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International Conference on Advanced Computing, ICAC

作者： C. Chandra Sekhar Sasi Kumar Madhan Subhas Raj Kumar Buyya Department of Computer Science and Engineering Indian Institute of Technology Madras CDAC Pune Chronus Corporation Computer Science and Software Engineering and Director of the Cloud Computing and Distributed Systems (CLOUDS) Laboratory at the University of Melbourne Australia

Support vector machine (SVM) is a pattern classification model suitable for classification and annotation of images using non-vectorial type representations of images. Varying length patterns extracted from image data correspond to sets of local feature vectors. Kernels designed for varying length patterns are called as dynamic kernels. The talk presents the issues in designing the dynamic kernel based SVMS for classification and annotation of images. Different methods for designing the dynamic kernels are presented. An intermediate matching kernel (IMK) for a pair of varying length patterns is constructed by matching the pairs of local feature vectors selected using a set of virtual feature vectors. For patterns corresponding to sets of feature vectors, a Gaussian mixture model (GMM) is used as the set of virtual feature vectors. The GMM-based IMK is considered for image processing tasks such as image classification, matching and annotation in content-based image retrieval. The talk presents results of experimental studies on image classification, annotation and retrieval of images using the kernel methods.

关键词： Cloud computing Kernel Technological innovation Support vector machine classification Learning systems Hidden Markov models Computational modeling

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NetworkCloudSim: Modelling Parallel Applications in Cloud Simulations

NetworkCloudSim: Modelling Parallel Applications in Cloud Si...

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IEEE International Conference on Utility and Cloud Computing (UCC)

作者： Saurabh Kumar Garg Rajkumar Buyya Cloud Computing and Distributed Systems (CLOUDS) Laboratory Department of Computer Science and Software Engineering University of Melbourne Australia

As interest in adopting Cloud computing for various applications is rapidly growing, it is important to understand how these applications and systems will perform when deployed on Clouds. Due to the scale and complexity of shared resources, it is often hard to analyze the performance of new scheduling and provisioning algorithms on actual Cloud test beds. Therefore, simulation tools are becoming more and more important in the evaluation of the Cloud computing model. Simulation tools allow researchers to rapidly evaluate the efficiency, performance and reliability of their new algorithms on a large heterogeneous Cloud infrastructure. However, current solutions lack either advanced application models such as message passing applications and workflows or scalable network model of data center. To fill this gap, we have extended a popular Cloud simulator (CloudSim) with a scalable network and generalized application model, which allows more accurate evaluation of scheduling and resource provisioning policies to optimize the performance of a Cloud infrastructure.

关键词： Computational modeling Data models Cloud computing Network topology Bandwidth Processor scheduling Virtual machining

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Resource Provisioning Policies to Increase IaaS Provider's Profit in a Federated Cloud Environment

Resource Provisioning Policies to Increase IaaS Provider's P...

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IEEE International Conference on High Performance Computing and Communications (HPCC)

作者： Adel Nadjaran Toosi Rodrigo N. Calheiros Ruppa K. Thulasiram Rajkumar Buyya Cloud Computing and Distributed Systems (CLOUDS) Laboratory Department of Computer Science and Software Engineering University of Melbourne Australia Department of Computer Science University of Manitoba Canada

Cloud Federation is a recent paradigm that helps Infrastructure as a Service (IaaS) providers to overcome resource limitation during spikes in demand for Virtual Machines (VMs) by outsourcing requests to other federation members. IaaS providers also have the option of terminating spot VMs, i.e, cheaper VMs that can be canceled to free resources for more profitable VM requests. By both approaches, providers can expect to reject less profitable requests. For IaaS providers, pricing and profit are two important factors, in addition to maintaining a high Quality of Service (QoS) and utilization of their resources to remain in the business. For this, a clear understanding of the usage pattern, types of requests, and infrastructure costs are necessary while making decisions to terminate spot VMs, outsourcing or contributing to the federation. In this paper, we propose policies that help in the decision-making process to increase resources utilization and profit. Simulation results indicate that the proposed policies enhance the profit, utilization, and QoS (smaller number of rejected VM requests) in a Cloud federation environment.

关键词： Outsourcing Quality of service Mathematical model Equations Pricing Computational modeling Availability

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QoS-aware Deployment of Network of Virtual Appliances Across Multiple Clouds

QoS-aware Deployment of Network of Virtual Appliances Across...

