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Architecture Design of distributed Medical Big Data Platform Based on Spark 8

Architecture Design of Distributed Medical Big Data Platform...

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IEEE 8th Joint international Information Technology and Artificial Intelligence conference (ITAIC)

作者： Tu, Yongqiu Lu, Yiqiang Chen, Guohua Zhao, Jie Yi, Faling Guangdong Pharmaceut Univ Guangzhou Guangdong Peoples R China

ISBN: (纸本)9781538681787

An Apache Spark based distributed computing and storage system designed for large-scale health data. the system provides the solution for health data digitalization and analysis, while enabling high-throughput data processing, real-time processing and messaging capabilities. the design of the system has the potential to provide many health-related services to medical professionals, such as data retrieving/processing, real-time alerts, data mining. the article described key considerations throughout the system designing process, including comparison of different component, finding the optimal data flow mechanics for specific tasks, etc. During the design and implementation, these core technologies are involved: (1) Java, Scala, programming languages, with IntelliJ IDEA IDE. (2)Apache Spark, general purpose distributed data processing engine. (3)Apache Hadoop: HDFS and YARN, distributed storage system and computational resource manager, respectively. (4)MySQL, relational database engine.(5)Apache Hive, distributed relational database engine.(6)Apache Kafka, distributed messaging system.

关键词： MapReduce Spark Streaming Hadoop Big Health data

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An optimization method for resource allocation in fog computing 13

An optimization method for resource allocation in fog comput...

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2020 IEEE Congress on Cybermatics: 13th IEEE international conferences on Internet of things, ithings 2020, 16th IEEE international conference on Green computing and Communications, GreenCom 2020, 13th IEEE international conference on Cyber, Physical and Social computing, CPSCom 2020 and 6th IEEE international conference on Smart Data, SmartData 2020

作者： Yin, Chao Li, Tongfang Qu, Xiaoping Yuan, Sihao School of Information Science and Technology Jiujiang University Jiujiang332005 China

ISBN: (纸本)9781728176475

With the rapid development of the network, a huge amount of data will be generated. Existing technologies usually use cloud computing to process data. However, when all the data of users need to be transferred to the cloud for processing, it will cause long transmission delay due to the distance between users and cloud computing data center. Fog computing connects network edge devices downward and cloud data center upward, which greatly shortens the transmission distance of user data. Fog computing is an effective way to solve the problems of high delay, bandwidth bottleneck and security. In this paper, we have developed an optimization method, which establish an optimization problem with minimum average task delay as optimization objective and various system resources. By variable substitution, the nonconvex optimization problem is equivalent to a new optimization problem whose objective is nonconvex and all constraints are convex. In order to solve the global optimal solution of the nonconvex optimization problem, a new lower bound is designed by relaxing the objective to a lower bound quadratic function. We have evaluated our system by simulation test. the results verify the effectiveness of the optimization method. © 2020 IEEE.

关键词： Resource allocation

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XAI: A Middleware for Scalable AI 8

XAI: A Middleware for Scalable AI

引用

8th international conference on Data Science, Technology and Applications (DATA)

作者： Salama, Abdallah Linke, Alexander Rocha, Igor Pessoa Binnig, Carsten Tech Univ Darmstadt Data Management Lab Darmstadt Germany

ISBN: (纸本)9789897583773

A major obstacle for the adoption of deep neural networks (DNNs) is that the training can take multiple hours or days even with modern GPUs. In order to speed-up training of modern DNNs, recent deep learning frameworks support the distribution of the training process across multiple machines in a cluster of nodes. However, even if existing well-established models such as AlexNet or GoogleNet are being used, it is still a challenging task for data scientists to scale-out distributed deep learning in their environments and on their hardware resources. In this paper, we present XAI, a middleware on top of existing deep learning frameworks such as MXNet and Tensorflow to easily scale-out distributed training of DNNs. the aim of XAI is that data scientists can use a simple interface to specify the model that needs to be trained and the resources available (e.g., number of machines, number of GPUs per machine, etc.). At the core of XAI, we have implemented a distributed optimizer that takes the model and the available cluster resources as input and finds a distributed setup of the training for the given model that best leverages the available resources. Our experiments show that XAI converges to a desired training accuracy 2x to 5x faster than default distribution setups in MXNet and TensorFlow.

关键词： distributed Deep Learning Machine Learning Cloud computing Scalability

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distributed anomaly detection method in wireless sensor networks based on temporal-spatial QSSVM 8th

Distributed anomaly detection method in wireless sensor netw...

