paths between servers. Acinonyx adaptively installs flow entries on the switches of the shortest path with the lowest congestion and redirects VM migration traffic to the appropriate path. We describe the implementation of the proposed solution over our testbed environment, where we use OpenStack for managing commodity servers and OpenDaylight SDN controller for managing the OpenFlow switches. Our experimental results show that Acinonyx can significantly reduce the migration time of VMs while improving the overall network throughput for other VM communications.

关键词： Software-defined networking Cloud computing Dynamic Flow Scheduling Live VM Migration OpenDaylight OpenStack

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Contract-Based Demand Response Model for High Performance computing Systems 16

Contract-Based Demand Response Model for High Performance Co...

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16th IEEE ISPA / 17th IEEE IUCC / 8th IEEE BDCloud / 11th IEEE SocialCom / 8th IEEE SustainCom

作者： Ahmed, Kishwar Bull, Jesse Liu, Jason Florida Int Univ Miami FL 33199 USA

ISBN: (纸本)9781728111414

High-performance computing (HPC) systems can consume substantial electricity during their operation, and consequently incur significant energy cost. Demand response is a scheme adopted by energy consumers to reduce energy use during the high load periods upon request from the power grid. In this paper, we propose a demand response model to allow both HPC operators and HPC users to jointly reduce the energy consumption. We apply the contract theory, originated from economics for studying the contractual arrangements among economic actors, and design a reward mechanism to ensure participation of both HPC operators and HPC users in the demand response program. We perform both analytical and simulation studies of our proposed approach. Our analyses show that our contract-based demand response model is both feasible (in ensuring both individual rationality and incentive compatibility) and optimal. the trace-based simulation demonstrates the practicality of the proposed approach.

关键词： Demand Response Energy Efficiency Contract theory High-Performance computing

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Fog computing with the integration of Internet of things: Architecture, Applications and Future Directions 16

Fog computing with the integration of Internet of things: Ar...

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16th IEEE ISPA / 17th IEEE IUCC / 8th IEEE BDCloud / 11th IEEE SocialCom / 8th IEEE SustainCom

作者： Wadhwa, Heena Aron, Rajni Lovely Profess Univ Jalandhar Dept CSE Jalandhar Punjab India Chandigarh Engn Coll Dept IT Landran Mohali Punjab India

ISBN: (纸本)9781728111414

Information Technology industry has competitiveness on the basis of technological environment. In this environment, the use of cloud services has been increasing to provide high quality services and fast delivery of products to cloud users. But still some issues are unresolved especially, related to latency between cloud data center and end user. Fog computing is used to support increasing demand of IT service with the collaboration of cloud computing. It provides computational and storage services of cloud proximate to IoT devices. Fog computing is enhancement of the cloud-based network and computing services. this paper discusses the concept, architecture of fog computing and implemented application. It also highlights about resource provisioning techniques to identify over utilization of fog nodes. Along with the resource utilization, different scheduling terminologies have also been discussed on various parameters. the motive of this survey is to understand the application of fog computing to improve the existing smart healthcare system.

关键词： Fog computing Fog Provisioning IoT with Fog computing Scheduling techniques Resource utilization Healthcare application

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Polynomial-time Algorithm for distributed Server Allocation Problem

Polynomial-time Algorithm for Distributed Server Allocation ...

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IEEE international conference on Cloud networking (CLOUDNET)

作者： Takaaki Sawa Fujun He Akio Kawabata Eiji Oki Kyoto University Kyoto Japan NTT Network Service System Laboratories Tokyo Japan

this paper proposes an algorithm for the distributed server allocation problem, namely Minimizing the Maximum Delay (MMD), where an optimal solution is obtained when all server-server delays are the same constant valu... 详细信息

ISBN: (数字)9781728148328

ISBN: (纸本)9781728148335

关键词： Servers Delays Resource management Time complexity Optimization Two dimensional displays Bipartite graph

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Improving Data Locality in P2P-based Fog computing Platforms 9

Improving Data Locality in P2P-based Fog Computing Platforms

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9th international conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN) / 8th international conference on Current and Future Trends of Information and Communication Technologies in Healthcare (ICth)

作者： Steffenel, Luiz Angelo Pinheiro, Manuele Kirsch Univ Reims Reims France Univ Paris 1 Pantheon Sorbonne Paris France

Fog computing extends the Cloud computing paradigm to the edge of the network, relying on computing services intelligently distributed to best meet the applications needs such as low communication latency, data caching or confidentiality reinforcement. While P2P is especially prone to implement Fog computing platforms, it usually lacks important elements such as controlling where the data is stored and who will handle the computing tasks. In this paper we propose both a mapping approach for data-locality and a location-aware scheduling for P2P-based middlewares, improving the data management performance on fog environments. Experimental results comparing the data access performances demonstrate the interest of such techniques. (C) 2018 the Authors. Published by Elsevier Ltd.

关键词： fog computing P2P overlay data locality big data distributed hash table

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