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Automatic Energy Efficient HPC Programming: A Case Study 16

Automatic Energy Efficient HPC Programming: A Case Study

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

作者： Rais, Issam Coullon, Helene Lefevr, Laurent Perez, Christian INRIA IMT Atlantique LS2N UBL F-44307 Nantes France Univ Claude Bernard Lyon 1 Univ Lyon CNRS INRIAENS LyonLIP Lyon France

ISBN: (纸本)9781728111414

Energy consumption is one of the major challenges of modern datacenters and supercomputers. By applying Green Programming techniques, developers have to iteratively implement and test new versions of their software, thus evaluating the impact of each code version on their energy, power and performance objectives. this approach is manual and can be long, challenging and complicated, especially for High Performance computing applications. In this paper, we formally introduces the definition of the Code Version Variability (CVV) leverage and present a first approach to automate Green Programming (i.e., CVV usage) by studying the specific use-case of an HPC stencil-based numerical code, used in production. this approach is based on the automatic generation of code versions thanks to a Domain Specific Language (DSL), and on the automatic choice of code version through a set of actors. Moreover, a real case study is introduced and evaluated though a set of benchmarks to show that several trade-offs are introduced by CVV1. Finally, different kinds of production scenarios are evaluated through simulation to illustrate possible benefits of applying various actors on top of the CVV automation.

关键词： Code version variability leverage green programming automation energy efficiency power capping high performance computing DSL shallow-water equations

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MOCCAA: A Delta-synchronized and Adaptable Mobile Cloud computing Framework 8

MOCCAA: A Delta-synchronized and Adaptable Mobile Cloud Comp...

引用

8th international conference on Cloud computing and Services Science (CLOSER)

作者： Baraki, Harun Schwarzbach, Corvin Fax, Malte Geihs, Kurt Univ Kassel Distributed Syst Grp Wilhelmshoher Allee 73 Kassel Germany

ISBN: (纸本)9789897582950

Mobile Cloud computing (MCC) requires an infrastructure that is merging the capabilities of resource-constrained but mobile and context-aware devices with that of immovable but powerful resources in the cloud. Application execution shall be boosted and battery consumption reduced. However, a solution's practicability is only ensured, if the provided tools, environment and framework themselves are performant too and if developers are able to adopt, extend and apply it easily. In this light, we introduce our comprehensive and extendable framework MOCCAA (MObile Cloud computing AdaptAble) and demonstrate its effectiveness. Its performance gain is mainly achieved through minimized monitoring efforts for resource consumption prediction, scalable and location-aware resource discovery and management, and, in particular, through our graph-based delta synchronization of local and remote object states. this allows us to reduce synchronization costs significantly and improve quality dimensions such as latency and bandwidth consumption.

关键词： Mobile Cloud computing Delta Synchronization Resource Management System

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Fisher: An Efficient Container Load Prediction Model with Deep Neural Network in Clouds 16

Fisher: An Efficient Container Load Prediction Model with De...

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

作者： Tang, Xuehai Liu, Qiuyang Dong, Yangchen Han, Jizhong Zhang, Zhiyuan Chinese Acad Sci Inst Informat Engn Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Cyber Secur Beijing 100190 Peoples R China

ISBN: (纸本)9781728111414

Recently, more and more applications have been deployed in container, and prediction of container load is essential in Clouds for improving resource utilization and achieving service-level agreements. However, accurate prediction of container load in Clouds remains an extremely challenge because the container load fluctuates drastically at small timescales. Furthermore, with many metrics of container in Clouds, it is hard to find which metrics are going to be useful. To address these challenges, we design an efficient container load prediction model named Fisher to improve the accuracy and efficiency of prediction. It mainly includes two modules: a metrics selection module and a neural network training module. We first selects relevant metrics by metrics selection module which is a novel algorithm for shape-based time-series clustering. Afterwards, we apply a powerful deep neural network model built with bidirectional long short-term memory to predict actual load one-step-ahead. We evaluate Fisher using a 30-day load trace from a data center with 500 containers. Experiments show that Fisher can reduce training metrics while maintaining prediction accuracy. More importantly, our model significantly improves prediction accuracy over 50% compared to other state-of-the-art methods based on autoregressive integrated moving-average and long short-term memory.

关键词： Cloud computing Container Load prediction Bidirectional Long short-term memory Time series analysis

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IoV distributed architecture for real-time traffic data analytics 9th

IoV distributed architecture for real-time traffic data anal...

