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检索条件"任意字段=International Conference on Parallel Distributed and Grid Computing"

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Research on parallel Processing Method for Ultra-large-scale Drug Screening Data 4

Research on Parallel Processing Method for Ultra-large-scale...

引用

4th international conference on Computer Information Science and Artificial Intelligence, CISAI 2021

作者： Dai, Xuebing Liu, Hao Shan, Liyang Yang, Yanbo Guo, Jingjing Ocean University of China College of Computer Science and Technology Qingdao China

ISBN: (纸本)9781665406925

Artificial intelligence has become the core driving force of a new round of industrial innovation around the world and a strategic technology that leads future development. The application of artificial intelligence to new drug discovery has become the world's medical field. In order to reduce costs, it is the main technical means to quickly discover new drugs. Virtual screening is an important step in new drug discovery. However, it needs to solve many problems, such as the large scale of the compound, the uneven quality, and the complicated processing steps. This paper studies a parallel processing method for ultra-large-scale drug screening data to improve the accuracy of drug virtual screening and the efficiency of drug discovery. Research distributed storage architecture and data balanced distribution, small molecule batch standardized pre-processing and structure optimization. And through experiments to compare the execution efficiency of different modes of the method, the results show that the method can process compound data efficiently and quickly, and improve the efficiency of virtual screening. Summarize the advantages and disadvantages of the method, and point out the general applicability of the method in the next step, and expand the diversification of compound processing functions. © 2021 IEEE.

关键词： Efficiency

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Querying Shared Data with Security Heterogeneity 20

Querying Shared Data with Security Heterogeneity

引用

ACM SIGMOD international conference on Management of Data (SIGMOD)

作者： Cao, Yang Fan, Wenfei Wang, Yanghao Yi, Ke Univ Edinburgh Edinburgh Midlothian Scotland Shenzhen Univ SICS Shenzhen Peoples R China Beihang Univ BDBC Beijing Peoples R China HKUST Hong Kong Peoples R China

ISBN: (纸本)9781450367356

There has been increasing need for secure data sharing. In practice a group of data owners often adopt a heterogeneous security scheme under which each pair of parties decide their own protocol to share data with diverse levels of trust. The scheme also keeps track of how the data is used. This paper studies distributed SQL query answering in the heterogeneous security setting. We define query plans by incorporating toll functions determined by data sharing agreements and reflected in the use of various security facilities. We formalize query answering as a bi-criteria optimization problem, to minimize both data sharing toll and parallel query evaluation cost. We show that this problem is PSPACE-hard for SQL and Sigma(p)(3)-hard for SPC, and it is in NEXPTIME. Despite the hardness, we develop a set of approximate algorithms to generate distributed query plans that minimize data sharing toll and reduce parallel evaluation cost. Using real-life and synthetic data, we empirically verify the effectiveness, scalability and efficiency of our algorithms.

关键词： data sharing security protocol query processing distributed databases privacy-preserving

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Description for Smart grid: Towards the Ontological Approach 8

Description for Smart Grid: Towards the Ontological Approach

引用

8th international conference on Information Technology and Multimedia, ICIMU 2020

作者： Yee Chong, Alicia Tang Mahmoud, Moamin A Lim, Fung-Cheng Kasim, Hairoladenan Institute of Informatics and Computing in Energy Universiti Tenaga Nasional Malaysia College of Computing and Informatics Universiti Tenaga Nasional Malaysia

ISBN: (纸本)9781728173108

Smart grids facilitate the use of distributed and renewable resources on the supply side and providing consumers with a range of tailored services on the consumption side. The introduction of energy smart grid in Malaysia allows other stakeholders to reap the potential benefits it offers. However, for the stakeholders to share knowledge and collaborate, a common language that can act as intermediary that allows any application to communicate with each other is needed. Ontologies have been successful in integrating the knowledge required for solving complex problems such as energy management problems. Ontology has become a promising future direction towards devising a context-aware middleware platform for the smart grid. Hence, we propose to develop ontology for energy smart grid to support information integration for existing smart grid applications and to produce an efficient, semantically aware and operationally accurate software environment for managing flexibility in Malaysian energy distribution networks. © 2020 IEEE.

关键词： Ontology

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UniGPS: A Unified Programming Framework for distributed Graph Processing

UniGPS: A Unified Programming Framework for Distributed Grap...