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8th international conference on Computer Engineering and Networks, CENet 2018

作者： Chen, Zhili Wu, Huarui Zhu, Huaji Miao, Yisheng National Engineering Research Center for Information Technology in Agriculture Beijing100097 China College of Information and Electrical Engineering China Agricultural University Beijing100083 China Beijing Research Center for Information Technology in Agriculture Beijing Academy of Agriculture and Forestry Sciences Beijing100097 China

ISBN: (纸本)9783030146795

In Wireless Sensor Networks (WSNs), abnormal sensing data is easily generated due to factors such as the harsh working environment, sensor faults and external events. In order to enhance the detection rate of abnormal data and reduce the false positive rate, we propose a distributed anomaly detection method using one-class quarter-sphere support vector machine (QSSVM) based on temporal-spatial fusion in WSNs. Firstly, according to the synthetic data, the temporal-spatial QSSVM model is trained to determine the relevant parameters. Secondly, the trained QSSVM model is used to classify the streaming data in WSNs, and the abnormal data types are classified into noise, faults and events. Finally, the method decides whether to update the classification model based on whether the new sample has an effect on the boundary of the hypersphere. the experimental results illustrate that the proposed method has a detection rate of 96% compared with other three methods, and the false positive rate is only 14%. © Springer Nature Switzerland AG 2020.

关键词： Wireless sensor networks

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Enhancing the performance of elliptic curve digital signature algorithm (ECDSA) in named data networking (NDN) 8

Enhancing the performance of elliptic curve digital signatur...

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8th IEEE international conference on Control System, computing and Engineering, ICCSCE 2018

作者： Ting, Ren Leau, Yu-Beng Park, Yong Jin Obit, Joe H. Kota Kinabalu Sabah Malaysia

ISBN: (纸本)9781538663240

Named data networking (NDN) had been considered as a most recognizable Information Centric networking (ICN) infrastructure. the deployment of NDN in the internet architecture requires the confidentiality and integrity of the contents. In this context, Elliptic Curve Digital Signature Algorithm (ECDSA) is a more promising algorithm. this research applied Montgomery Reduction on the existing asymmetrical security algorithm to shorter the processing period, lower the memory consumption and reduce the complexity over large computational requests. An experiment had been implemented in NDNv2 over ndnSIM environment. the results showed that modified ECDSA has reduced the processing period of 1%-3% in private key generation and 50% in public key signing based on exponential analysis on modified ECDSA over existing ECDSA in key generation. the total time required to establish the connection among the nodes in NDN also has reduced of 12% by using modified ECDSA over ndnSIM. © 2018 IEEE.

关键词： Geometry

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On the Optimal Size of Ring-canal in Starfish Routing 8

On the Optimal Size of Ring-canal in Starfish Routing

引用

Joint 8th international conference on Informatics, Electronics and Vision (ICIEV) / 3rd international conference on Imaging, Vision and Pattern Recognition (icIVPR) / international conference on Activity and Behavior computing (ABC)

作者： Habib, Md Ahsan Saha, Sajeeb Razzaque, Md Abdur Mamun-Or-Rashid, Md Univ Dhaka Dept Comp Sci & Engn Green Networking Res Grp Dhaka Bangladesh

ISBN: (纸本)9781728107882

Backbone based routing strategies for Mobile Wireless Sensor Networks (MWSNs) are becoming very popular for minimizing end-to-end delay with extended network lifetime, while collecting real-time sensed data from different corners of the network. Existing backbone architectures, i.e., Ringand Starfish-backbone, constitute rings of fixed radius ignoring the sizes of network. Moreover, the network performance and routing issues are greatly affected by the fixed size of the ring in the existing literature works, i.e., Ring- and Starfish-backbone, since the size has not been determined optimally based on the network size. In this paper, at first, we estimate the optimal size (or radius) of the ring-canal dynamically based on sensor's transmission range and network area. Later, we evaluate end-to-end delay and network throughput for Starfish routing with optimal ring-canal. the simulation results, performed in Network Simulator (NS-2), show significant improvement for delay and throughput compared to the existing literature works.

关键词： MWSN Starfish routing backbone Mobile sink Optimal ring size delay and throughput

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Method of complex internet of things simulation attack and reliability analysis 8th

Method of complex internet of things simulation attack and r...

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8th international conference on Computer Engineering and Networks, CENet 2018

作者： Chen, Bingwei Chen, Zidi Yuan, Hecun Rui, Lanlan State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications No. 10 Xitucheng Road Haidian District Beijing China

ISBN: (纸本)9783030146795

In recent years, with the rapid development of Internet of things, the scale of networks has gradually increased, link capacity has become higher and higher. In this context, the research on the reliability of complex networks has been paid more and more attention. the network reliability analysis and evaluation technology need to be implemented by a corresponding network simulation and reliability comprehensive test analysis system, and presented to the user in a variety of visual forms more intuitively, so as to be further applied to the actual network environment. Simulate the network attack mode under complex network environment and get the reliability evaluation results under different attack strategies. Establishing complex network simulation attacks and analyzing them is of great significance in evaluating the reliability of complex IoT topologies. In this paper, a complex network evaluation model was further established. At the same time, three kinds of strategies are designed to simulate attacks on complex networks. Based on Django and the smart home network, the method is implemented in a more appropriate form of visualization. Finally, the method is tested and analyzed. the results show that the method can better represent the process of complex network simulation attacks and the changes of network reliability indicators. © Springer Nature Switzerland AG 2020.