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IEEE International Conference on Cloud Computing Technology and science (CloudCom)

作者： Amir Vahid Dastjerdi Saurabh Kumar Garg Rajkumar Buyya Cloud Computing and Distributed Systems (CLOUDS) Laboratory Department of Computer Science and Software Engineering University of Melbourne Parkville VIC Australia

Cloud computing paradigm allows on-demand access to computing and storages services over the Internet. To solve the complexity of application deployment in Cloud infrastructure, virtual appliances, pre-configured, ready-to-run applications are emerging as a breakthrough technology. However, an automated approach for deploying network of appliances is required to guarantee minimum deployment cost, low latency, and high reliability. In this paper, we propose and compare two different deployment approaches: Forward-checking-based backtracking (FCBB) and genetic-based. They take into account Quality of Service (QoS) criteria such as reliability, data communication cost, and latency between multiple Clouds to choose the most appropriate combination of virtual machines and appliances. We evaluate our approach using a real case study and different request types. Experimental results show both algorithms reach near optimal solution. Further, we investigate effects of factors such as latency requirements, and data communication between appliances on the performance of the algorithms and placement of appliances across multiple Clouds.

关键词： Home appliances Quality of service Servers Monitoring Cloud computing Availability

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SMICloud: A Framework for Comparing and Ranking Cloud Services

SMICloud: A Framework for Comparing and Ranking Cloud Servic...

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IEEE International Conference on Utility and Cloud Computing (UCC)

作者： Saurabh Kumar Garg Steve Versteeg Rajkumar Buyya Cloud Computing and Distributed Systems (CLOUDS) Laboratory Department of Computer Science and Software Engineering University of Melbourne Australia CA Technologies Melbourne Australia

With the growth of Cloud Computing, more and more companies are offering different cloud services. From the customer's point of view, it is always difficult to decide whose services they should use, based on users' requirements. Currently there is no software framework which can automatically index cloud providers based on their needs. In this work, we propose a framework and a mechanism, which measure the quality and prioritize Cloud services. Such framework can make significant impact and will create healthy competition among Cloud providers to satisfy their Service Level Agreement (SLA) and improve their Quality of Services (QoS).

关键词： Quality of service Time factors Cloud computing Organizations Measurement Security Indexes

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A comparison of Wireless Fidelity (Wi-Fi) fingerprinting techniques

A comparison of Wireless Fidelity (Wi-Fi) fingerprinting tec...

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International Conference on Information and Communication Technology Convergence (ICTC)

作者： Lersan B. Del Mundo Rafael Lean D. Ansay Cedric Angelo M. Festin Roel M. Ocampo Networks and Distributed Systems Laboratory Department of Computer Science University of the Philippines Diliman Quezon Philippines Computer Networks Lab Electrical and Electronics Engineering Institute University of the Philippines Diliman Quezon Philippines

Among several techniques proposed for indoor positioning using IEEE 802.11 Wireless Fidelity (Wi-Fi) based networks, those that rely on fingerprinting have been demonstrated to outperform those based on lateration, angulation, and cell of origin in terms of accuracy. We compare and evaluate three Wi-Fi fingerprinting techniques that use the K-Nearest Neighbor (k-NN), Naive Bayes Classifier (NBC) and Support Vector Machine (SVM) algorithms. Our experiments show that SVM-based fingerprinting outperformed both k-NN and NBC-based fingerprinting, achieving accuracies of 2 meters or better within our testbed.

关键词： Accuracy Support vector machines IEEE 802.11 Standards Vectors Databases Fingerprint recognition Kernel

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Persistent Ocean Monitoring with Underwater Gliders: Towards Accurate Reconstruction of Dynamic Ocean Processes

Persistent Ocean Monitoring with Underwater Gliders: Towards...

