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Multi-cloud DRaaS using OpenStack Keystone Federation

Multi-cloud DRaaS using OpenStack Keystone Federation

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International Conference on Advances in computing and Communication Engineering (ICACCE)

作者： Sudheendra Harwalkar Dinkar Sitaram Shivangi Jadon Center for Cloud Computing and Big Data PES University Bangalore India

ISBN: (数字)9781728132501

ISBN: (纸本)9781728132518

Disaster recovery (DR) for the distributed workload and data in multi-cloud environments is very complex and challenging. There exist point tools for failover from one cloud to another cloud with active/passive data replications or with simple backup of private cloud data to public cloud(s). However, these point solutions are not integrated with the cloud environment. In this paper, we demonstrate how cost-effective DR process/solution can be accomplished with our Federated cloud Services Framework (middleware), which is built upon OpenStack [16], by leveraging existing OpenStack functionalities. As our solution leverages the functionality of the federated cloud environment, it generalizes easily to multi-cloud scenarios, and is better integrated with the cloud infrastructure. We also compare our solution to current DR process/solutions available in the market.

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Multicloud- auto scale with prediction and delta correction algorithm

Multicloud- auto scale with prediction and delta correction ...

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International Conference on Intelligent computing, Instrumentation and Control Technologies (ICICICT)

作者： Sudheendra Harwalkar Dinkar Sitaram Dhanaraj V Kidiyoor Milan M L Ornella D'souza Radhika Agarwal Yamini Agarwal Center for Cloud Computing and Big Data PES University Bangalore India

IT enabled enterprise organizations are embracing multi-cloud to handle their peak loads in addition to their private cloud (own data centers) and the market prediction indicates that by year 2020, about 80% of enterprise will have or working towards multi-cloud enablement for their IT needs. There are multiple products from third-party supporting multi-cloud and also some of the cloud service providers have already enabled the service using proprietary cloud management tools with custom built plug-ins. One of the major challenges in multi-cloud is efficient resource utilization and cost savings without vendor/broker lock-in. At present, multi-cloud interface standardization is still in draft. In this paper we propose handling of cloud burst at peak load with our OpenStack [9] Middleware Framework, which uses default OpenStack services. It also has built-in support for prediction, resource allocation and proactive workload migration techniques which can be integrated easily with cloud provider solutions.

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Security analysis oriented physical components modeling in quantum key distribution 1

引用

1st International Symposium on Mobile Internet Security, MobiSec 2016

作者： Mao, Xilong Li, Yan Peng, Yan Zhao, Baokang College of Computer National University of Defense Technology Changsha410073 China Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex Systems Guilin University of Electronic Technology Guilin541004 China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guilin541004 China

ISBN: (数字)9789811078507

ISBN: (纸本)9789811078491

Quantum Key Distribution (QKD), based on fundamental principles of quantum mechanics, plays an irreplaceable role in national defense, financial and government affairs. Security analysis of QKD system is of great importance. However, existing studies on modeling QKD system are theory analysis based. In this paper, we propose a Simulation System of Physical Components (SSPC) in QKD system which modeling the three key modules: single photon source, quantum channel and single photon detector, it could generate the simulated key resemble to real QKD physical system and its parameters of the physical components are configurable. Therefore, solution can be deployed in different QKD physical systems. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Quantum cryptography

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A Fast Geometric Modeling Method for Cold Blades 1

引用

Asia-Pacific International Symposium on Aerospace Technology, APISAT 2018

作者： Liu, Kaicheng Wang, Jianjun Ni, Bowen School of Energy and Power Engineering Beihang University Beijing100191 China Cloud Computing and Big Data Center China Mobile Group Xinjiang Company Limited Xinjiang830018 China

ISBN: (数字)9789811333057

ISBN: (纸本)9789811333040

A geometric modeling method for cold blade is proposed based on hot-to-cold finite element (FE) transformation calculation. The main idea is to interpolate the deformation result calculated from hot-to-cold transformation to the control points of the hot blade profile. Subtract the interpolated displacement values from the coordinates of the hot control points then the coordinates of the cold control points are obtained. The resulting coordinates could be directly used for solid modeling in commercial CAD programs. Both the hot-to-cold FE transformation calculation part and the output part of the cold blade profile’s control point coordinates could be accomplished in a whole process automatically in the commercial FE program ANSYS15.0. The flow chart of the entire process is given attached with ANSYS APDL commands. Finally, a numerical example based on a blisk sector model is provided. The hot-to-cold FE transformation calculation is performed, the finite element model (FEM) is obtained and solid model is built. Additionally, the effect of mesh density on the modeling accuracy is investigated. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Computer aided design