引用

international conference on parallel and distributed Systems (ICPADS)

作者： Zhaokang Wang Junhong Li Yifan Qi Guanghui Zhu Chunfeng Yuan Yihua Huang State Key Laboratory for Novel Software Technology Nanjing University Nanjing P. R. China Nanjing University Nanjing P. R. China

ISBN: (纸本)9781665408790

The industry and academia have proposed many distributed graph processing systems. However, the existing systems are not friendly enough for users like data analysts and algorithm engineers. On the one hand, the programming models and interfaces differ a lot in the existing systems, leading to high learning costs and program migration costs. On the other hand, these graph processing systems are tightly bound to the underlying distributed computing platforms, requiring users to be familiar with distributed computing. To improve the usability of distributed graph processing, we propose a unified distributed graph programming framework UniGPS. Firstly, we propose a unified cross-platform graph programming model VCProg for UniGPS. VCProg hides details of distributed computing from users. It is compatible with the popular graph programming models Pregel, GAS, and Push-Pull. VCProg-based programs can be executed by compatible distributed graph processing systems without modification, reducing the learning overheads of users. Secondly, UniGPS supports Python as the programming language. We propose an interprocess-communication-based execution environment isolation mechanism to enable Java/C++-based graph processing systems to call user-defined methods written in Python. The experimental results show that UniGPS enables users to process big graphs beyond the memory capacity of a single machine without sacrificing usability. UniGPS shows near-linear data scalability and machine scalability.

关键词： Industries Costs Computational modeling Scalability conferences Programming distributed computing

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A Study on Blockchain Application in Donation Platform

A Study on Blockchain Application in Donation Platform

引用

Software Engineering, Artificial Intelligence, Networking and parallel/distributed computing (SNPD-Winter), ACIS international Winter conference on

作者： Wooyoung Lee Dukjin Kim Byeong Ryun Jeon Graduate School Soongsil Univ. Seoul South Korea

ISBN: (纸本)9781665418430;9781665448260

Recently, interest in the spread of the culture of sharing has been increasing at a social level due to the deepening income polarization, poverty, and the rapid growth of civil society and the importance of public interest activities of private organizations. In 2016, the National Statistical Office conducted a survey on changes in donation attitudes and recognition of donations, items that took up a large part in the area for the spread of the overall donation culture were the convenience of donation methods and the enhancement of transparency of donation organizations. The existing donation system is a way for donors to donate directly to several donor organizations. However, this method has its disadvantage: it is difficult for donors to see how their donations are spent. To address the convenience of such donation methods, based on the platform that is the core of the fourth industrial era, it enables unrestricted interaction in the network environment such as mobile or PC, inducing open participation in talent donation to the general public. Blockchain is a data forgery/modulation prevention technology based on distributed computing technology. Because the block chain records continuously changing data on all participating nodes, it is impossible to arbitrarily manipulate the data by the operators of distributed nodes. Blockchain technology is in the spotlight because it can secure transparency in transactions. In this paper, to solve these problems, we try to introduce the block chain technology into the donation system.

关键词： distributed databases Blockchain Organizations Artificial intelligence Software engineering

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Agent-Navigable Dynamic Graph Construction and Visualization over distributed Memory 8

Agent-Navigable Dynamic Graph Construction and Visualization...

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8th IEEE international conference on Big Data (Big Data)

作者： Gilroy, Justin Paronyan, Satine Acoltzi, Jonathan Fukuda, Munehiro Univ Washington Bothell Comp & Software Syst Bothell WA 98011 USA

ISBN: (纸本)9781728162515

Some graph analyses, such as social network and biological network, need large-scale graph construction and maintenance over distributed memory space. distributed data-streaming tools, including MapReduce and Spark, restrict some computational freedom of incremental graph modification and run-time graph visualization. Instead, we take an agent-based approach. We construct a graph from a scientific dataset in CSV, tab, and XML formats;dispatch many reactive agents on it;and analyze the graph in the form of their collective group behavior: propagation, flocking, and collision. The key to success is how to automate the run-time construction and visualization of agent-navigable graphs mapped over distributed memory. We implemented this distributed graph-computing support in the multi-agent spatial simulation (MASS) library, coupled with the Cytoscape graph visualization software. This paper presents the MASS implementation techniques and demonstrates its execution performance in comparison to MapReduce and Spark, using two benchmark programs: (1) an incremental construction of a complete graph and (2) a KD tree construction.

关键词： multi-agent systems agent-based modeling data analysis data visualization parallel programming

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parallel Training of a Set of Online Sequential Extreme Learning Machines

Parallel Training of a Set of Online Sequential Extreme Lear...

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Computer Science Society (SCCC) international conference Chilean

作者： Elkin Gelvez-Almeida Ricardo J. Barrientos Karina Vilches-Ponce Marco Mora Universidad Católica del Maule Talca Chile Facultad de Ciencias Básicas Universidad Simón Bolívar San José de Cúcuta Colombia Laboratorio LITRP Facultad de Ciencias de la Ingeniería Universidad Católica del Maule Talca Chile Facultad de Ciencias de la Ingeniería Universidad Católica del Maule Talca Chile

