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The green sustainable telco cloud: Minimizing greenhouse gas emissions of server load migrations between distributed data centres 12

The green sustainable telco cloud: Minimizing greenhouse gas...

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12th international conference on Network and Service Management, CNSM 2016 and workshops, 3rd international Workshop on Management of SDN and NFV, ManSDN/NFV 2016 and international Workshop on Green ICT and Smart Networking, GISN 2016

作者： Dandres, Thomas Samson, Rejean Moghaddam, Reza Farrahi Nguyen, Kim Khoa Cheriet, Mohamed Lemieux, Yves Polytechnique Montreal CIRAIG Montreal Canada Ecole de Technologie Superieure Synchromedia Ericsson Canada Inc. Montreal Canada Ecole de Technologie Superieure Synchromedia Montreal Canada Ericsson Canada Inc. Montreal Canada

ISBN: (纸本)9783901882852

Among the innovative approaches to reduce the greenhouse gas (GHG) emissions of data centres during their use phase, electrical power from renewable sources appears promising. However, renewable electricity is often intermittent due to meteorological conditions. Consequently, the regional availability of renewable power varies constantly over time. This created the opportunity to deploy cloud computing systems relying on data centres located in different regions. Cloud computing technology enables real-time load migration to a data centre in the region where the GHG emissions per kWh are the lowest. While this approach is becoming popular to manage distributed data centres, there is still room for improvement in its implementation. Indeed, the consequences of data centre power demand migrations across electric networks and the resulting GHG emissions are usually neglected. In this project, we developed a novel GHG emission factor based on the sources of electricity affected by the server load migrations. Then, we used this emission factor in a simulation of distributed data centres to minimize their GHG emissions. Results show, the use of the novel emission factor enables an extra reduction of 23% of GHG emissions as compared to the usual approach. © 2016 IFIP.

关键词： Greenhouse gases

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HiPC 2016 Workshop 1: international Workshop on Foundations of Big Data computing (BigDF)

HiPC 2016 Workshop 1: International Workshop on Foundations ...

引用

IEEE international conference on High Performance computing workshops (HiPCW)

作者： Madhu Govindaraju Saumyadipta Pyne

ISBN: (纸本)9781509057740

Summary form only given. The complete presentation was not made available for publication as part of the conference proceedings. What constitutes a "Big Data" problem? What application domains are best suited to benefit from Big Data analytics and computing? What are the traits and characteristics of an application that make it suited to exploit Big Data analytics? How can Big Data systems and frameworks be designed to allow the integration and analysis of complex data sets? How can research in Big Data Analytics benefit from the latest advances in supercomputing and High Performance computing (HPC) architectures? The goal of this workshop is to address questions like these that are fundamental to the advancement of Big Data computing, and in the process, build a diverse research community that has a shared vision to advance the state of knowledge and discovery through Big Data computing.

关键词： Big data Event detection High performance computing Real-time systems Social network services Convergence

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A High Performance computing Framework for Data Mining

A High Performance Computing Framework for Data Mining

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IEEE international conference on High Performance computing workshops (HiPCW)

作者： Navneet Goyal Sundar Balasubramaniam Poonam Goyal Saiyedul Islam Mohit Sati Department of Computer Science & Information Systems Birla Institute of Technology & Science Pilani Pilani India

ISBN: (纸本)9781509057740

Mining large data sets is no longer the prerogative of computer scientists - specialists in a wide variety of domains are performing analytics as a day-to-day activity. Often such analyses are specific to the domain and analysts are required to devise new algorithms or techniques. For such scenarios, providing a high-level programming environment that delivers high performance on clusters is a challenge. We propose a framework that supports high-level programming using domain abstractions in data mining while delivering scalable performance on commodity clusters i.e. clusters of multi-core workstations. This framework includes a domain specific programming language, DWARF, to enable data mining specialists to rapidly prototype algorithms. DWARF is supported by a compiler that automatically parallelizes code by identifying domain specific patterns and translating them to parallel code that exploits data parallelism and task parallelism. The compiler generates code for a hybrid virtual machine supporting distributed memory model at the top level and shared memory model nested within. The code generated by the compiler can be scheduled on commodity clusters. We compare the proposed framework with other frameworks commonly used for data mining on distributed platforms.