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Sentiment analysis of mixed language employing Hindi-English code switching

Sentiment analysis of mixed language employing Hindi-English...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Dinkar Sitaram Savitha Murthy Debraj Ray Devansh Sharma Kashyap Dhar Center for Cloud computing and Big Data (CCBD) PES University Bangalore

Sentiment analysis has emerged as one of the prominent research branches because of its endless usages and applications. Monitoring social media, forums, blogs and other online resources for customer reviews, product competition and survey responses to understand customer insight is of significant importance in business analytics. With the proliferation of informal user generated data online, the use of mixed language has become a common phenomenon. Mixed language arises through the use of linguistic code switching (LCS) or the practice of using more than one language in a single sentence. Such mixed language has rarely been a subject of sentiment analysis before. The lack of a clear grammatical structure renders the previous approaches to sentiment analysis ineffective for such text. In this paper, we propose a strategy to determine the sentiment of sentences written in a mixed language comprising of Hindi and English lexicons. Our technique can be used to analyze the sentiment of data belonging to any one of the source languages as well as the mixed language data. Grammatical transitions which are very common in mixed language have been taken into account during the sentiment analysis. We demonstrate the effectiveness of the proposed approach via case studies on social media data sets.

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DCSim: Cooling Energy Aware VM Allocation Framework for a cloud data center

DCSim: Cooling Energy Aware VM Allocation Framework for a Cl...

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International Conference on Advances in computing and Communication Engineering (ICACCE)

作者： Priyank Bhandia Ravi S. Anupindi Pavan Yekbote Nikhil Singh H.L. Phalachandra Dinkar Sitaram Center for Cloud Computing and Big Data PES University Bangalore India

ISBN: (数字)9781728132501

ISBN: (纸本)9781728132518

Explosion of digital content has resulted in large amounts of resources being provisioned and managed for various applications in cloud data centers. Energy consumption in these large cloud data centers is a rising concern, accounting for 1.3% of the worlds electricity consumption [1]. data center cooling accounts for 40% of this energy consumption [2]. Of the various mechanisms available for studying the energy consumption in data centers, a simulation based approach is quite popular. In this paper, we propose DCSim, a configurable extension to cloudSim, a popularly used cloud infrastructure and simulation framework. cloudSim provides coarse power models to calculate total energy consumption in a data center for a given workload, but has no provision to factor in the data center topology and current cooled area into this power model. This makes building intelligent cooling energy aware allocation policies in cloudSim difficult. In DCSim, we introduce a novel data center model that addresses the shortcomings of cloudSim by encapsulating concepts of Racks, Aisles, Sectors and Zones (collectively referred to as DCObjects). We also provide the capability to model the cooling of these DCObjects. This makes the study of cooling aware resource provisioning for workloads easier. The DCObjects and the data center model presented are designed to be fully extensible to support future developments in this area. In this work we also implement a Cooling aware VM allocation policy, and demonstrate using multiple algorithms, that this VM allocation policy will effectively reduce the total data center power consumption by 18.18% over an algorithm which does not factor in the cooled DCObjects.

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Predicting Virtual Machine Resource Consumption Based on Optimized Grey Model

Predicting Virtual Machine Resource Consumption Based on Opt...

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第二届先进电子材料、计算机与材料工程国际学术会议（AEMCME 2019）

作者： Shi Aiwu Gao Di He Kai Cloud Computing and Big Data Research Center Wuhan Textile University

In order to relatively change the computing specifications of virtual machines(VMs for short) for the changing resource consumption of VMs, and reduce the impact of the changes, this paper proposes the optimized grey GM(1, 1) model to predict the resource consumption of VMs. Because VM resources may fluctuate greatly in a short time, the initial data are smoothed first, and then modeled, the model edge value is optimized according to the characteristics of cloud environment. Experiments show that the accuracy and stability of the prediction model can be improved by sorting out the initial data and optimizing the model. The prediction value is helpful to design the allocation scheme of VM resources, improve the utilization rate of physical resources in cloud environment.

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Predicting the Next Move: Determining Mobile User Location using Semantic Information

Predicting the Next Move: Determining Mobile User Location u...

