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1995 Euromicro Workshop on Parallel and distributed Processing

作者： Boianov, Lüben Jelly, Lines Laboratory for Distributed Systems and Computer Networks CICT Bulgarian Academy of Sciences Acad. G. Bonchev Str. bl. 25-A Sofia1113 Bulgaria Computing Research Centre School of Computing and Management Sciences Sheffield Hallam University SheffieldS11 8HD United Kingdom

ISBN: (纸本)0818670312

The implementation of a distributed digital logic simulation algorithm on a network of workstations is presented. The simulation of digital circuits is done using a demand driven approach. The simulation is performed on a network of workstations using the Parallel Virtual Machine (PVM) software. The use of the PVM as a platform for parallel and distributed applications is assessed in the light of the test results. The feasibility of running parallel logical simulation algorithms on such platform is considered. © 1995 IEEE.

关键词： Timing circuits

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Efficient and deadlock-free reconfiguration for source routed networks

Efficient and deadlock-free reconfiguration for source route...

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International Symposium on Parallel and distributed Processing (IPDPS)

作者： Ashild Gronstad Solheim Olav Lysne Aurelio Bermudez Rafael Casado Thomas Sodring Tor Skeie Antonio Robles-Gomez Networks and Distributed Systems Group Simula Research Laboratory Lysaker Norway Department of Informatics University of Oslo Oslo Norway Computing Systems Department University of Castilla-La Mancha Albacete Spain Simula Research Laboratory Networks and Distributed Systems Group Lysaker Norway

Overlapping Reconfiguration is currently the most efficient method to reconfigure an interconnection network, but is only valid for systems that apply distributed routing. This paper proposes a solution which enables utilization of Overlapping Reconfiguration in a source routed environment. We demonstrate how a synchronized injection of tokens has a significant impact on the performance of the method. Furthermore, we propose and evaluate an optimization of the original algorithm that reduces (and in some cases even eliminates) performance issues caused by the token forwarding regime, such as increased latency and decreased throughput.

关键词： System recovery Routing Synchronization Delay Throughput Fabrics Switches Laboratories Informatics Computer networks

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An efficient local address generation for the block-cyclic distribution 3

An efficient local address generation for the block-cyclic d...

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3rd International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 1997

作者： Kwon, Oh-Young Kim, Tae-Geun Han, Tack-Don Yang, Sung-Bong Kim, Shin-Dug Distributed Computing Lab. Systems Engineering Research Institute 1 Ueun-dong Yusong-gu Taejon305-333 Korea Republic of Parallel Processing System Laboratory Dept. of Computer Science Yonsei University Seoul120-749 Korea Republic of

ISBN: (纸本)0780342291

In order to generate local addresses for an array section A(l:h:s) with block-cyclic distribution, an efficient compiling method is required. In this paper, two local address generation methods for the block-cyclic distribution are presented. One is a simple local address generation method that is modified from the virtual-block scheme. The other is a linear-time ΔM table construction method. The array elements of A(l:h:s) to be accessed at run-time build up a family of lines. By using the equation of the lines, a ΔM table can be generated in O(k) time. Experimental results show that a simple local address generation method has poor performance but a linear-time ΔM table generation method is faster than other algorithms in ΔM table generation time and access time for 10,000 array elements. © 1997 IEEE.

关键词： Virtual addresses

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Towards a Deep Learning Pain-Level Detection Deployment at UAE for Patient-Centric-Pain Management and Diagnosis Support: Framework and Performance Evaluation

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Procedia computer science 2023年 220卷 339-347页

作者： Leila Ismail Muhammad Danish Waseem Clouds and Distributed Computing and Systems (CLOUDS) Lab School of Computing and Information Systems Faculty of Engineering and Information Technology The University of Melbourne Australia. Intelligent Distributed Computing and Systems (INDUCE) Research Laboratory Department of Computer Science and Software Engineering College of Information Technology United Arab Emirates University UAE. National Water and Energy Center United Arab Emirates University UAE.

The outbreak of the COVID-19 pandemic revealed the criticality of timely intervention in a situation exacerbated by a shortage in medical staff and equipment. Pain-level screening is the initial step toward identifying the severity of patient conditions. Automatic recognition of state and feelings help in identifying patient symptoms to take immediate adequate action and providing a patient-centric medical plan tailored to a patient's state. In this paper, we propose a framework for pain-level detection for deployment in the United Arab Emirates and assess its performance using the most used approaches in the literature. Our results show that a deployment of a pain-level deep learning detection framework is promising in identifying the pain level accurately.

