the proceedings contain 136 papers. the topics discussed include: a survey paper on computer aided detection of tuberculosis;sentiment analysis approaches, types, challenges, and applications: an exploratory analysis;...
ISBN:
(纸本)9781665454018
the proceedings contain 136 papers. the topics discussed include: a survey paper on computer aided detection of tuberculosis;sentiment analysis approaches, types, challenges, and applications: an exploratory analysis;enigmas in emotion detection techniques tools: challenges and concerns;analysis of apple plant leaf diseases detection and classification: a review;does metaverse a technological revolution in artificial intelligence? a bibliometric analysis;credit card fraud detection using machine learning, deep learning, and ensemble of the both;machine learning based data classification methods in cloud security using cloudlightning framework;parallel chaos hash based LSB steganography technique using logistic map;a review on sentiment analysis of twitter data for diabetes classification and prediction;an analysis of deep learning models for detection of COVID-19 diseases;and engagement measurement of a learner during e-learning: a deep learning architecture.
the proceedings contain 58 papers. the topics discussed include: load balancing optimization using the algorithm DEPRO in a distributed environment;modeling resource prices in grid markets;MIP model scheduling for BSP...
the proceedings contain 58 papers. the topics discussed include: load balancing optimization using the algorithm DEPRO in a distributed environment;modeling resource prices in grid markets;MIP model scheduling for BSP parallel applications on multi-cluster environments;analysis of the BitTorrent protocol modified with fountain code;data replication in P2P collaborative systems;large-scale mining of co-occurrences: challenges and solutions;implementing hadoop platform on eucalyptus cloud infrastructure;a data reception method to reduce interruption time for model and motion separated data in P2P streaming environments;distributed systems in the wild: the theoretical foundations and experimental perspectives;parallel perspectives: reverse engineering for generation multi-X;parallel enhanced hybrid evolutionary algorithm for continuous function optimization;and analysis of the BitTorrent protocol modified with multicast.
Artificial Intelligence is an interdisciplinary field that combines Machine Learning, Big Data, Cloud computing, and Information theory. the major advantage of machine learning is that it builds on prior experience, s...
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Main characteristics of large-scale, geographically distributedgrid systems are resource heterogeneity and network latency. In this paper, we use queuing network models to analyze data-parallelgrid applications and ...
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ISBN:
(纸本)9781424403431
Main characteristics of large-scale, geographically distributedgrid systems are resource heterogeneity and network latency. In this paper, we use queuing network models to analyze data-parallelgrid applications and we show the effects of resource heterogeneity, communications delays, network bandwidths and synchronization overheads on the application-level performance. the proposed models rely on the statistical pattern of computation, communication, and I/O operations in the parallel applications, as well as on measurable infrastructure characteristics. We finally show how the high variability in the execution and communication times must be considered when modeling applications on geographically distributedgrid infrastructures.
this paper presents a High Performance computing-based application for 3D structural analysis of buildings. Since the solution of a large linear system of sparse equations supposes the most time-consuming phase, sever...
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this paper presents a High Performance computing-based application for 3D structural analysis of buildings. Since the solution of a large linear system of sparse equations supposes the most time-consuming phase, several public domain parallel numerical libraries, with state-of-the-art capabilities, have been tested. the parallel application developed allows reducing the analysis time and simulating larger structures. Nevertheless, structural engineers rarely have available high cost parallel machines. thus, a grid Structural Analysis service, that integrates the parallel application, has been implemented, taking advantage of computers geographically distributed in Internet. this service makes it possible to simulate in a realistic way, and concurrently, a high number of different structural alternatives of large dimension buildings during their design stage, without considering structural simplifications or investing in expensive computers. (c) 2006 Elsevier Ltd. and Civil-Comp Ltd. All rights reserved.
this paper studies the QoS-aware replica placement problem. Although there has been much work on replica placement problem, most of them concerns average system performance and ignores quality assurance issue. Quality...
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ISBN:
(纸本)9781424403431
this paper studies the QoS-aware replica placement problem. Although there has been much work on replica placement problem, most of them concerns average system performance and ignores quality assurance issue. Quality assurance is very important, especially in heterogeneous environments. We propose a new heuristic algorithm that determines the positions of replicas in order to satisfy the quality requirements imposed by data requests. the experimental results indicate that the proposed algorithm finds a near-optimal solution effectively and efficiently for algorithm can also adapt to various parallel and distributed environments.
In this paper we propose a systematic approach to performance analysis of workflow applications on the grid. We introduce an ideal model for the workflow execution time and explain the difference to the real measured ...
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ISBN:
(纸本)9781424403431
In this paper we propose a systematic approach to performance analysis of workflow applications on the grid. We introduce an ideal model for the workflow execution time and explain the difference to the real measured times based on a hierarchy of performance overheads for gridcomputing. We describe how to systematically measure and compute the overheads from individual activities to entire workflow applications. We adjusted well-known parallel processing metrics to the scope of gridcomputing, comprising speedup and efficiency. We have implemented and largely automatised our analysis approach in the context of the ASKALON grid application development and computing environment. We present experimental results that show detailed overhead analysis of two real-world workflow applications executed in a national grid environment.
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