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Research ArticleOpen accessIn the abstractMulti Resources and Constraints Based Consolidation Model to Mitigate the Energy ExtravaganceArchana Patil, Rekha PatilTo design green clouds with optimal energy and resource consumption, the host consolidation process became the most prominent cloud management policy today. In case of a consolidation, the underloaded host's VMs are shifted to the other hosts to control the energy extravagance at a data center. The consolidation process is considered an NP-hard problem, as it depends on several computational … …Journal of Computer Science, Vol. 18, Issue 7 · 28 Jul 2022 · 5,861 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting of Multistep Multivariate Financial Data Through GSO Algorithm Infused Vanilla LSTM ModelNikhitha Pai, Ilango Velchamy, Nithya B RameshPredicting time series in the financial domain requires using models that can do sequence processing tasks. One such model is the LSTM model which belongs to the family of deep learning networks. The performance measure of LSTM in a regression task is to bring down the error in the predicted values. In this study, a novel fused LSTM model integrating … …Journal of Computer Science, Vol. 19, Issue 7 · 10 Jul 2023 · 6,074 accessesView PDFCite
Review ArticleOpen accessIn the abstractRRDTool: A Round Robin Database for Network MonitoringManmohan Singh, Sweta Dargada, Hemant Mewada et al.RRDtool is a circular database that stores time series data. RRD tool assumes time-variable data inintervals of a certain length. An interval is named as a step, and specifiedupon creation of an RRD file which cannot be changed afterward. Because datamay not always come at just the right time, RRD tool will automaticallyinterpolate any submitted data. This is done to … …Journal of Computer Science, Vol. 18, Issue 8 · 27 Aug 2022 · 8,350 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnomaly Detection Algorithms for Streaming Data: Performance ComparisonZirije HasaniToday’s most of the data are streaming time-series data, where is very important anomaly detection over this data because gives significant information of possible critical situations. Detecting anomalies in big streaming data is yet difficult task because we have to process them in real time, even before they are stored and instantly alarm on potential threats. For real time streaming … …Journal of Computer Science, Vol. 16, Issue 7 · 18 Jul 2020 · 7,288 accessesView PDFCite
Research ArticleOpen accessIn the abstractFeasibility Analysis of Non-Preemptive Periodic Systems from Infeasibility PerspectiveNasro Min-AllahDue to simple implementation, non-preemptive scheduling has the advantage over preemptive counterpart when it comes to deployment of real-time systems. Accordingly, many feasibility techniques have been established to answer schedulability of the task set for non-preemptive case. The time complexity of exact condition for non-preemptive under dynamic priority assignment is of pseud-polynomial nature. Recently, efforts are made to decrease the … …Journal of Computer Science, Vol. 15, Issue 9 · 9 Sep 2019 · 7,617 accessesView PDFCite
Research ArticleOpen accessIn the abstractConjugate Gradient ‎Method: A Developed Version to Resolve Unconstrained Optimization ProblemsAhmad Alhawarat, Nguyen-Thoi Trung, Zabidin SallehOne of the important methods that are widely utilized to resolve ‎unconstrained ‎optimization problems is the Conjugate Gradient (CG) method. This paper aims to propose a new version of the CG method on the basis of Weak Wolfe-Powell (WWP) line search. The assumption is bounded below optimization problems with the Lipschitz continuous gradient. The new parameter obtains global convergence properties … …Journal of Computer Science, Vol. 16, Issue 9 · 18 Sep 2020 · 6,887 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Method to Predict Processor Performance by Modeling Different Architecture ParametersJoseph IssaPredicting processor throughput and performance is one of the essential aspects of computer architecture. It is crucial to model processor performance behavior for future architectures based on the existing data set. Modeling processor performance for a given workload enables architects to enhance processor features to meet specific performance targets for a given benchmark. Developing an estimation method to predict performance … …Journal of Computer Science, Vol. 16, Issue 4 · 22 Apr 2020 · 7,317 accessesView PDFCite
Research ArticleOpen accessIn the abstractDecentralized Predictive Secure VS Placement in Cloud EnvironmentSuresh Baliram Rathod, Vuyyuru Krishna ReddyHosts in distributed cloud environment configured with Local Resource Monitors (LRM) that runs autonomously, monitors underlying host’s resource usage and balances underlying host’s resource usage by migrating Virtual Machine (VM) to other hosts. LRM takes decision for VM migration at fixed interval considering own current CPU usage and the other hosts CPU usage. The peer hosts unawares about the decision … …Journal of Computer Science, Vol. 14, Issue 3 · 21 Mar 2018 · 7,905 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Analysis of Deep Learning Libraries: TensorFlow and PyTorchFelipe Florencio, Thiago Valenç, Edward David Moreno, Methanias Colaço JuniorThrough the increase in deep learning study and use, in the last years there was a development of specific libraries for Deep Neural Network (DNN). Each one of these libraries has different performance results and applies different techniques to optimize the implementation of algorithms. Therefore, even though implementing the same algorithm and using different libraries, the performance of their executions … …Journal of Computer Science, Vol. 15, Issue 6 · 11 Apr 2019 · 10,293 accessesView PDFCite
Research ArticleOpen accessIn the abstractHYBRID IMPLEMENTATION AND PERFORMANCE ANALYSIS FOR HIGH PERFORMANCE COMPUTATION WORKLOADJoseph IssaGiven the need to achieve maximum performance possible, offloading intensive computation workload to GPU is a key to achieve this goal. Offloading most of the workload to GPU may not results in desired performance, so a middle approach is more suitable such as splitting the workload between the CPU and the GPU can be considered as an optimized approach. In … …Journal of Computer Science, Vol. 10, Issue 9 · 26 Apr 2014 · 6,514 accessesView PDFCite