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SmartVM: A Multi-Layer Microservice-Based Platform for Deploying SaaS

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SmartVM: A Multi-Layer Microservice-Based Platform for Deplo...

IEEE International Symposium on Parallel and Distributed Processing with Applications and IEEE International Conference on Ubiquitous computing and Communications (ISPA/IUCC)

作者： Xi Zheng Jiaojiao Jiang Yuqun Zhang Yao Deng Min Fu Tianlei Zheng Xiao Liu Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China School of Software and Electrical Engineering Swinburne University of Technology Melbourne Australia School of Information Technology Deakin University Melbourne Australia Data61 CSIRO Sydney Australia School of Computing and Information Systems The University of Melbourne Melbourne Australia

ISBN: (纸本)9781538637913

With the advent of Software-as-a-Service (SaaS), SaaS developers are facing many challenges associated with the multi-tenancy and the dramatically increased number of users. In order to achieve resource-optimized, on-demand dynamic scaling across multiple tenants, and reduce costs, in this paper, a new platform, named SmartVM, is created to enable SaaS developer to create, customize, and deploy SaaS solutions in a multi-tier microservice-based manner. We develop an e-commerce SaaS prototype to evaluate effectiveness and efficiency of SmartVM. The results show that the SmartVM deployments outperforms the conventional monolithic and microservice deployments in smart monitoring, cost reduction, and resource optimization.

关键词： Containers Monitoring Business Software as a service Australia Scalability Measurement

Active self-paced learning for cost-effective and progressive face identification

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arXiv 2017年

作者： Lin, Liang Wang, Keze Meng, Deyu Zuo, Wangmeng Zhang, Lei School of Data and Computer Science Sun Yat-sen University Guangzhou China Engineering Research Center Advanced Computing Engineering Software of Ministry of Education China School of Mathematics and Statistics Ministry of Education Key Lab of Intelligent Networks and Network Security Xi'an Jiaotong University China School of Computer Science and Technology Harbin Institute of Technology Harbin China Dept. of Computing Hong Kong Polytechnic University Hong Kong

This paper aims to develop a novel cost-effective framework for face identification, which progressively maintains a batch of classifiers with the increasing face images of different individuals. By naturally combining two recently rising techniques: active learning (AL) and self-paced learning (SPL), our framework is capable of automatically annotating new instances and incorporating them into training under weak expert recertification. We first initialize the classifier using a few annotated samples for each individual, and extract image features using the convolutional neural nets. Then, a number of candidates are selected from the unannotated samples for classifier updating, in which we apply the current classifiers ranking the samples by the prediction confidence. In particular, our approach utilizes the high-confidence and low-confidence samples in the self-paced and the active user-query way, respectively. The neural nets are later fine-tuned based on the updated classifiers. Such heuristic implementation is formulated as solving a concise active SPL optimization problem, which also advances the SPL development by supplementing a rational dynamic curriculum constraint. The new model finely accords with the "instructor-student-collaborative" learning mode in human education. The advantages of this proposed framework are two-folds: i) The required number of annotated samples is significantly decreased while the comparable performance is guaranteed. A dramatic reduction of user effort is also achieved over other state-of-the-art active learning techniques. ii) The mixture of SPL and AL effectively improves not only the classifier accuracy compared to existing AL/SPL methods but also the robustness against noisy data. We evaluate our framework on two challenging datasets, which include hundreds of persons under diverse conditions, and demonstrate very promising results. Please find the code of this project at: http://***/projects/aspl/ Copyright © 201

关键词： Cost effectiveness

Dense small cell networks: From noise-limited to dense interference-limited

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arXiv 2017年

作者： Yang, Bin Mao, Guoqiang Ding, Ming Ge, Xiaohu Tao, Xiaofeng School of Electronic Information and Communications Huazhong University of Science and Technology China School of Computing and Communication University of Technology Sydney Australia Data61 CSIRO Australia National Engineering Lab. for Mobile Network Security Beijing University of Posts and Telecommunications China

Considering both non-line-of-sight (NLoS) and line-of-sight (LoS) transmissions, the transitional behaviors from noise-limited regime to dense interference-limited regime have been investigated for the fifth generation (5G) small cell networks (SCNs). Besides, we identify four performance regimes based on base station (BS) density, i.e., (i) the noise-limited regime, (ii) the signal-dominated regime, (iii) the interference-dominated regime, and (iv) the interference-limited regime. To characterize the performance regime, we propose a unified framework analyzing the future 5G wireless networks over generalized shadowing/fading channels, in which the user association schemes based on the strongest instantaneous received power (SIRP) and the strongest average received power (SARP) can be studied, while NLoS/LoS transmissions and multi-slop path loss model are considered. Simulation results indicate that different factors, i.e., noise, desired signal, and interference, successively and separately dominate the network performance with the increase of BS density. Hence, our results shed new light on the design and management of SCNs in urban and rural areas with different BS deployment densities. Copyright © 2017, The Authors. All rights reserved.

