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12th KIPS international conference on Ubiquitous Information technologies and applications (CUTE) / 9th international conference on Computer Science and its applications (CSA)

作者： Dai, Wei Liu, Wei Zhao, Xin-dong Shao, Jian Li, Qun Ma, Sheng-kun Xiong, Neal Lin, Chang-nian Jiangsu Elect Power Co Res Inst Nanjing 211103 Jiangsu Peoples R China Jiangsu Elect Power Co Nanjing 210000 Jiangsu Peoples R China Northeastern State Univ Dept Math & Comp Sci Tahlequah OK USA Tech Beijing Kedong Elect Power Control Syst Co L Beijing 100000 Peoples R China

ISBN: (纸本)9789811076053;9789811076046

Regarding the imperfection and poor collaborative interaction ability in existing substation simulation training system, this paper proposes a virtual reality simulation training system model for multiuser cooperation in substation maintenance which realizes multiuser collaborative virtual maintenance training of large-scale complex scenes of the substation and solves the competition of the electrical equipment resources. through analysis of hybrid heterogeneous hierarchical process modeling technology and Petri Nets sharing sub-network synthesis technology, the key technologies such as hierarchical maintenance process modeling, distributed cooperative concurrency control and asynchronous message delay strategy was put forward. the proposed model technique has been practical applied in virtual substation training system, and the effective application results have verified the rationality and effectiveness of the model.

关键词： Substation simulation training VR distributed collaboration Hybrid heterogeneous hierarchical modeling Synthesis of Petri nets

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distributed Approach for the Security of P2P Wireless Network

Distributed Approach for the Security of P2P Wireless Networ...

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12th KIPS international conference on Ubiquitous Information technologies and applications (CUTE) / 9th international conference on Computer Science and its applications (CSA)

作者： Yin, Chunyong Stacey, Nimenya Beita, Tatiana Moreira Wang, Jin Nanjing Univ Informat Sci & Technol Jiangsu Engn Ctr Network Monitoring Jiangsu Collaborat Innovat Ctr Atmospher Environm Sch Comp & Software Nanjing Jiangsu Peoples R China Yangzhou Univ Coll Informat Engn Yangzhou Jiangsu Peoples R China

ISBN: (纸本)9789811076053;9789811076046

Security for mobile P2P networks represents an open research and a main challenge regarding to their vulnerability and convenience to different security attacks such as Sybil attacks, black holes, etc. In this paper, we propose a solution based on a modification of the AODV routing protocol, taking into account the behavior of each node participating in the network solution. the benefits of our proposal are evaluated by simulation.

关键词： P2P Wireless mobile network Security Black hole AODV

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Design and Analysis of a Resonant 4th Order Converter Features with ADC Controller for Constant-Current applications 9

Design and Analysis of a Resonant 4th Order Converter Featur...

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9th Annual international Power Electronics, Drives Systems, and technologies conference (PEDSTC)

作者： Davoodi, Kamran Hamzeh, Mohsen Dobakhshari, Sina Salehi Shahid Beheshti Univ Tehran Iran Mazandaran Reg Elect Co Sari Iran AUT Tehran Iran

ISBN: (纸本)9781538646991

this paper presents a 4th order CLCL resonant converter that has a simple and unique design, and also it has the constant current power supply characteristic that is used for many constant current applications in various laboratories and industries. this converter is designed with Immittance two inductors and two capacitors, to property for constant current power supply. A detailed analysis, design and control process of a 200w converter is given, and simulation results are verified with results of a constructed converter. this converter with its unique structure, a combination of series and parallel resonant converter, has the advantages of both. As a constant current supply, CLCL resonant converter has the advantages of rigidity against short circuit even without a controller, easy operation in parallel mode, low circulating currents and high efficiency due to its soft switching operation. For this converter, leakage and magnetizing inductance of a transformer can be used as a part in the resonance network, and it decreases the converter size. Furthermore, series capacitor, eliminates the DC component and prevents the transformer saturation in unbalance conditions. With fixed-frequency performance, filter design also will be easier. Considering these advantages, the proposed topology can be used in a variety of applications such as magnetic power supplies, capacitor charging power supplies and agitator for laser diodes.

