检索结果-内蒙古大学图书馆

Algorand: A secure and efficient distributed ledger

THEORETICAL COMPUTER SCIENCE 2019年 777卷 155-183页

作者： Chen, Jing Micali, Silvio SUNY Stony Brook Comp Sci Dept Stony Brook NY 11794 USA MIT CSAIL 77 Massachusetts Ave Cambridge MA 02139 USA

A distributed ledger is a tamperproof sequence of data that can be publicly accessed and augmented by everyone, without being maintained by a centralized party. distributed ledgers stand to revolutionize the way a modern society operates. They can secure all kinds of traditional transactions, such as payments, asset transfers and titles, in the exact order in which the transactions occur;and enable totally new transactions, such as cryptocurrencies and smart contracts. They can remove intermediaries and usher in a new paradigm for trust. As currently implemented, however, distributed ledgers scale poorly and cannot achieve their enormous potential. In this paper we propose Algorand, an alternative, secure and efficient distributed ledger. Algorand is permissionless and works in a highly asynchronous environment. Unlike prior implementations of distributed ledgers based on "proof of work," Algorand dispenses with "miners" and requires only a negligible amount of computation. Moreover, its transaction history "forks" only with negligible probability: that is, Algorand guarantees the finality of a transaction the moment the transaction enters the ledger. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Public ledger Blockchain Byzantine agreement distributed computation Cryptographic self-selection Permissionless system

来源：评论

学校读者我要写书评

暂无评论

A distributed optimal reactive power flow for global transmission and distribution network

引用

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2019年第Jan.期104卷 524-536页

作者： Zhao, Jinquan Zhang, Zhenwei Yao, Jianguo Yang, Shengchun Wang, Ke Bohai Univ Coll Energy & Elect Engn Nanjing 210098 Jiangsu Peoples R China State Grid Elect Power Res Inst Nanjing 210003 Jiangsu Peoples R China

With the large-scale integration of distributed generators (DGs), the relationships between transmission network (TN) and distribution networks (DNs) are becoming more closely, especially in the aspects of reactive power and voltage. Optimal reactive power flow (ORPF) problems for TN and DNs are not suitable to be solved independently. Due to the fact that TN and DNs are operated by different control centers, a heterogeneous decomposition (HGD) based distributed ORPF method for global transmission and distribution (T&D) networks is presented in this paper. Considering the characteristics of the master slave structure, the global T&D-ORPF problem can be decomposed into the TN-ORPF master sub-problem, the DN-ORPF slave sub-problems and the boundary consistency coordination sub-problem. Any of those optimization algorithms based on duality and gradient theory can be adopted to solve the TN-ORPF or DN-ORPF sub-problems. By incorporating a penalty function into optimization algorithm, the discrete control variables can successively discretized and therefore the augmented Lagrangian functions are differentiable. Boundary sensitivities constructed by the boundary dual multipliers are used to decouple the global ORPF problem of T&D networks. The same solution as the centralized optimization is achieved by transferring the boundary variables and sensitivities between the TN control center and DN control centers. The simulation results of IEEE 30-bus (TN) and modified IEEE 33-bus (DN) test systems containing multiple DGs show that the HGD algorithm is effective.

关键词： Global transmission and distribution network Optimal reactive power flow distributed computation Heterogeneous decomposition algorithm

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Analysis of Computing Paradigms Leading to Fog Computing: Simulation Tools, Applications, and Use Cases

引用

Data Processor for Better Business Education 2023年第6期63卷 1495页

作者： Sandipkumar Patel Ritesh Patel CSPIT Charusat Changa India

ABSTRACTThe emerging trend of computing technologies and the Internet of Things (IoT) makes applications optimal and more responsive for real-time data processing. It generates an unprecedented and heterogeneous amount of data. Cloud computing technologies were introduced with on-demand and highly scalable resources to address this data explosion problem. However, challenges like bandwidth limitation, high response time, latency-sensitive and real-time application resource demands have still existed, mostly solved through cloud computing. Therefore, cutting edge technologies in fog, edge, mist, and dew calculation are established to improve the utilization of network bandwidth, latency, and mobility in an efficient way. Research in fog computing is still in investigation mode, and several productive issues still need to be dig in depth based on platform, infrastructure, and application-oriented. Such key challenges include task partitioning, scheduling, and resource allocation. This presented survey aims to deliver a comprehensive analysis and gives cutting-edge technologies’ inside journey and evolution. The survey of simulation tools is also presented, which helps to understand & conclude the results of several scenarios and algorithms. Furthermore, major technology areas of fog, case studies on various applications and open issues are also presented.