关键词： Data mining DSL Clustering algorithms Parallel processing Programming Algorithm design and analysis Sparks

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QoS Aware Resource Management for Apache Cassandra

QoS Aware Resource Management for Apache Cassandra

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IEEE international conference on High Performance computing workshops (HiPCW)

作者： Yasaswi Kishore N.H. Venkat Datta K.V. Subramaniam Dinkar Sitaram PESIT Bangalore India PES University Bangalore Karnataka IN PES University Bangalore India

ISBN: (纸本)9781509057740

Apache Cassandra is a distributed database of choice when it comes to big data management with zero downtime, linear scalability, and seamless multiple data center deployment. However, resource allocation for the system during deployment is a major issue which could either lead to bad performance or under-utilization of resources. In this paper we describe a QoS-aware architecture that manages resources for the distributed storage system to proactively and dynamically allocate resources for the distributed storage system to ensure that effective resource utilization and deliver performance according to the specified QoS. The architecture uses machine learning techniques to proactively predict and judge the performance of the system and make decisions for effective resource management for the database. In addition, we propose an adaptive sampling mechanism for classification to ensure that the architecture does not impose an unreasonable overhead on the system. We evaluate and provide results using Yahoo! Cloud Serving Benchmark (YCSB) on the modified Cassandra cluster. Our evaluation shows an increase of the overall utilization of the allocated resources without compromising on the required QoS latency for the overall cluster.

关键词： Peer-to-peer computing Quality of service Resource management Engines Computer architecture Databases Cloud computing

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23rd international conference on Computer Networks, CN 2016

引用

23rd international conference on Computer Networks, CN 2016

ISBN: (纸本)9783319392066

The proceedings contain 36 papers. The special focus in this conference is on Computer Networks Architectures, Protocols, Teleinformatics and Telecommunications. The topics include: Real-time traffic over the cognitive packet network;investigating long-range dependence in e-commerce web traffic;more just measure of fairness for sharing network resources;classification of solutions to the minimum energy problem in one dimensional sensor networks;detection of malicious data in vehicular ad hoc networks for traffic signal control applications;anti-evasion technique for the botnets detection based on the passive DNS monitoring and active DNS probing;probabilistic model checking of security protocols without perfect cryptography assumption;high-interaction Linux honeypot architecture in recent perspective;about the efficiency of malware monitoring via server-side honeypots;algorithms for transmission failure detection in a communication system with two buses;a failure influence on parameters of real-time system with two buses;event-driven approach to modeling and performance estimation of a distributed control system;influence of noise and voice activity detection on speaker verification;quantum network protocol for qudits with use of quantum repeaters and Pauli z-type operational errors;multi-level virtualization and its impact on system performance in cloud computing;ping-pong protocol eavesdropping in almost perfect channels;a regeneration-based estimation of high performance multiserver systems;queuing model of the access system in the packet network;a study of IP router queues with the use of Markov models and a dual tandem queue with multi-server stations and losses.

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High Frequency Trading with Complex Event Processing

High Frequency Trading with Complex Event Processing

引用

IEEE international conference on High Performance computing workshops (HiPCW)

作者： Ajay Acharya Nandini S. Sidnal Dept. of CS&E KLE Dr. MSSCET Belagavi India

ISBN: (纸本)9781509057740

High frequency trading is steadily taking over the equity trading world. High frequency trading involves very high speed systems placing trades at sub millisecond speeds across multiple stock exchanges. HFT is a good example for Big Data analytics - especially the velocity aspect of big data. For HFT strategies to be profitable, real time processing of big data is essential. In this paper we discuss the challenges faced by HFT systems and the opportunity for big data processing with low latency in the field. Most HFT systems are designed using real time stream processing, which have certain drawbacks. We present a theoretical framework for building high frequency trading systems using the complex event processing paradigm which could overcome the drawbacks of stream processing. Complex event processing enables detecting patterns of events from disparate events streams and responds to the detected pattern. The applicability of the framework for HFT applications is discussed.

关键词： Real-time systems Big data Stock markets Computer architecture High performance computing Consumer electronics Feeds

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Towards Understanding Optimal Load-Balancing of Heterogeneous Short-Range Molecular Dynamics

Towards Understanding Optimal Load-Balancing of Heterogeneou...

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IEEE international conference on High Performance computing workshops (HiPCW)

作者： Steffen Hirschmann Dirk Pflüger Colin W. Glass Institute for Parallel and Distributed Systems University of Stuttgart Stuttgart Germany High Performance Computing Center Stuttgart University of Stuttgart Stuttgart Germany

ISBN: (纸本)9781509057740

For heterogeneous dynamic short-range molecular dynamics simulations it is critical to employ suitable load-balancing methods to minimize the time to solution. However, designing and parametrizing the optimal load-balancing method is a complex task, depending on detailed properties of the simulation *** main challenge in balancing the load of molecular dynamics simulations is the extreme difference in load density for scenarios with heterogeneous particle density, which can easily reach 4-6 orders of magnitude. Therefore, heterogeneity is deemed to be a relevant property and a suitable metric to reliably quantifying heterogeneity is formulated. This metric, which is based on binning particles and evaluating statistical moments, is then applied to example scenarios and correlated to the performance of five load balancing methodologies. Furthermore, how rapidly the load varies over time will determine how long the benefits of a specific partitioning are expected to last. We deem this to be another relevant property, the dynamics, and introduce corresponding metrics. The results indicate that these metric are useful to differentiate between scenarios and facilitate reasoning over the complex relationship between particle simulation scenarios and optimal load balancing methods. This work is a first step towards understanding this relationship, while introducing key concepts we regard as a crucial for this understanding.