关键词： Constant current DC-DC Immittance resonance converter soft switching

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Real-Time Stream Data Processing at Scale

Real-Time Stream Data Processing at Scale

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IEEE international conference on parallel and distributed computing, applications and technologies (PDCAT)

作者： M. Reza HoseinyFarahabady Ali Jannesari Wei Bao Zahir Tari Albert Y. Zomaya Center for Distributed & High Performance Computing School of Computer Science The University of Sydney NSW Australia Department of Computer Science Iowa State University IA USA School of Science RMIT University Melbourne VIC Australia

ISBN: (数字)9781728126166

ISBN: (纸本)9781728126173

A typical scenario in a stream data-flow processing engine is that users submit continues queries in order to receive the computational result once a new stream of data arrives. the focus of the paper is to design a dynamic CPU cap controller for stream data-flow applications with real-time constraints, in which the result of computations must be available within a short time period, specified by the user, once a recent update in the input data occurs. It is common that the stream data-flow processing engine is deployed over a cluster of dedicated or virtualized server nodes, e.g., Cloud or Edge platform, to achieve a faster data processing. However, the attributes of incoming stream data-flow might fluctuate in an irregular way. To effectively cope with such unpredictable conditions, the underlying resource manager needs to be equipped with a dynamic resource provisioning mechanism to ensure the real-time requirements of different applications. the proposed solution uses control theory principals to achieve a good utilization of computing resources and a reduced average response time. the proposed algorithm dynamically adjusts the required quality of service (QoS) in an environment when multiple stream & data-flow processing applications concurrently run with unknown and volatile workloads. Our study confirms that such a unpredictable demand can negatively degrade the system performance, mainly due to adverse interference in the utilization of shared resources. Unlike prior research studies which assumes a static or zero correlation among the performance variability among consolidated applications, we presume the prevalence of shared-resource interference among collocated applications as a key performance-limiting parameter and confront it in scenarios where several applications have different QoS requirements with unpredictable workload demands. We design a low-overhead controller to achieve two natural optimization objectives of minimizing QoS violation amount an

关键词： Resource management Quality of service Data processing Microsoft Windows Adaptation models Computational modeling Real-time systems

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distributed representation learning of knowledge graph with diverse information 9

Distributed representation learning of knowledge graph with ...

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9th international conference on parallel Architectures, Algorithms and Programming (PAAP)

作者： Guo, Wenzhong Dai, Yuanfei Chen, Yiyan Chen, Xing Xiong, Neal N. Fuzhou Univ Coll Math & Comp Sci Fuzhou Fujian Peoples R China Fuzhou Univ Key Lab Network Comp & Intelligent Informat Proc Fuzhou Fujian Peoples R China Northeastern State Univ Dept Math & Comp Sci Tahlequah OK USA

ISBN: (纸本)9781538694039

Knowledge graph is a type of network structure in which nodes represent entities and edges indicate relations. However, as the network size explosively increases, the issues of data sparsity and computation inefficiency on large-scale knowledge graph become more difficult to manipulate and manage. Knowledge graph embedding, which is a representation technique of embedding entities and relations in the knowledge graph into continuous, dense, and low-dimensional semantics vector spaces to tackle these challenges and endow the model with the abilities of knowledge fusion and inference, has recently attracted much attention. In this paper, we firstly introduce the overall framework and specific idea of embedding models. We then introduce two applications that apply KG embedding, compare the performance of the methods in these applications. Finally, we summarize several challenges to overcome, and provide some prospective future research directions such as deep learning network for approaches and applications.

关键词： Knowledge graph embedding Knowledge representation Deep learning Statistical relational learning

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SPARK Processing of computing-Intensive Classification of Remote Sensing Images: the Case on K-Means Clustering Algorithm 26

SPARK Processing of Computing-Intensive Classification of Re...