关键词： 5G mobile communication systems

An interview based study of pioneering experiences in teaching and learning complex systems in higher education

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arXiv 2018年

作者： Lizier, Joseph T. Harré, Michael S. Mitchell, Melanie DeDeo, Simon Finn, Conor Lindgren, Kristian Lizier, Amanda L. Sayama, Hiroki Centre for Complex Systems Complex Systems Research Group Faculty of Engineering and IT University of Sydney NSW Australia Department of Computer Science Portland State University PortlandOR United States Santa Fe Institute Santa FeNM United States School of Informatics and Computing Indiana University BloomingtonIN United States Department of Social and Decision Sciences Carnegie Mellon University PittsburghPA United States CSIRO Data 61 MarsfieldNSW Australia Department of Space Earth and Environment Chalmers University of Technology Göteborg Sweden School of Education University of Technology Sydney NSW Australia Center for Collective Dynamics of Complex Systems Department of Systems Science and Industrial Engineering Binghamton University State University of New York NY United States

Due to the interdisciplinary nature of complex systems as a field, students studying complex systems at University level have diverse disciplinary backgrounds. This brings challenges (e.g. wide range of computer programming skills) but also opportunities (e.g. facilitating interdisciplinary interactions and projects) for the classroom. However, there is little published regarding how these challenges and opportunities are handled in teaching and learning Complex Systems as an explicit subject in higher education, and how this differs in comparison to other subject areas. We seek to explore these particular challenges and opportunities via an interview-based study of pioneering teachers and learners (conducted amongst the authors) regarding their experiences. We compare and contrast those experiences, and analyse them with respect to the educational literature. Our discussions explored: approaches to curriculum design, how theories/models/frameworks of teaching and learning informed decisions and experience, how diversity in student backgrounds was addressed, and assessment task design. We found a striking level of commonality in the issues expressed as well as the strategies to handle them, for example a significant focus on problem-based learning, and the use of major student-led creative projects for both achieving and assessing learning outcomes. Copyright © 2018, The Authors. All rights reserved.

关键词： Students

Network slicing for service-oriented networks under resource constraints

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arXiv 2017年

作者： Zhang, Nan Liu, Ya-Feng Farmanbar, Hamid Chang, Tsung-Hui Hong, Mingyi Luo, Zhi-Quan School of Mathematical Sciences Peking University State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China Huawei Canada Research Center Ottawa Canada Department of Electrical and Computer Engineering University of Minnesota United States Shenzhen Research Institute of Big Data Chinese University of Hong Kong Shenzhen China

To support multiple on-demand services over fixed communication networks, network operators must allow flexible customization and fast provision of their network resources. One effective approach to this end is network virtualization, whereby each service is mapped to a virtual subnetwork providing dedicated on-demand support to network users. In practice, each service consists of a prespecified sequence of functions, called a service function chain (SFC), while each service function in a SFC can only be provided by some given network nodes. Thus, to support a given service, we must select network function nodes according to the SFC and determine the routing strategy through the function nodes in a specified order. A crucial network slicing problem that needs to be addressed is how to optimally localize the service functions in a physical network as specified by the SFCs, subject to link and node capacity constraints. In this paper, we formulate the network slicing problem as a mixed binary linear program and establish its strong NP-hardness. Furthermore, we propose efficient penalty successive upper bound minimization (PSUM) and PSUM-R(ounding) algorithms, and two heuristic algorithms to solve the problem. Simulation results are shown to demonstrate the effectiveness of the proposed algorithms. Copyright © 2017, The Authors. All rights reserved.

关键词： Network function virtualization

A Multiobjective Approach to Multi-microgrid System Design

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arXiv 2017年

作者： Chiu, Wei-Yu Sun, Hongjian Poor, H. Vincent Department of Electrical Engineering and Innovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan32003 Taiwan School of Engineering and Computing Science Durham University DH1 3LE United Kingdom Department of Electrical Engineering Princeton University PrincetonNJ08544 United States

—The main goal of this study is to design a market operator (MO) and a distribution network operator (DNO) for a network of microgrids in consideration of multiple objectives. This is a high-level design and only those microgrids with nondispatchable renewable energy sources are considered. For a power grid in the network, the net value derived from providing power to the network must be maximized. For a microgrid, it is desirable to maximize the net gain derived from consuming the received power. Finally, for an independent system operator, stored energy levels at microgrids must be maintained as close as possible to storage capacity to secure network emergency operation. To achieve these objectives, a multiobjective approach is proposed: the price signal generated by the MO and power distributed by the DNO are assigned based on a Pareto optimal solution of a multiobjective optimization problem. By using the proposed approach, a fair scheme that does not advantage one particular objective can be attained. Simulations are provided to validate the proposed methodology. Copyright © 2017, The Authors. All rights reserved.