关键词： Fog computing simulation tools Internet of Things cloud computation resource allocation distributed computation

来源：评论

学校读者我要写书评

暂无评论

Adaptive Medium Access Control for distributed Processing in Wireless Sensor Networks

引用

IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS 2019年第1期5卷 113-126页

作者： Asensio-Marco, Cesar Beferull-Lozano, Baltasar Univ Agder Dept Informat & Commun Technol N-4879 Grimstad Norway UVEG CSIC Inst Integrat Syst Biol Valencia Spain

Signal and information processing tasks over Wireless Sensor Networks can he successfully accomplished by means of a distributed implementation among the nodes. Existing distributed schemes are commonly based on iterative strategies that imply a huge demand of one-hop transmissions, which must be efficiently processed by the lower layers of the nodes. At the link layer, general purpose medium access (MAC) policies for wireless communications usually focus on avoiding collisions. These existing approaches result in a reduction of the number of simultaneous transmissions, and an underutilization of the channel as a consequence. This leads to a decrease in the performance of the distributed tasks, since an efficient channel occupation is not generally accomplished. In this paper, we propose a new MAC protocol that, besides focusing on the reliability of the communications, provides an efficient channel occupation. While the former has a direct impact on the energy consumption of usually battery powered devices, the latter affects the performance of the distributed task executed. We include both aspects in a global utility function that the nodes, relying just on local available information, aim to increase at every communication step. Furthermore, our proposal combines in a unique framework both unicast and broadcast scenarios. Through several simulation results, we show that our adaptive protocol outperforms the related literature.

关键词： CSMA protocol high traffic demand energy ficiency distributed computation wireless sensor networks

来源：评论

学校读者我要写书评

暂无评论

Imputation of Mixed Data With Multilevel Singular Value Decomposition

引用

JOURNAL OF computationAL AND GRAPHICAL STATISTICS 2019年第3期28卷 552-566页

作者： Husson, Francois Josse, Julie Narasimhan, Balasubramanian Robin, Genevieve UMR CNRS 6625 IRMAR Agrocampus Ouest Dept Stat Rennes France Ecole Polytech INRIA XPOP F-91120 Paris France Ecole Polytech Ctr Appl Math F-91120 Paris France Stanford Univ Dept Biomed Data Sci Stanford CA 94305 USA Stanford Univ Dept Stat Stanford CA 94305 USA Ecole Polytech Traumabase Grp Paris France

Statistical analysis of large datasets offers new opportunities to better understand underlying processes. Yet, data accumulation often implies relaxing acquisition procedures or compounding diverse sources. As a consequence, datasets often contain mixed data, that is, both quantitative and qualitative, and many missing values. Furthermore, aggregated data present a natural multilevel structure, where individuals or samples are nested within different sites, such as countries or hospitals. Imputation of multilevel data has therefore drawn some attention recently, but current solutions are not designed to handle mixed data, and suffer from important drawbacks, such as their computational cost. In this article, we propose a single imputation method for multilevel data, which can be used to complete either quantitative, categorical, or mixed data. The method is based on multilevel singular value decomposition (SVD), which consists in decomposing the variability of the data into two components, the between and within groups variability, and performing an SVD on both parts. We show on a simulation study that in comparison to competitors, the method has the advantages of handling datasets of various size, and being computationally faster. Furthermore, it is the first so far to handle mixed data. We apply the method to impute a medical dataset resulting from the aggregation of several hospitals datasets. This application falls in the framework of a larger project on Trauma patients. To overcome obstacles associated to the aggregation of medical data, we turn to distributed computation. The method is implemented in the R package missMDA. for this article are available online.

关键词： distributed computation Hierarchical data Low-rank matrix estimation Matrix completion Systematically and sporadically missing values

来源：评论

学校读者我要写书评

暂无评论

Web Archive Analysis Using Hive and SparkSQL 19

Web Archive Analysis Using Hive and SparkSQL

引用

19th ACM/IEEE Joint Conference on Digital Libraries (JCDL)

作者： Wang, Xinyue Xie, Zhiwu Virginia Polytech Inst & State Univ Blacksburg VA 24061 USA

Analyzing large web archive collections incurs high computational costs. We propose an analytic framework based on Apache Hive and SparkSQL with integrated data storage and processing. This method achieves a more bala... 详细信息

ISBN: (纸本)9781728115474

关键词： web archive big data distributed computation

来源：评论

学校读者我要写书评

暂无评论

Core-sets: An updated survey

引用

WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY 2020年第1期10卷 e1335-e1335页

作者： Feldman, Dan Univ Haifa Comp Sci Dept IL-3498838 Haifa Israel

In optimization or machine learning problems we are given a set of items, usually points in some metric space, and the goal is to minimize or maximize an objective function over some space of candidate solutions. For example, in clustering problems, the input is a set of points in some metric space, and a common goal is to compute a set of centers in some other space (points, lines) that will minimize the sum of distances to these points. In database queries, we may need to compute such a some for a specific query set of k centers. However, traditional algorithms cannot handle modern systems that require parallel real-time computations of infinite distributed streams from sensors such as GPS, audio or video that arrive to a cloud, or networks of weaker devices such as smartphones or robots. Core-set is a "small data" summarization of the input "big data," where every possible query has approximately the same answer on both data sets. Generic techniques enable efficient coreset maintenance of streaming, distributed and dynamic data. Traditional algorithms can then be applied on these coresets to maintain the approximated optimal solutions. The challenge is to design coresets with provable tradeoff between their size and approximation error. This survey summarizes such constructions in a retrospective way, that aims to unified and simplify the state-of-the-art. This article is categorized under Algorithmic Development > Structure Discovery Fundamental Concepts of Data and Knowledge > Big Data Mining Technologies > Machine Learning Algorithmic Development > Scalable Statistical Methods

关键词： big data cloud coresets distributed computation streaming

来源：评论

学校读者我要写书评

暂无评论

EC-Shuffle: Dynamic Erasure Coding Optimization for Efficient and Reliable Shuffle in Spark 19

EC-Shuffle: Dynamic Erasure Coding Optimization for Efficien...