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2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)

作者： Ryan N. Smith Mac Schwager Daniela Rus Stephen L. Smith Gaurav S. Sukhatme School of Engineering Systems at the Queensland University of Technology BrisbaneQLD4000 Australia GRASP Lab University of PennsylvaniaPhiladelphiaPA 19104USA Distributed Robotics Lab Computer Science and Artificial Intelligence LaboratoryMassachusetts Insti Robotic Embedded Systems Laboratory Department of Computer ScienceUniversity of Southern California

This paper proposes a path planning algorithm and a velocity control algorithm for underwater gliders to persistently monitor a patch of ocean. The algorithms address a pressing need among ocean scientists to collect high-value data for studying ocean events of scientific and environmental interest, such as the occurrence of harmful algal blooms. The path planner optimizes a cost function that blends two competing factors: it maximizes the information value of the path, while minimizing the deviation from the path due to ocean currents. The speed control algorithm then optimizes the speed along the planned path so that higher resolution samples are collected in areas of higher information value. The resulting paths are closed circuits that can be repeatedly traversed to collect long term ocean data in dynamic environments. The algorithms were tested during sea trials on an underwater glider operating off the coast of southern California over the course of several weeks. The results show significant improvements in data resolution and path reliability compared to a sampling path that is typically used in the region.

关键词： Oceans Heuristic algorithms Vehicles Monitoring Sea measurements Vehicle dynamics Read only memory

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Wide area distributed file systems-A scalability and performance survey

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Scalable Computing 2010年第3期11卷 305-326页

作者： Ponnavaikko, Kovendhan Dharanipragada, Janakiram Distributed and Object Systems Lab Department of Computer Science and Engineering Indian Institute of Technology Madras Chennai India

Recent decades have witnessed an explosive growth in the amounts of digital data in various fields of arts, science and engineering. Such data is generally of interest to a large number of people spread over wide geographical areas. Over the years, several distributed File systems (DFS) have, to varying degrees, addressed this requirement of sharing large amounts of data, stored in the form of files, among several users and applications. Scalability and performance are two important measures that determine the suitability of a file system for the applications executing over them. We perform a detailed comparative analysis of popular distributed file systems in terms of these measures in our survey. © 2010 SCPE.

关键词： Surveys

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A taxonomy of autonomic application management in grids

A taxonomy of autonomic application management in grids

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16th IEEE International Conference on Parallel and distributed systems, ICPADS 2010

作者： Rahman, Mustafizur Ranjan, Rajiv Buyya, Rajkumar Cloud Computing and Distributed Systems Laboratory Department of Computer Science and Software Engineering University of Melbourne Australia Service Oriented Computing Research Group School of Computer Science and Engineering University of New South Wales Australia

ISBN: (纸本)9780769543079

In this paper, we propose a taxonomy that characterizes and classifies different components of autonomic application management in Grids. We also survey several representative Grid systems developed by various projects world-wide to demonstrate the comprehensiveness of the taxonomy. The taxonomy not only highlights the similarities and differences of state-of-the-art technologies utilized in autonomic application management from the perspective of Grid computing, but also identifies the areas that require further research initiatives. © 2010 IEEE.

关键词： Surveys

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Optimizing Service Level Agreements for Autonomic Cloud Bursting Schedulers

Optimizing Service Level Agreements for Autonomic Cloud Burs...

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International Conference on Parallel Processing Workshops (ICPPW)

作者： Sriram Kailasam Nathan Gnanasambandam Janakiram Dharanipragada Naveen Sharma Distributed and Object Systems Laboratory Department of Comp. Science and Engineering Indian Institute of Technology Madras Chennai India Xerox Research Center Webster Xerox Corporation Webster NY USA

The practice of computing across two or more data centers separated by the Internet is growing in popularity due to an explosion in scalable computing demands and pay-as-you-go schemes offered on the cloud. While cloud-bursting is addressing this process of scaling up and down across data centers (i.e. between private and public clouds), offering service level guarantees, is a challenge for inter-cloud computation, particularly for best-effort traffic and large files. The parallel workload we address is real-time and involves inter-cloud processing and analysis of images and documents. In our production printing domain, dedicated processing/network resources are cost-prohibitive. Further, the problem is exacerbated by data intensive computing - we encounter huge file sizes atypical of intercloud parallel processing. To address these problems we propose three flavors of autonomic cloud-bursting schedulers that offer probabilistic guarantees on service levels required by customers (such as speed-up and queue sequence preservation) by adapting to changing workload characteristics, variation in bandwidth and available resources. In particular, these opportunistic schedulers use a quadratic response surface model for processing time in concert with a time-of-day dependent bandwidth predictor to increase the throughput and utilization while simultaneously reducing out-of-sequence completions for a document processing workload.

关键词： Clouds Bandwidth Integrated circuits Measurement Out of order Response surface methodology Real time systems

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