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26th international conference on Geoinformatics (Geoinformatics)

作者： Shangguan, Boyi Yue, Peng Wuhan Univ Sch Remote Sensing & Informat Engn 129 Luoyu Rd Wuhan 430079 Hubei Peoples R China Wuhan Univ Hubei Prov Engn Ctr Intelligent Geoproc 129 Luoyu Rd Wuhan 430079 Hubei Peoples R China

ISBN: (纸本)9781538676196

High performance processing of remote sensing images is an important topic in remote sensing applications. One typical type of remote sensing processing is the iterative computing algorithms such as image classification algorithms, which are often computing-intensive and time-consuming. Recent advancement of cloud computing technologies such as APACHE SPARK has shown great promise for improving the computing performance. this paper presents a MapReduce based approach for parallelizing classification algorithms of remote sensing images on the cloud computing platform. the iterative processing is transformed into iterative Map and Reduce tasks that can be executed in parallel. the K-Means clustering algorithm is experimented with the SPARK cluster deployed on the OpenStack cloud computing platform to illustrate the applicability and effectiveness of the approach.

关键词： distributed computing remote sensing images classification cloud computing

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Performance Optimization of Wildlife Recognition with distributed Learning in Ecological Surveillance

Performance Optimization of Wildlife Recognition with Distri...

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IEEE international conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： Wan Dai Hongpeng Wang Yulin Song Yunwei Xin Tianjin Key Laboratory of Intelligent Robotics Tianjin Research Laboratory of Machine Learning and Pervasive Computing Nankai University Tianjin

ISBN: (数字)9781728107707

ISBN: (纸本)9781728107714

Recently, deep learning technology has been widely used in ecological environment monitoring, but there are still huge challenges in specific tasks. For example, data sets have increased over the past few years, and in a CPU environment, training is quite time consuming. In order to solve these problems, we bring up a novel and effective method to improve training speed. In this paper, we make use of multi-GPUs to achieve distributed parallel acceleration. Small and shallow networks are not suitable for distributed training, because the computation of each parameter in this network is much higher than that of multi-layer perception or automatic encoder architecture, we use convolutional neural network with parameter sharing as the training network. In this paper, the main adopted method is to compare the performance of training wildlife recognition in single GPU and multi-GPUs environments by using distributed deep learning framework TensorFlow. the experimental results show that multi-GPUs which adopt distributed architecture can significantly accelerate training time consumption than single GPU. the results of this experiment also provides strong support for our follow-up work.

关键词： Training parallel processing Graphics processing units distributed databases Computational modeling Data models Neural networks

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Exploring Scalable computing Architectures for Interactions Analysis 27

Exploring Scalable Computing Architectures for Interactions ...

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27th international conference on Computer Communications and Networks (ICCCN)

作者： Seth, Taruna Feng, Chao Ramanathan, Murali Chaudhary, Vipin Dept Comp Sci & Engn Buffalo NY USA Dept Pharmaceut Sci Buffalo NY USA

ISBN: (纸本)9781538651568

Characterization of pharmacological signal transductions leading to drug-induced expressions of genes and proteins requires the capability to identify interactions among different potential predictor components, e.g. genomic data, clinical data, and environmental data. the detection of these gene-gene and gene-environment interactions remains challenging due to the exponential computational complexity and high dimensionality of the interaction problem. the problem is further exacerbated due to the involvement of very large-scale epidemiological datasets. Efficient high-order interaction analysis of such large-scale data is not feasible with the traditional frameworks. parallel implementations of such applications in traditional cluster environments are often inefficient due to the storage bandwidth and network I/O limitations. Scalable distributed platforms can offer better scalability to such problems compared to the cluster architectures. Moreover, such data- and compute-intensive problems can benefit even further from data-intensive supercomputing (DISC) architectures that have been shown to yield superior performance compared to the regularly used cluster platforms. In this paper, we evaluate the applicability of different architectures such as traditional server based distributed architectures supported on commodity hardware and shared nothing architectures with massively parallel processing capabilities, towards the Interaction Analysis problem. Our experiments show that the massively parallel processing, shared-nothing architecture outweigh the benefits often realized through traditional server based and even distributed computing architectures. We conclude that the rapidly growing class of shared nothing architectures offers a potentially efficient and viable alternative to facilitate high-order interaction analysis involving extremely large scale biological datasets and is well suited to this category of data- and compute-intensive problems that cannot be a