关键词： Reliability analysis

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Identifying the Writing Style of Bangla Language Using Natural Language Processing

Identifying the Writing Style of Bangla Language Using Natur...

引用

international conference on computing and networking Technology (ICCNT)

作者： Syeda Farjana Shetu Mohd. Saifuzzaman Masuma Parvin Nazmun Nessa Moon Ridwanullah Yousuf Sharmin Sultana Daffodil International University Dhaka Bangladesh

ISBN: (数字)9781728168517

ISBN: (纸本)9781728168524

Bangla is one of the 8th major spoken languages around the world and like other widely spoken languages, it is a very morphologically rich language. It has two styles, one is standard literary style, known as Sadhu Bhasha and the other one is a standard colloquial style which is known as Cholito Bhasha. Mixing both the styles in a written document is considered as a grammatical error in Bangla language known as Guruchondali Dosh. this research aims to develop an algorithm to identify the style of a Bangla paragraph i.e. whether it is in Sadhu Bhasha or Cholito Bhasha from a given Bangla paragraph input. It's a contribution towards finding the Goruchondali Dosh which is a common grammatical mistake in written Bangla language as it was observed that a number of research work for identifying Bangla grammar mistakes is not so notable whereas it is a common trend in other language researchers.

关键词： Grammar Syntactics Morphology Tokenization Standards Tools Mathematical model

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Edge-Centric Queries’ Stream Management Based on an Ensemble Model 8th

Edge-Centric Queries’ Stream Management Based on an Ensembl...

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8th international Workshop on Combinations of Intelligent Methods and Applications, CIMA 2018 held in conjunction with the 30th IEEE international conference on Tools with Artificial Intelligence, IEEE ICTAI 2018

作者： Kolomvatsos, Kostas Anagnostopoulos, Christos School of Computing Science University of Glasgow GlasgowG12 8RZ United Kingdom

ISBN: (纸本)9789811519178

the Internet of things (IoT) involves numerous devices that can interact with each other or with their environment to collect and process data. the collected data streams are guided to the cloud for further processing and the production of analytics. However, any processing in the cloud, even if it is supported by improved computational resources, suffers from an increased latency. the data should travel to the cloud infrastructure as well as the provided analytics back to end users or devices. For minimizing the latency, we can perform data processing at the edge of the network, i.e., at the edge nodes. the aim is to deliver analytics and build knowledge close to end users and devices minimizing the required time for realizing responses. Edge nodes are transformed into distributed processing points where analytics queries can be served. In this paper, we deal with the problem of allocating queries, defined for producing knowledge, to a number of edge nodes. the aim is to further reduce the latency by allocating queries to nodes that exhibit low load (the current and the estimated);thus, they can provide the final response in the minimum time. However, before the allocation, we should decide the computational burden that a query will cause. the allocation is concluded by the assistance of an ensemble similarity scheme responsible to deliver the complexity class for each query. the complexity class, thus, can be matched against the current load of every edge node. We discuss our scheme, and through a large set of simulations and the adoption of benchmarking queries, we reveal the potentials of the proposed model supported by numerical results. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Internet of things

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A Method of Document Sensitivity Calculation Based on Semantic Dependency Analysis 8

A Method of Document Sensitivity Calculation Based on Semant...

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IEEE 8th Joint international Information Technology and Artificial Intelligence conference (ITAIC)

作者： Gang, Lu Xu, Wu Xie Xia-qing Beijing Univ Posts & Telecommun Sch Cyberspace Secur Beijing 100876 Peoples R China BUPT Key Lab Trustworthy Distributed Comp & Serv Minist Educ Beijing 100876 Peoples R China Beijing Univ Posts & Telecommun Lib Beijing 100876 Peoples R China

ISBN: (纸本)9781538681787

Sensitive text recognition has become an important technical means to maintain the harmonious development of network environment. this paper proposes a document sensitivity calculation method (SDC) based on semantic dependencies. this method associates the sensitivity of vocabulary with its semantic roles in sentences, and uses sequence annotation instead of dictionary matching. According to the semantic dependency relation, the sensitivity direction of the sentence is determined, and the sensitive vector of sentence and document level is obtained. A number of classifiers are used for comparison experiments at all levels of sensitive document sets. the experimental results show that the SVM classifier has achieved more than 80% F-measurement in all levels of documents, which is more than 10% higher than that of the control experiment. SDC algorithm reduces the propagation and diffusion of sensitive text by efficiently recognizing sensitive text.

关键词： Document sensitivity semantic role semantic dependency sensitive vector classifier

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