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9th international conference on Ambient Systems, Networks and Technologies (ANT) / 8th international conference on Sustainable Energy Information Technology (SEIT)

作者： Nahri, Mohamed Boulmakoul, Azedine Karim, Lamia Lbath, Ahmed Hassan II Univ Casablanca FSTM LIM IOS BP 146 Mohammadia Morocco Hassan 1st Univ Higher Sch Technol EST Berrechid Beni Mellal Khenifra Morocco Univ Grenoble Alpes LIG MRIM CNRS Grenoble France

In this paper, we present necessary premises for the deployment of the Internet of Vehicles (IoV) integrating Big Data analytics of road network traffic measurements of the city of Mohammedia, Morocco. thus, we introduce an architecture based on three main layers such as IoV, Fog computing and Cloud computing Layer. We specifically put more focus on Fog computing layer in which we develop a framework for a real-time collecting and processing events generated by intelligent vehicles as well as visualizing traffic state on each road section. Furthermore, we consider deployment and test of the proposed framework using events retrieved from a Vanets-type micro simulation. Finally, we present and discuss the first obtained results as well as the advantages and limitations of the proposed architecture. (C) 2018 the Authors. Published by Elsevier B.V.

关键词： IoV Big Data analytics Fog computing Real-time data analytics Traffic control

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Scalable Data Placement of Data-intensive Services in Geo-distributed Clouds 8

Scalable Data Placement of Data-intensive Services in Geo-di...

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8th international conference on Cloud computing and Services Science (CLOSER)

作者： Atrey, Ankita Van Seghbroeck, Gregory Volckaert, Bruno De Turck, Filip UGent IDLAB Imec Technol Pk Ghent Belgium

ISBN: (纸本)9789897582950

the advent of big data analytics and cloud computing technologies has resulted in wide-spread research in finding solutions to the data placement problem, which aims at properly placing the data items into distributed datacenters. Although traditional schemes of uniformly partitioning the data into distributed nodes is the defacto standard for many popular distributed data stores like HDFS or Cassandra, these methods may cause network congestion for data-intensive services, thereby affecting the system throughput. this is because as opposed to MapReduce style workloads, data-intensive services require access to multiple datasets within each transaction. In this paper, we propose a scalable method for performing data placement of data-intensive services into geographically distributed clouds. the proposed algorithm partitions a set of data-items into geo-distributed clouds using spectral clustering on hypergraphs. Additionally, our spectral clustering algorithm leverages randomized techniques for obtaining low-rank approximations of the hypergraph matrix, thereby facilitating superior scalability for computation of the spectra of the hypergraph laplacian. Experiments on a real-world trace-based online social network dataset show that the proposed algorithm is effective, efficient, and scalable. Empirically, it is comparable or even better (in certain scenarios) in efficacy on the evaluated metrics, while being up to 10 times faster in running time when compared to state-of-the-art techniques.

关键词： Data Placement Geo-distributed Clouds Location-based Services Online Social Networks Scalability Spectral Clustering Hypergraphs Approximation

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Access Domain-Based Approach for Anomaly Detection and Resolution in XACML Policies 8th

Access Domain-Based Approach for Anomaly Detection and Resol...

引用

8th international conference on Innovations in Bio-Inspired computing and Applications (IBICA)

作者： El Hadj, Maryem Ait Benkaouz, Yahya Khoumsi, Ahmed Erradi, Mohammed Mohammed V Univ Rabat ENSIAS ITM Team Networking & Distributed Syst Res Grp Rabat Morocco Mohammed V Univ Rabat Concept & Syst Lab FSR Rabat Morocco Univ Sherbrooke Dept Elect & Comp Engn Sherbrooke PQ Canada

ISBN: (纸本)9783319763545;9783319763538

Access control protects systems' resources against unauthorized access via a set of policy rules. In distributed environments, access control policies might be aggregated from multiple tenants and could be managed by more than one administrator. therefore, errors in the rules definitions may compromise the system security by leading to unauthorized access or denying authorized access. this may result into anomalies, i.e. conflicting rules and redundant rules. In this paper, we propose an approach to detect and resolve anomalies in XACML (eXtensible Access Control Markup Language) policies. We introduce the concept of a rule access domain, which is used to accurately identify and resolve policy anomalies.

关键词： XACML policies Clustering Anomaly detection Anomaly resolution Access domain

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On Cost Efficient Dataflow computing Program Deployment in SDN Managed distributed computing Environment 13th

On Cost Efficient Dataflow Computing Program Deployment in S...

