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Optimizing Energy Consumption of Cloud Computing IaaS
Published 2017Subjects: Get full text
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Optimized Load-Scheduling Algorithm for CubeSat's Electric Power System Management Considering Communication Link
Published 2023“…This article presents an approach for optimizing load management and scheduling in CubeSat applications to ensure optimal coordination between the load demand, power generation, and energy storage while maintaining communication's quality of service requirements, namely the data rate and bit error rate (BER). The loads are divided into four types based on their priority. …”
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GENETIC SCHEDULING OF TASK GRAPHS
Published 2020“…A genetic algorithm for scheduling computational task graphs is presented. …”
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GIJA:Enhanced geyser‐inspired Jaya algorithm for task scheduling optimization in cloud computing
Published 2024“…In this article, we introduce GIJA (Geyser‐inspired Jaya Algorithm), a novel optimization approach tailored for task scheduling in cloud computing environments. …”
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Efficient Prioritization and Processor Selection Schemes for HEFT Algorithm: A Makespan Optimizer for Task Scheduling in Cloud Environment
Published 2022“…Among these methods, the Heterogeneous Earliest Finish Time (HEFT) algorithm is recognized to produce optimal outcomes in a shorter time period for scheduling tasks in a heterogeneous environment. …”
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Proactive Fault Tolerance and Minimizing Task Execution Failure in A Cloud Data Center
Published 2024Get full text
doctoralThesis -
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Minimizing Deadline Misses of Mobile IoT Requests in a Hybrid Fog- Cloud Computing Environment
Published 2019Subjects: Get full text
doctoralThesis -
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A simulated evolution approach to task-matching and scheduling in heterogeneous computing environments
Published 2020“…Abstract This paper applies a simulated evolution (SE) approach to the problem of matching and scheduling dependent tasks in a heterogeneous suite of computers interconnected via a high-speed network. …”
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Web Based Online Hybrid Teaching Method of Network Music Course
Published 2022“…Based on Web data mining, an improved algorithm of hybrid hierarchical recommendation algorithm and genetic algorithm is used in the experiment, and compared with the other two algorithms in the experiment. …”
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Bird’s Eye View feature selection for high-dimensional data
Published 2023“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”
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Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm
Published 2022“…Researchers have scrutinized data hiding schemes in recent years. Data hiding in standard images works well, but does not provide satisfactory results in distortion-sensitive medical, military, or forensic images. …”
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Web Applications Security Testing: Genetic Algorithms Based Test Data Generator
Published 2020Get full text
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An Uncertainty Based Genetic Algorithm Approach for Project Resource Scheduling
Published 2016“…Several nonlinear optimization models were developed for this purpose assuming uniform resource availability and sequence based project tasks. The work presented in thesis add to the existing literature in a proposing the use of a genetic algorithm uncertain approach to resource- scheduling in projects. …”
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Automated Mutation-Based Test Data Generation: Genetic Algorithm Game-Like Approach
Published 2020Get full text
masterThesis -
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Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing
Published 2016Get full text
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Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering
Published 2022Subjects: “…Data clustering…”