引用

19th Annual IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing (CCGRID)

作者： Yao, Xin Wang, Cho-Li Zhang, Mingzhe Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China

ISBN: (纸本)9781728109121

Fault-tolerance capabilities attract increasing attention from existing data processing frameworks, such as Apache Spark. To avoid replaying costly distributed computation, like shuffle, local checkpoint and remote replication arc two popular approaches. They incur significant runtime overhead, such as extra storage cost or network traffic. Erasure coding is another emerging technology, which also enables data resilience. It is perceived as capable of replacing the checkpoint and replication mechanisms for its high storage efficiency. However, it suffers heavy network traffic due to distributing data partitions to different locations. In this paper, we propose EC-Shuffle with two encoding schemes and optimize the shuffle-based operations in Spark or MapReduce-like frameworks. Specifically, our encoding schemes concentrate on optimizing the data traffic during the execution of shuffle operations. They only transfer the parity chunks generated via erasure coding, instead of a whole copy of all data chunks. EC-Shuffle also provides a strategy, which can dynamically select the per shuffle biased encoding scheme according to the number of senders and receivers in each shuffle. Our analyses indicate that this dynamic encoding selection can minimize the total size of parity chunks. The extensive experimental results using BigDataBench with hundreds of mappers and reducers shows this optimization can reduce up to 50% network traffic and achieve up to 38% performance improvement.

关键词： fault tolerance distributed computation erasure coding

来源：评论

学校读者我要写书评

暂无评论

RaSQL: Greater Power and Performance for Big Data Analytics with Recursive-aggregate-SQL on Spark 19

RaSQL: Greater Power and Performance for Big Data Analytics ...

引用

ACM SIGMOD International Conference on Management of Data (SIGMOD)

作者： Gu, Jiaqi Watanabe, Yugo H. Mazza, William A. Shkapsky, Alexander Yang, Mohan Ding, Ling Zaniolo, Carlo Univ Calif Los Angeles Los Angeles CA 90095 USA Univ Naples Federico II Naples Italy Workday Inc Pleasanton CA USA Google LLC Mountain View CA USA

ISBN: (纸本)9781450356435

Thanks to a simple SQL extension, Recursive-aggregate-SQL (RaSQL) can express very powerful queries and declarative algorithms, such as classical graph algorithms and data mining algorithms. A novel compiler implementation allows RaSQL to map declarative queries into one basic fixpoint operator supporting aggregates in recursive queries. A fully optimized implementation of this fixpoint operator leads to superior performance, scalability and portability. Thus, our RaSQL system, which extends Spark SQL with the before-mentioned new constructs and implementation techniques, matches and often surpasses the performance of other systems, including Apache Giraph, GraphX and Myria.

关键词： Recursive Query Aggregates in Recursion Declarative Algorithms in SQL distributed computation

来源：评论

学校读者我要写书评

暂无评论

A distributed Voltage Stability Contingency Screening and Ranking Method for Integrated Transmission and Distribution Networks

A Distributed Voltage Stability Contingency Screening and Ra...

引用

IEEE-Power-and-Energy-Society General Meeting (PESGM)

作者： Zhao, Jinquan Tang, Jianjun Lin, Qing Tang, Wei Yang, Cheng Hu, Xiaofei Hohai Univ Coll Energy & Elect Engn Nanjing Peoples R China State Grid Corp China Anhui Elect Power Dispatch & Control Ctr Hefei Peoples R China

ISBN: (纸本)9781728119816

As distributed generations (DGs) gradually convert the distribution networks (DNs) from passive to active distribution networks (ADN), voltage stability assessment (VSA) is not suitable to treat the transmission and distribution networks separately. A distributed voltage stability contingency screening and ranking method for integrated transmission and distribution (T-D) networks is proposed, which includes two stages. In Stage 1, distributed power flow of integrated T-D networks is used to quickly screen out critical contingencies where there are no power flow solutions at the operating conditions calculated by distributed continuation power flow (DCPF) of integrated T-D networks under the predefined load margin threshold. In Stage 2, the load margins of critical contingencies are calculated and ranked by look-ahead quadric curve fitting method based on DCPF. Numerical simulations on an integrated system composed of an IEEE30-bus transmission network (TN) and two IEEE33-bus DNs show that the proposed method can be fast and reliable to achieve voltage stability contingency screening and ranking for integrated T-D networks.

关键词： integrated transmission and distribution networks voltage stability contingency screening and ranking distributed computation distributed continuation power flow

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：