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International Conference on Advances in computing, Communications and Informatics

作者： Nitin Bhyri Gautham V. Kidiyoor Varun, S. K. Subramaniam Kalambur Dinkar Sitaram Chid Kollengode Center of Cloud Computing and Big Data PES Institute of technology DataXu

ISBN: (纸本)9781479987931

The location of a mobile user is used to deliver context sensitive information like advertisements and deals. Predicting the future possible locations of a mobile user can help target specific services. Nokia provided researchers with data collected from around 200 mobile users over a period of about 2 years for the purpose of research. Previous efforts have attempted either to predict the location of the user or the semantics associated with a location. In our work, we demonstrate that using a multi-level approach by predicting the semantics of a location and then the specific location within helps improve the accuracy of the prediction. We have shown that for certain semantic locations, the prediction accuracy can be as high as 90%.

关键词： Mobile User Semantic Location

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Automatic 3D modeling and exploration of indoor structures from panoramic imagery 24

Automatic 3D modeling and exploration of indoor structures f...

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2024 SIGGRAPH Asia 2024 Courses, SA Courses 2024

作者： Gobbetti, Enrico Pintore, Giovanni Agus, Marco National Research Center in High-Performance Computing Big Data and Quantum Computing Cagliari Italy Visual and Data-intensive Computing Center for Advanced Studies Research and Development in Sardinia Cagliari Italy College of Science and Engineering Hamad Bin Khalifa University Doha Qatar

ISBN: (纸本)9798400711350

Surround-view panoramic imaging delivers extensive spatial coverage and is widely supported by professional and commodity capture devices. Research on inferring and exploring 3D indoor models from 360° images has recently flourished, resulting in highly effective solutions. Nevertheless, challenges persist due to the complexity and variability of indoor environments and issues with noisy and incomplete data. This course provides an up-to-date integrative view of the field. After introducing a characterization of input sources, we define the structure of output models, the priors exploited to bridge the gap between imperfect input and desired output, and the main characteristics of geometry reasoning and data-driven approaches. We then identify and discuss the main sub-problems in indoor reconstruction from panoramas and review and analyze state-of-the-art solutions for indoor capture, room modeling, integrated model computation, visual representation generation, and immersive exploration. Relevant examples of implemented pipelines are described, focusing on deep-learning solutions. We finally point out relevant research issues and analyze research trends. © 2024 Copyright held by the owner/author(s).

关键词： 3D reconstruction

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GraSU: A fast graph update library for fpga-based dynamic graph processing 21

GraSU: A fast graph update library for fpga-based dynamic gr...

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2021 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, FPGA 2021

作者： Wang, Qinggang Zheng, Long Huang, Yu Yao, Pengcheng Gui, Chuangyi Liao, Xiaofei Jin, Hai Jiang, Wenbin Mao, Fubing National Engineering Research Center for Big Data Technology and System Service Computing Technology and System Lab Cluster and Grid Computing Lab Huazhong University of Science and Technology China

ISBN: (纸本)9781450382182

Existing FPGA-based graph accelerators, typically designed for static graphs, rarely handle dynamic graphs that often involve substantial graph updates (e.g., edge/node insertion and deletion) over time. In this paper, we aim to fill this gap. The key innovation of this work is to build an FPGA-based dynamic graph accelerator easily from any off-the-shelf static graph accelerator with minimal hardware engineering efforts (rather than from scratch). We observe\em spatial similarity of dynamic graph updates in the sense that most of graph updates get involved with only a small fraction of vertices. We therefore propose an FPGA library, called GraSU, to exploit spatial similarity for fast graph updates. GraSU uses a differential data management, which retains the high-value data (that will be frequently accessed) in the specialized on-chip UltraRAM while the overwhelming majority of low-value ones reside in the off-chip memory. Thus, GraSU can transform most of off-chip communications arising in dynamic graph updates into fast on-chip memory accesses. Our experiences show that GraSU can be easily integrated into existing state-of-the-art static graph accelerators with only 11 lines of code modifications. Our implementation atop AccuGraph using a Xilinx Alveo#8482;\U250 board outperforms two state-of-the-art CPU-based dynamic graph systems, Stinger and Aspen, by an average of 34.24× and 4.42× in terms of update throughput, improving further overall efficiency by 9.80× and 3.07× on average. © 2021 ACM.

关键词： Field programmable gate arrays (FPGA)

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