关键词： Computer Vision Deep Learning Image Processing Machine Learning Pain Detection Patient-Centric Smart healthcare eHealth

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Unprecedented Smart Algorithm for Uninterrupted SDN Services During DDoS Attack

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Computers, Materials & Continua 2022年第1期70卷 875-894页

作者： Muhammad Reazul Haque Saw Chin Tan Zulfadzli Yusoff Kashif Nisar Rizaludin Kaspin Iram Haider Sana Nisar J.P.C.Rodrigues Bhawani Shankar Chowdhry Muhammad AslamUqaili Satya Prasad Majumder Danda B.Rawat Richard Etengu Rajkumar Buyya Faculty of Computing&Informatics Multimedia UniversityPersiaranMultimediaCyberjaya63100SelangorMalaysia Faculty of Engineering Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Computing and Informatics University Malaysia SabahJalan UMSKota Kinabalu Sabah88400Malaysia Telekom Malaysia Research&Development TM Innovation Centre63000CyberjayaSelangorMalaysia Federal University of Piauí(UFPI) TeresinaPIBrazil Instituto de Telecomunica珲es 6201-001Covilh?Portugal National Center of Robotics and Automation-Condition Monitoring Systems Lab MUETJamshoroPakistan Department of Electrical and Electronic Engineering BUETDhaka1205Bangladesh Department of Electrical Engineering and Computer Science Data Science and Cybersecurity CenterHoward UniversityWashingtonDCUSA Cloud Computing and Distributed Systems(CLOUDS)Laboratory School of Computing and Information SystemsThe University of MelbourneMelbourneVIC 3053Australia

In the design and planning of next-generation Internet of Things(IoT),telecommunication,and satellite communication systems,controller placement is crucial in software-defined networking(SDN).The programmability of the SDN controller is sophisticated for the centralized control system of the entire ***,it creates a significant loophole for the manifestation of a distributed denial of service(DDoS)attack ***,recently a distributed Reflected Denial of Service(DRDoS)attack,an unusual DDoS attack,has been ***,minimal deliberation has given to this forthcoming single point of SDN infrastructure failure ***,recently the high frequencies of DDoS attacks have increased *** this paper,a smart algorithm for planning SDN smart backup controllers under DDoS attack scenarios has *** proposed smart algorithm can recommend single or multiple smart backup controllers in the event of DDoS *** obtained simulated results demonstrate that the validation of the proposed algorithm and the performance analysis achieved 99.99%accuracy in placing the smart backup controller under DDoS attacks within 0.125 to 46508.7 s in SDN.

关键词： SDN smart algorithm RTZLK-DAASCP DDoS attack DRDoS

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Performance measurements of a small-scale VOD server based on the UNIX

Performance measurements of a small-scale VOD server based o...

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IEEE International Conference on Performance, computing and Communications (IPCCC)

作者： Jong Moon Sohn Gil Yong Kim Tae Geun Kim Distributed Computing Laboratory Systems Engineering Research Institute South Korea Department of Computer Engineering Pusan National University South Korea

ISBN: (纸本)0780344685

Recent progress in network technologies has made it possible to integrate digital video and audio into distributed computing environments. Among the various distributed multimedia applications, video-on-demand (VOD) services are the most typical application area. However, interest in large-scale VOD systems is gradually transferring to small and low-cost VOD systems because of the excess investment required in the transmission media. When we make a small-scale VOD system, one of the most important factors is the efficient resource management of the VOD server in order to achieve cost-effectiveness. Thus, multimedia has generated widespread interest in real-time and high-performance I/O support within general-purpose operating systems. This paper presents the performance of a small-scale, UNIX-based VOD server equipped with a real-time scheduler and a continuous media file system (CMFS). The real-time scheduler is based on the theory of non-preemptive real-time systems to test schedulability within polynomial time. To reduce interference of the interrupt processing for the real-time processes, the processes are classified into two groups in order of importance. The CMFS has been designed and implemented to acquire the performance of the raw disk. According to the analysis of the measured data, UNIX can efficiently transfer video data from disk to network and it can also guarantee most deadlines.