关键词： distributed shared nothing architectures information theory scalable architectures

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Trends and Constraints on Brazilian Photovoltaic Industry: Energy Policies, Interconnection Codes, and Equipment Certification

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IEEE TRANSACTIONS ON INDUSTRY applications 2018年第5期54卷 4017-4027页

作者： Marafao, Fernando Pinhabel dos Santos Alonso, Augusto Matheus Goncalves, Flavio A. S. Brandao, Danilo Iglesias Germano Martins, Antonio Cesar Morales Paredes, Helmo Kelis Univ Estadual Paulista Grp Automat & Integrated Syst BR-18087180 Sorocaba Brazil Univ Fed Minas Gerais Grad Program Elect Engn BR-31270901 Belo Horizonte MG Brazil

After years of dormant scenarios, the Brazilian industry of photovoltaic (PV) energy systems is now growing fast. therefore, improving interconnection and certification codes, as well as standards, has become undeniably important to establish a well-regulated market under concern of businesses, equipment, and power quality matters. thus, considering international standards and world-recognized scenarios for distributed PV systems, this paper aims to discuss the existing local energy regulations, grid connection codes, and other related limitations that restrain a faster market and technology development in Brazil. Special attention is given to the certification requirements for grid-connected inverters and other PV equipment, along with the new trends in energy policies, focusing on their impacts on Brazilian PV industry. In the end, it demonstrates that despite its current underdeveloped status, the Brazilian scenario is expected to be quite enthusiastic in the following years and may represent an attractive and dynamic market for professionals, companies, and energy investors.

关键词： Brazilian distributed generation rules distributed generation energy policies microgeneration photovoltaic (PV) PV certification PV equipment renewable energy

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Blockchain based distributed Consensus for Byzantine Fault Tolerance in PMU Network

Blockchain based Distributed Consensus for Byzantine Fault T...

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international conference on computing and Networking Technology (ICCNT)

作者： Sreerag Iyer Snehal thakur Mihirraj Dixit Ashish Agrawal Rajneesh Katkam Faruk Kazi Centre of Excellence (CoE) in Complex and Non-linear Dynamical Systems (CNDS) Veermata Jijabai Technological Institute Mumbai India

Smart grids are in their developing stages, but they are going to impact the world soon. the more they influence us, the more they have a threat of being misused. Industrial Internet of things(IIoT) is being extensively used in various smart grid based applications. IIoT has been an area for cyber-attacks to drastically affect various industries and businesses. Existing technologies are just not enough to deal with cyber-physical systems. Blockchain can help in creating more efficient, secure and reliable IIoT systems. Such systems, which involve rapid, distributed and complex energy transactions and data exchanges often face integrity and trust related issues. Blockchain can provide a solution to such problems. third-party interactions have been removed using blockchain based smart contracts, thereby facilitating the adoption of decentralization and establishing a global truth across all the nodes in the network. Efficiency can further be increased by logging only the most important events like faults in the system or injection of malicious data. this paper proposes an innovative collective decision algorithm using blockchain to build a resilient network of Phasor Measurement Units(PMUs) for Wide Area Measurement System(WAMS). the algorithm not only identifies “malicious” nodes in the system but also takes the correct decision, even in their presence, to perform further action. the proposed solution is validated on a hardware-in-loop platform with the hardware PMUs connected on an IEEE 9 bus system.

关键词： Phasor measurement units Blockchain Peer-to-peer computing Smart grids Data communication Smart contracts

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