关键词： Load modeling Computational modeling Measurement Dynamics Force Partitioning algorithms Load management

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A Numerical Investigation on Bubble Formation in Coolant Channel with Various Ethylene Glycol and Water Compositions and Change in Contact Angle

A Numerical Investigation on Bubble Formation in Coolant Cha...

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IEEE international conference on High Performance computing workshops (HiPCW)

作者： Vamshi Krishna Chitikase Chih-Cheng Hsu Global Propulsion Systems Transmission & Electrification CFD General Motors Bangalore India Engineering Propulsion Systems Electrification Thermal General Motors North America

ISBN: (纸本)9781509057740

Numerous latest high power electronic circuit systems use an external cooling channel filled with circulating liquid coolant which acts as a heat sink to remove generated heat from surrounding components. While filling the coolant, air in the channel has to be completely removed before the final sealing is applied for good thermal and Noise, Vibration & Harshness (NVH) performance of the heat sink. It is also important from pump durability perspective. A numerical investigation has been conducted to understand the effect of capillary number and contact angle on the bubble formation by using several compositions of Ethylene Glycol and water mixture. The results indicated that bubble formation decreases with increase in Capillary number and increases with increase in contact angle.

关键词： Coolants Mathematical model Liquids Geometry Computational fluid dynamics Solids Computational modeling

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A Hybrid Recommender System Using Weighted Ensemble Similarity Metrics and Digital Filters

A Hybrid Recommender System Using Weighted Ensemble Similari...

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IEEE international conference on High Performance computing workshops (HiPCW)

作者： Ramesh Naidu Laveti Janaki Ch Supriya N Pal N. Sarat Chandra Babu Centre for Development of Advanced Computing (C-DAC) Bangalore Karnataka India Centre for Development of Advanced Computing Juhu Maharashtra IN

ISBN: (纸本)9781509057740

Recommender systems aim to predict the rating or preference of a user given to an item and provide suggestions of further resources that are likely to be of interest. The critical part of the recommender algorithm is finding the similarity metrics, which yield predictions with different accuracies and varieties. In the case of high dimensional feature space, the recommender systems using traditional similarity metrics suffer from several problems such as cold-start problem, scalability, over-specialization and data imbalance. In this paper, a recommender system using weighted ensemble hybrid similarity metric model is proposed by combining two or more traditional similarity metrics such as Pearson correlation, log-likelihood and Tanimoto coefficient. The digital filter is extended and adapted in order to handle the posterior intractability and spatial smoothing of high dimensional recommender space. The proposed recommender system is implemented using Apache Mahout. The evaluation of the model has been done using three large MovieLens datasets consist of 100 thousand ratings, 1 Million ratings and 10 Million ratings. We provide a quantitative and a qualitative evaluation. Interesting conclusions were extracted from the real-time execution of the proposed system on the above-mentioned data sets. The comparison with the results obtained from the traditional recommender systems shows that the proposed system achieved significant improvement in the accuracy for large data sets.

关键词： Digital filters Recommender systems Collaboration Correlation Euclidean distance

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Molecular Dynamics Simulation of Nanoscopic Couette Flow and Lubricated Nanoindentation

Molecular Dynamics Simulation of Nanoscopic Couette Flow and...

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IEEE international conference on High Performance computing workshops (HiPCW)

作者： S. Stephan M. Lautenschläger M. Horsch H. Hasse Laboratory of Engineering Thermodynamics University of Kaiserslautern Germany

Summary form only given. Molecular dynamics simulation is a powerful tool for the investigation of nanoscopic processes that are hard or impossible to investigate by experiment in detail at the molecular level. The present work concerns tribological properties of model systems which are described by the Lennard-Jones truncated-shifted potential. Two related scenarios are studied: 1) Couette flow; 2) lubricated contact of two solid bodies. The influence of the solid-fluid interaction energy on the tribological properties, which is found to be significant, controls the adhesion of the fluid at the solid surface and therefore the wetting properties of the system. In particular, it is shown here that the solid-fluid interaction energy decisively affects the heat balance of stationary non-equilibrium states for the studied systems, regarding both the source and the sink term. Thereby, various phenomena combine in a non-trivial way: Firstly, upon increasing the solid-fluid interaction energy, the friction coefficient increases, so that more heat is dissipated. This leads to an enhanced heating of the surrounding fluid. Simultaneously, the thermal resistance at the solid-fluid interface decreases due to a stronger thermal coupling between the substrate and the adsorbed fluid. Since a greater solid-fluid interaction energy leads to a higher average fluid temperature (at otherwise constant conditions), the thermal conductivity of the fluid increases, which reinforces these effects by enhancing the transfer of the dissipated heat to the fluid.

关键词： Fluids conferences Computational modeling Solids Heating Thermal resistance High performance computing

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