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Information Theory Based Genome-scale Gene Networks Construction using MapReduce 22

Information Theory Based Genome-scale Gene Networks Construc...

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22nd international conference on High Performance computing

作者： Chockalingam, Sriram P. Aluru, Maneesha Aluru, Srinivas Indian Inst Technol Dept Comp Sci & Engn Mumbai Maharashtra India Georgia Inst Technol Sch Biol Atlanta GA USA Georgia Inst Technol Sch Computat Sci & Engn Atlanta GA USA

ISBN: (纸本)9781467384889

Reverse-engineering genome-scale gene networks from gene expression data is a principal challenge in systems biology. Mutual information (MI) based methods are favored because of their ability to recover non-linear relationships, low algorithmic complexity, and their successful use in various biological applications such as gene function prediction. In this paper, we present the first ever construction of MI based genome-scale gene networks using MapReduce. We develop the solution for all the stages of a MI-based network construction algorithm using only the map and reduce operations on distributed datasets. Our solution is implemented using Spark, a software that provides a compute and memory abstraction for distributed datasets. We deploy our solution using on-demand virtual instances on Amazon EC2 cloud computing platform, thus demonstrating the use of a rent-by-the-hour ad-hoc cluster for this grand challenge problem in systems biology. Our implementation can scale with the number of virtual instances, and can be used to construct networks of sizes in the range of 2000 to 5000 genes within an hour in a cost effective manner. We demonstrate the capability to construct genome-scale networks by reverse engineering a network of over 17,000 genes for the widely studied model plant Arabidopsis Thaliana.

关键词： reverse-engineering map reduce gene networks mutual information

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A proposed architecture for soft computing in smart grid as a cloud-based service

A proposed architecture for soft computing in smart grid as ...

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international conference on Knowledge-Based engineering and Innovation (KBEI)

作者： Naghmeh Dezhabad Seyed Ahmad Motamedi Saeed Sharifian Electrical Engineering Department Amirkabir University of Technology Tehran Iran

Smart grid empowers the electrical utilities improve the efficiency and the availability of the power system while constantly monitoring, controlling and managing the demands of customers. Computational requirements for Smart grid applications can be met by utilizing the cloud computing model. Collecting, storing and analyzing large amount of data, which can be very varied and produced at high rates will be done in a distributed manner. The scalable and elastic resources of a cloud infrastructure not only satisfy these needs but also offer interesting properties to utility companies (i.e., elasticity, scalability, pay-as-you-go model, etc.) and make a reliable, robust, and efficient Smart grid environment. In this paper, we present the opportunities and challenges of using cloud computing in power grid Applications and propose a cloud-based solution for information requirements of Smart grid.

关键词： Handheld computers Decision support systems Smart grids Big data Spatial databases cloud computing Electronic mail

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Analyzing and predicting failure in hadoop clusters using distributed hidden markov model 2nd

Analyzing and predicting failure in hadoop clusters using di...

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2nd international conference on cloud computing and Big Data, cloudCom-Asia 2015

作者： Agrawal, Bikash Wiktorski, Tomasz Rong, Chunming Department of Computer and Electrical Engineering University of Stavanger Stavanger Norway

ISBN: (纸本)9783319284293

In this paper, we propose a novel approach to analyze and predict failures in Hadoop cluster. We enumerate several key challenges that hinder failure prediction in such systems: heterogeneity of the system, hidden complexity, time limitation and scalability. At first, clustering approach is applied to group similar error sequences, which makes training of the model effectual subsequently Hidden Markov Models (HMMs) is used to predict failure, using the MapReduce programming framework. The effectiveness of the failure prediction algorithm is measured by precision, recall and accuracy metrics. Our algorithm can predict failure with an accuracy of 91% with 2 days in advance using 87% of data as training sets. Although the model presented in this paper focuses on Hadoop clusters, the model can be generalized in other cloud computing frameworks as well. © Springer international Publishing Switzerland 2015.