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13th European-Alliance-for-Innovation (EAI) international conference on Collaborative computing - networking, Applications and Worksharing (CollaborateCom)

作者： Zhang, Yating Li, Yuepeng Zheng, Long Zeng, Deze Shanghai Jiao Tong Univ Dept Comp Sci & Engn Shanghai Peoples R China China Univ Geosci Sch Comp Sci Wuhan Hubei Peoples R China Shenzhen Univ Coll Comp Sci & Software Engn Shenzhen Guangdong Peoples R China

ISBN: (纸本)9783030009168;9783030009151

Dataflow computing has been regarded one of the most promising computing paradigms in the big data era. With the vast distribution of data sources, it is significant to deploy the dataflow based applications in distributed environment to digest these data. In dataflow computing, the data flows shall be transferred between different processing units to the accomplish the predefined semantics. Software-defined networking (SDN) has emerged as an effective network management technology to orchestrate the data flows among these processing units. For each data flow, a forwarding rule shall be inserted into the forwarding table of each switch on the routing path. However, the number of rules that can be inserted in one forwarding table is limited. We are motivated to take such constraints into the consideration of dataflow applications deployment in distributed computing environment managed by SDN. An efficient deployment algrotithm is proposed and evaluated in this paper.

关键词： Data transfer

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Exploring Computation Offloading in Vehicular Clouds

Exploring Computation Offloading in Vehicular Clouds

引用

IEEE international conference on Cloud networking (CLOUDNET)

作者： Alisson Barbosa de Souza Paulo Antonio Leal Rego José Neuman de Souza GREat / Federal University of Ceará Fortaleza Brazil

ISBN: (数字)9781728148328

ISBN: (纸本)9781728148335

VANETs (Vehicular Ad Hoc Networks) aim to provide safety and comfort services for drivers on roads and highways. Among these services, there are computation-intensive tasks in real-time applications that need to be executed as quickly as possible. Using VCC (Vehicular Cloud computing) paradigm, where vehicles offer their underutilized computing resources as a service and with the goal of reducing the execution time of tasks, this paper investigates how the computation offloading technique can be leveraged to speed up the execution of tasks under different conditions and in varied scenarios. We present an offloading decision algorithm and several simulations results that show we can achieve better processing times than to execute locally and better success rates than random algorithm.

关键词： Task analysis Cloud computing Data models Road transportation Vehicular ad hoc networks Vehicles Performance evaluation

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A Case for Data Centre Traffic Management on Software Programmable Ethernet Switches

A Case for Data Centre Traffic Management on Software Progra...

引用

IEEE international conference on Cloud networking (CLOUDNET)

作者： Kamil Tokmakov Mitalee Sarker Jörg Domaschka Stefan Wesner High Performance Computing Center Stuttgart (HLRS) Stuttgart Germany Institute of Information Resource Management Ulm University Germany

ISBN: (数字)9781728148328

ISBN: (纸本)9781728148335

Virtualisation first and cloud computing later has led to a consolidation of workload in data centres that also comprises latency-sensitive application domains such as High Performance computing and telecommunication. these types of applications require strict latency guarantees to maintain their Quality of Service. In virtualised environments with their churn, this demands for adaptability and flexibility to satisfy. At the same time, the mere scale of the infrastructures favours commodity (Ethernet) over specialised (Infiniband) hardware. For that purpose, this paper introduces a novel traffic management algorithm that combines Rate-limited Strict Priority and Deficit round-robin for latency-aware and fair scheduling respectively. In addition, we present an implementation of this algorithm on the bmv2 P4 software switch by evaluating it against standard priority-based and best-effort scheduling.

关键词： Scheduling algorithms Data centers Quality of service Software Standards Delays Cloud computing

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CLOSER 2018 - Proceedings of the 8th international conference on Cloud computing and Services Science

CLOSER 2018 - Proceedings of the 8th International Conferenc...

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8th international conference on Cloud computing and Services Science, CLOSER 2018

ISBN: (纸本)9789897582950

the proceedings contain 70 papers. the topics discussed include: model-driven configuration management of cloud applications with OCCI;HIOBS: a block storage scheduling approach to reduce performance fragmentation in heterogeneous cloud environments;power and cost-aware virtual machine placement in geo-distributed data centers;detection of access control violations in the secure sharing of cloud storage;MOCCAA: a delta-synchronized and adaptable mobile cloud computing framework;transparent interoperability middleware between data and service cloud layers;and scheduling latency-sensitive applications in edge computing.

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