关键词： Smart power grids

Multi-label inductive matrix completion for joint MGMT and IDH1 status prediction for glioma patients 1

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20th International Conference on Medical Image computing and Computer-Assisted Intervention, MICCAI 2017

作者： Chen, Lei Zhang, Han Thung, Kim-Han Liu, Luyan Lu, Junfeng Wu, Jinsong Wang, Qian Shen, Dinggang Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing China Department of Radiology and BRIC University of North Carolina Chapel Hill United States School of Biomedical Engineering Med-X Research Institute Shanghai Jiao Tong University Shanghai China Department of Neurosurgery Huashan Hospital Fudan University Shanghai China Shanghai Key Lab of Medical Image Computing and Computer Assisted Intervention Shanghai China

ISBN: (数字)9783319661858

ISBN: (纸本)9783319661841

MGMT promoter methylation and IDH1 mutation in high-grade gliomas (HGG) have proven to be the two important molecular indicators associated with better prognosis. Traditionally, the statuses of MGMT and IDH1 are obtained via surgical biopsy, which is laborious, invasive and time-consuming. Accurate presurgical prediction of their statuses based on preoperative imaging data is of great clinical value towards better treatment plan. In this paper, we propose a novel Multi-label Inductive Matrix Completion (MIMC) model, highlighted by the online inductive learning strategy, to jointly predict both MGMT and IDH1 statuses. Our MIMC model not only uses the training subjects with possibly missing MGMT/IDH1 labels, but also leverages the unlabeled testing subjects as a supplement to the limited training dataset. More importantly, we learn inductive labels, instead of directly using transductive labels, as the prediction results for the testing subjects, to alleviate the overfitting issue in small-sample-size studies. Furthermore, we design an optimization algorithm with guaranteed convergence based on the block coordinate descent method to solve the multivariate non-smooth MIMC model. Finally, by using a precious single-center multi-modality presurgical brain imaging and genetic dataset of primary HGG, we demonstrate that our method can produce accurate prediction results, outperforming the previous widely-used single- or multi-task machine learning methods. This study shows the promise of utilizing imaging-derived brain connectome phenotypes for prognosis of HGG in a non-invasive manner. © Springer International Publishing AG 2017.

关键词： Forecasting

Empirical data analysis: A new tool for data analytics

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Empirical data analysis: A new tool for data analytics

2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016

作者： Angelov, Plamen Gu, Xiaowei Kangin, Dmitry Principe, Jose Data Science Group School of Computing and Communications Lancaster University Lancaster United Kingdom Computational Neuro Engineering Laboratory Department of Electrical and Computer Engineering University of Florida GrainsvilleFL United States

ISBN: (纸本)9781509018970

In this paper, a novel empirical data analysis approach (abbreviated as EDA) is introduced which is entirely data-driven and free from restricting assumptions and pre-defined problem- or user-specific parameters and thresholds. It is well known that the traditional probability theory is restricted by strong prior assumptions which are often impractical and do not hold in real problems. Machine learning methods, on the other hand, are closer to the real problems but they usually rely on problem- or user-specific parameters or thresholds making it rather art than science. In this paper we introduce a theoretically sound yet practically unrestricted and widely applicable approach that is based on the density in the data space. Since the data may have exactly the same value multiple times we distinguish between the data points and unique locations in the data space. The number of data points, k is larger or equal to the number of unique locations, l and at least one data point occupies each unique location. The number of different data points that have exactly the same location in the data space (equal value), f can be seen as frequency. Through the combination of the spatial density and the frequency of occurrence of discrete data points, a new concept called multimodal typicality, τMM is proposed in this paper. It offers a closed analytical form that represents ensemble properties derived entirely from the empirical observations of data. Moreover, it is very close (yet different) from the histograms, from the probability density function (pdf) as well as from fuzzy set membership functions. Remarkably, there is no need to perform complicated pre-processing like clustering to get the multimodal representation. Moreover, the closed form for the case of Euclidean, Mahalanobis type of distance as well as some other forms (e.g. cosine-based dissimilarity) can be expressed recursively making it applicable to data streams and online algorithms. Inference/estimation of the ty

关键词： Membership functions

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Path ω-automaton

Journal of Information Hiding and Multimedia Signal Processing 2017年第3期8卷 640-648页

作者： Jiang, Hua Zou, Fumin Lin, Rongde Li, Lingxiang Key Lab of Granular Computing Minnan Normal University ZhangzhouFujian China Beidou Navigation and Smart Traffic Innovation Center of Fujian Province FuzhouFujian China School of Mathematical Science Huaqiao university QuanzhouFujian China Fujian Provincial Key Laboratory of Big Data Mining and Applications FuzhouFujian China School of Electronics and Information Engineering Hunan University of Science and Engineering YongzhouHunan China

Automata theory is an important branch of theoretical computer science. ω-automaton is an important part of automata theory. The judgment standard for the equivalence of two automata is the equivalence of their acceptance language. Acceptance conditions for automata are expressed with state set. This paper tries to use path to express acceptance conditions for ω-automaton that is convenient for judging the automatons equivalence property and transforming between different types of automata. With the help of Path ω-automaton, Muller automaton is transformed into Büchi automaton. Compared with the existing algorithm, the state scale of Büchi automaton has been reduced and the problem of state space explosion has been relieved. The research findings in this paper contribute to enrich the existing ω-automaton theory and provide a new idea for ω-automaton theory and application research. © 2017.

关键词： Automata theory