关键词： Hidden Markov models

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AutoCSD: Automatic cloud system deployment in data centers 2nd

AutoCSD: Automatic cloud system deployment in data centers

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2nd international conference on cloud computing and Big Data, cloudCom-Asia 2015

作者： Xie, Tao Chen, Haibao Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China School of Computer and Information Engineering Chuzhou University Chuzhou239000 China

ISBN: (纸本)9783319284293

It is a huge challenge to deploy a cloud computing system in large-scale data centers. In order to help resolve this issue, we propose an automatic cloud system deployment approach with the characteristics of reliability, availability, and load balance. Specifically, we use workflow to deal with the dependencies among the automatic deployment processes of a cloud system. We also design a failover mechanism to avoid the single point failure of the deployment server. Besides, we adopt a load balancing algorithm to solve the bottleneck problem of deploying a cloud system. We implement a prototype, and evaluate it with 16 physical nodes as well as a virtualized environment with 160 virtual machines. Experimental results show that the average deployment time under our approach is lower than that with traditional deployment methods. In addition, it achieves a cloud system deployment success ratio of up to 90%, even in the high-concurrency environment. © Springer international Publishing Switzerland 2015.

关键词： cloud computing

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15th international conference on Computer Aided Systems Theory, EUROCAST 2015

15th International Conference on Computer Aided Systems Theo...

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15th international conference on Computer Aided Systems Theory, EUROCAST 2015

ISBN: (纸本)9783319273396

The proceedings contain 107 papers. The special focus in this conference is on Systems Theory and Applications. The topics include: A simple linearisation of the self-shrinking generator;systems theory and model of diversification in building of information systems;time sub-optimal control of triple integrator applied to real three-tank hydraulic system;use of the automatic identification system in academic research;application of multi-valued decision diagrams in computing the direct partial logic derivatives;identification of first order plants by relay feedback with non-symmetrical oscillations;managing certificate revocation in VANETs using hash trees and query frequencies;constrained pole assignment control for a 2nd order oscillatory system;parallel and distributed metaheuristics;dynamic similarity and distance measures based on quantiles;eulerian numbers weigths in distributed computing nets;autonomous paracopter control design;a class of 3-D distributed modular computing nets;standardized mapping model for heritage preservation and serendipity in cloud;structuring the model of complex system using parallel computing techniques;some remarks on first-passage times for integrated gauss-markov processes;a sequential test for evaluating air quality;population models and enveloping;fractional growth process with two kinds of jumps;towards stochastic modeling of neuronal interspike intervals including a time-varying input signal;a cancer dynamics model for an intermittent treatment involving reduction of tumor size and rise of growth rate;on time non-homogeneous feller-type diffusion process in neuronal modeling and a practical experience on reusing problem-solving methods for assessment tasks.

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Survey on software-defined networking 2nd

Survey on software-defined networking

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2nd international conference on cloud computing and Big Data, cloudCom-Asia 2015

作者： Chen, Jiangyong Zheng, Xianghan Rong, Chunming College of Mathematics and Computer Science Fuzhou University Fuzhou350108 China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou350108 China Department of Computer Science and Electronic Engineering University of Stavanger Stavanger Norway

ISBN: (纸本)9783319284293

Recently, both the academia and industry have initiated research directed toward the integration of software-defined networking (SDN) technologies into the next generation of networking. In this paradigm, SDN transfers the control function from the traditional distributed network equipment to the controllable computing devices, which makes the underlying network infrastructure abstract to network services and applications. In this study, we survey Open Flow-based SDN solutions that were recently proposed in both academia and industry. We consider technical issues, including SDN requirement, Open Flow-based approach, challenges, and possible approaches. In addition, security breaches and possible solutions are described. Our survey is based on recent research publications. © Springer international Publishing Switzerland 2015.

关键词： Software defined networking

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Optimal task scheduling in cloud computing environment: Meta heuristic approaches

Optimal task scheduling in cloud computing environment: Meta...

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international conference on Electrical Information and Communication Technology (EICT)

作者： Tripti Mandal Sriyankar Acharyya Computer Science and Engineering West Bengal University of Technology Kolkata West Bengal India

cloud computing is the latest continuation of parallel computing, distributed computing and grid computing. In this system, user can make use of different services like storage, servers and other applications. cloud resources are not only used by numerous users but are also dynamically redistributed on demand. Requested services are delivered to user's computers and devices through the Internet. The fundamental issue in cloud computing system is related to task scheduling where a scheduler finds an optimal solution in cost-effective manner. Task scheduling issue is mainly focus on to find the best or optimal resources in order to minimize the total processing time of Virtual Machines (VMs). cloud task scheduling is an NP-hard problem. The focus is on increasing the efficient use of the shared resources. A number of meta-heuristic algorithms have been implemented to solve this issue. In this work three meta-heuristic techniques such as Simulated Annealing, Firefly Algorithm and Cuckoo Search Algorithm have been implemented to find an optimal solution. The main goal of these algorithms is to minimize the overall processing time of the VMs which execute a set of tasks. The experimental result shows that Firefly Algorithm (FFA) performs better than Simulated Annealing and Cuckoo Search Algorithm.