ISBN: (纸本)9781665456753

Size databases have constantly increased from advances in technology and the Internet, so processing this vast amount of information has been a great challenge. The neural network Extreme Learning Machine (ELM) have been widely accepted in the scientific community due to their simplicity and good generalization capacity. This model consists of randomly assigning the weights of the hidden layer, and analytically calculating the weights of the output layer through the Moore- Penrose generalized inverse. High-Performance computing has emerged as an excellent alternative for tackling problems involving large-scale databases and reducing processing times. The use of parallel computing tools in Extreme Learning Machines and their variants, especially the Online Sequential Extreme Learning Machine (OS-ELM), has proven to be a good alternative to tackle regression and classification problems with largescale databases. In this paper, we present a parallel training methodology consisting of several Online Sequential Extreme Learning Machines running on different cores of the Central Processing Unit, with a balanced fingerprint database having 2,000,000 samples distributed in five classes. The results show that training and validation times decrease as the number of processes increases since the number of samples to train in each process decreases. In addition, by having several Online Sequential Extreme Learning Machines trained, new samples can beclassified on any of them.

关键词： Extreme learning machines Databases Training Fingerprint recognition Computer science Computational modeling Reactive power

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Fog computing Based Traffic and Car Parking Intelligent System 19th

Fog Computing Based Traffic and Car Parking Intelligent Syst...

引用

19th international conference on Algorithms and Architectures for parallel Processing (ICA3PP)

作者： Alajali, Walaa Gao, Shang Alhusaynat, Abdulrahman D. Deakin Univ Melbourne Vic 3217 Australia Thi Qar Univ Nasiriyah 64001 Iraq

ISBN: (纸本)9783030389611;9783030389604

Internet of Things (IoT) has attracted the attention of researchers from both industry and academia. Smart city, as one of the IoT applications, includes several sub-applications, such as intelligent transportation system (ITS), smart car parking and smart grid. Focusing on traffic flow management and car parking systems because of their correlation, this paper aims to provide a framework solution to both systems using online detection and prediction based on fog computing. Online event detection plays a vital role in traffic flow management, as circumstances, such as social events and congestion resulting from accidents and roadworks, affect traffic flow and parking availability. We developed an online prediction model using an incremental decision tree and distributed the prediction process on fog nodes at each intersection traffic light responsible for a connecting road. It effectively reduces the load on the communication network, as the data is processed, and the decision is made locally, with low storage requirements. The spatially correlated fog nodes can communicate if necessary to take action for an emergency. The experiments were conducted using the Melbourne city open data.

关键词： Traffic flow Prediction ITS Smart car parking

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distributed Graph Analytics 16th

Distributed Graph Analytics

引用

16th international conference on distributed computing and Internet Technology (ICDCIT)

作者： Srikant, Y. N. Indian Inst Sci Bengaluru 560012 India

ISBN: (纸本)9783030369873;9783030369866

Graph Analytics is important in different domains: social networks, computer networks, and computational biology to name a few. This paper describes the challenges involved in programming the underlying graph algorithms for graph analytics for distributed systems with CPU, GPU, and multi-GPU machines and how to deal with them. It emphasizes how language abstractions and good compilation can ease programming graph analytics on such platforms without sacrificing implementation efficiency.

关键词： Graph analytics Social networks parallel algorithms Multi-core processors GPU computation Graph frameworks Graph processing languages

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Data-driven Energy Theft Detection in Modern Power grids 21

Data-driven Energy Theft Detection in Modern Power Grids

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12th ACM international conference on Future Energy Systems, e-Energy 2021

作者： Althobaiti, Ahlam Jindal, Anish Marnerides, Angelos K. School of Computing and Communications Lancaster University United Kingdom School of Computer Science and Electronic Engineering University of Essex United Kingdom School of Computing Science University of Glasgow United Kingdom

ISBN: (纸本)9781450383332

Energy theft is an old and multifaceted phenomenon affecting our society on a global scale from both an operational as well as from a monetary perspective. The relatively recent decentralisation of the grid infrastructure with the integration of distributed Renewable Energy Resources (DRES) in synergy with the widely adopted demand-response business model, has undoubtedly broadened the spectrum of attack surface enabling energy theft. Conventional data-driven energy theft detection schemes have a strong dependency on assessing the spatio-temporal patterns of SCADA measurements aggregated at the Distribution System Operator (DSO) or Transmission System Operator (TSO) with minimal consideration of the intrinsic weather patterns related to individual DRES deployments. Hence, theft scenarios instrumented by DRES owners consuming the energy they produce (i.e., prosumers) can effectively be stealthy and hard to spot. Therefore, in this work we introduce a data-driven, SCADA-agnostic energy theft detection framework explicit to DRES-based scenarios. We provide a comprehensive formalisation of a DRES-based theft attack model and further assess the performance of our framework by utilising and relating freely available third-party weather measurements with real solar and wind turbine deployments in Australia and France. Evidently, our proposed framework yields an energy theft detection accuracy rate of over 98% with optimal computational costs. Thus, reasonably addressing the highly demanding requirements of low-cost and accurate real-time energy theft detection in modern power grids. © 2021 ACM.

关键词： Smart power grids

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