关键词： Measurement Real time systems Network servers distributed computing Large-scale systems Investments Resource management Multimedia systems Operating systems File servers

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HealthEdge: A Machine Learning-Based Smart Healthcare Framework for Prediction of Type 2 Diabetes in an Integrated IoT, Edge, and Cloud computing System

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Procedia Computer Science 2023年 220卷 331-338页

作者： Alain Hennebelle Huned Materwala Leila Ismail Independent Researcher Melbourne Australia Intelligent Distributed Computing and Systems (INDUCE) Research Laboratory Department of Computer Science and Software Engineering College of Information Technology United Arab Emirates University United Arab Emirates National Water and Energy Center United Arab Emirates University United Arab Emirates Cloud Computing and Distributed Systems (CLOUDS) Lab School of Computing and Information Systems The University of Melbourne Australia

Diabetes Mellitus has no permanent cure to date and is one of the leading causes of death globally. The alarming increase in diabetes calls for the need to take precautionary measures to avoid/predict the occurrence of diabetes. This paper proposes HealthEdge, a machine learning-based smart healthcare framework for type 2 diabetes prediction in an integrated IoT-edge-cloud computing system. Numerical experiments and comparative analysis were carried out between the two most used machine learning algorithms in the literature, Random Forest (RF) and Logistic Regression (LR), using two real-life diabetes datasets. The results show that RF predicts diabetes with 6% more accuracy on average compared to LR.

关键词： Artificial Intelligence (AI) Cloud computing Diagnosis Digital Health Edge computing eHealth Internet of Things (IoT) Logisitic Regression Machine Learning Prognosis Random Forest Risk Factors Smart Connected Healthcare Type 2 Diabetes Mellitus

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UNPCC: A novel unsupervised classification scheme for network intrusion detection

UNPCC: A novel unsupervised classification scheme for networ...

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18th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2006

作者： Xie, Zongxing Quirino, Thiago Shyu, Mei-Ling Chen, Shu-Ching Chang, LiWu Department of Electrical and Computer Engineering University of Miami Coral Gables FL 33124 United States Distributed Multimedia Information System Laboratory School of Computing and Information Sciences Florida International University Miami FL United States Center for High Assurance Computer Systems Naval Research Laboratory Washington DC United States

ISBN: (纸本)0769527280

The development of effective classification techniques, particularly unsupervised classification, is important for real-world applications since information about the training data before classification is relatively unknown. In this paper, a novel unsupervised classification algorithm is proposed to meet the increasing demand in the domain of network intrusion detection. Our proposed UNPCC (Unsu-pervised Principal Component Classifier) algorithm is a multi-class unsupervised classifier with absolutely no requirements for any a priori class related data information (e.g., the number of classes and the maximum number of instances belonging to each class), and an inherently natural supervised classification scheme, both which present high detection rates and several operational advantages (e.g., lower training time, lower classification time, lower processing power requirement, and lower memory requirement). Experiments have been conducted with the KDD Cup 99 data and network traffic data simulated from our private network testbed, and the promising results demonstrate that our UNPCC algorithm outperforms several well-known supervised and unsupervised classification algorithms. © 2006 IEEE.

关键词： Intrusion detection

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Collateral representative subspace projection modeling for supervised classification

Collateral representative subspace projection modeling for s...

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18th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2006

作者： Quirino, Thiago Xie, Zongxing Shyu, Mei-Ling Chen, Shu-Ching Chang, LiWu Department of Electrical and Computer Engineering University of Miami Coral Gables FL 33124 United States Distributed Multimedia Information System Laboratory School of Computing and Information Sciences Florida International University Miami FL 33199 United States Center for High Assurance Computer Systems Naval Research Laboratory Washington DC 20375 United States

ISBN: (纸本)0769527280

In this paper, a novel supervised classification approach called Collateral Representative Subspace Projection Modeling (C-RSPM) is presented. C-RSPM facilitates schemes for collateral class modeling, class-ambiguity solving, and classification, resulting a multi-class supervised classifier with high detection rate and various operational benefits including low training and classification times and low processing power and memory requirements. In addition, C-RSPM is capable of adaptively selecting nonconsecutive principal dimensions from the statistical information of the training data set to achieve an accurate modeling of a representative subspace. Experimental results have shown that the proposed C-RSPM approach outperforms other supervised classification methods such as SIMCA, C4.5 decision tree, Decision Table (DT), Nearest Neighbor (NN), KNN, Support Vector Machine (SVM), 1-NN Best Warping Window DTW, 1-NN DTW with no Warping Window, and the well-known classifier boosting method AdaBoost with SVM. © 2006 IEEE.

关键词： Classification (of information)

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distributed logic circuit simulation on a network of workstations

Distributed logic circuit simulation on a network of worksta...

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Euromicro Workshop on Parallel and distributed Processing

作者： L. Boianov I. Jelly Laboratory for Distributed Systems and Computer Networks CICI Bulgarian Academy of Sciences Sofia Bulgaria Computing Research Centre School of Computing and Management Sciences Sheffield Hallam University Sheffield UK

关键词： Logic circuits Circuit simulation Workstations Computational modeling Computer network management Digital circuits Application software Parallel algorithms Parallel processing Partitioning algorithms

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