关键词： cloud computing Optimal scheduling Simulated annealing Processor scheduling Algorithm design and analysis Mathematical model Software algorithms

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Smart grid DNP3 Vulnerability Analysis and Experimentation

Smart Grid DNP3 Vulnerability Analysis and Experimentation

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IEEE international conference on Cyber Security and cloud computing (CScloud)

作者： Ihab Darwish Obinna Igbe Orhan Celebi Tarek Saadawi Joseph Soryal Electrical Engineering Department City University of New York

ISBN: (纸本)9781467393010

This paper highlights different security threats and vulnerabilities that is being challenged in smart-grid utilizing distributed Network Protocol (DNP3) as a real time communication protocol. Experimentally, we will demonstrate two scenarios of attacks, unsolicited message attack and data set injection. The experiments were run on a computer virtual environment and then simulated in DETER testbed platform. The use of intrusion detection system will be necessary to identify attackers targeting different part of the smart grid infrastructure. Therefore, mitigation techniques will be used to ensure a healthy check of the network and we will propose the use of host-based intrusion detection agent at each Intelligent Electronic Device (IED) for the purpose of detecting the intrusion and mitigating it. Performing attacks, attack detection, prevention and counter measures will be our primary goal to achieve in this research paper.

关键词： Protocols Smart grids Authentication Computers TCPIP Standards

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Energy-Efficient VM Scheduling in IaaS clouds 2nd

Energy-Efficient VM Scheduling in IaaS Clouds

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2nd international conference on Future Data and Security engineering (FDSE) / 9th international conference on Advanced computing and Applications (ACOMP)

作者： Nguyen Quang-Hung Nam Thoai HCMC Univ Technol Fac Comp Sci & Engn VNUHCM 268 Ly Thuong Kiet St Ho Chi Minh City Vietnam

ISBN: (纸本)9783319261355;9783319261348

This paper investigates the energy-aware virtual machine (VM) scheduling problems in IaaS clouds. Each VM requires multiple resources in fixed time interval and non-preemption. Many previous researches proposed to use a minimum number of physical machines;however, this is not necessarily a good solution to minimize total energy consumption in the VM scheduling with multiple resources, fixed starting time and duration time. We observe that minimizing total energy consumption of physical machines in the scheduling problems is equivalent to minimizing the sum of total busy time of all active physical machines that are homogeneous. Based on these observations, we proposed ETRE algorithm to solve the scheduling problems. The ETRE algorithm's swapping step swaps an allocating VM with a suitable overlapped VM, which is of the same VM type and is allocated on the same physical machine, to minimize total busy time of all physical machines. The ETRE uses resource utilization during executing time period of a physical machine as the evaluation metric, and will then choose a host that minimizes the metric to allocate a new VM. In addition, this work studies some heuristics for sorting the list of virtual machines (e.g., sorting by the earliest starting time, or the longest duration time first, etc.) to allocate VM. Using log-traces in the Feitelson's parallel Workloads Archive, our simulation results show that the ETRE algorithm could reduce total energy consumption average by 48% compared to power-aware best-fit decreasing (PABFD [6]) and 49% respectively to vector bin-packing norm-based greedy algorithms (VBP-Norm-L1/L2 [15]).

关键词： IaaS cloud Virtual machine scheduling Energy efficiency cloud computing Total busy time Fixed interval

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Application Performance Analysis of distributed File Systems under cloud computing Environment

Application Performance Analysis of Distributed File Systems...

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international conference on Information Science and Control engineering (ICISCE)

作者： Tiezhu Zhao Zusheng Zhang Xin Ao Computer College Dongguan University of Technology Dongguan P.R. China

ISBN: (纸本)9781467368513

The processing efficiency of data-intensive application on Hadoop with the general-purpose distributed file system such as Lustre, as the backend file system, is not clear. This paper focuses on the similarities and differences between Lustre and HDFS (Hadoop distributed File System). We propose a Hadoop-Lustre platform and evaluate the performance differences of Lustre and HDFS by using a set of data-intensive computing benchmarks. Experimental results indicate Lustre can reach parity with HDFS, or even better than HDFS if the much faster network interconnect is available. It is necessary to study non-HDFS distributed file system to make up the performance lack of HDFS in some MapReduce-based application scenarios.

关键词： File systems Benchmark testing cloud computing Performance evaluation Computers Memory distributed databases

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