Search Results - parallel computing ((cloud algorithm) OR (means algorithm))*
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3d Morphing And Shape Transformation Using Slices
Published 2009“…Most of the existing shape transformation algorithms involve a lot of user intervention, do not scale well when the number of input objects is more than two and are not scalable in parallel and distributed computing environment whenever needed. …”
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Quantum Particle Swarm Optimization Technique for Load Balancing in Cloud Computing
Published 2013“…Load management is the focus of research in both of the area in distributed Cloud Computing systems and centralized Cloud Computing systems. …”
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Image Segmentation With Cyclic Load Balanced Parallel Fuzzy C - Means.
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Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function
Published 2012“…The other downside of the Bee Algorithm is that it has needless computation. This means that it spends a long time for the bees algorithm converge the optimum solution. …”
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Improving energy consumption in cloud computing datacenters using a combination of energy-aware resource allocation and scheduling mechanism
Published 2017“…Nowadays, DNA plays a vital role in many computing applications due to the massive processing parallelism. …”
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The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data
Published 2024“…Apache Spark is one of the most widely used large-scale data processing engines due to its speed, low latency in-memory computing, and powerful analytics. Therefore, we develop a Parallel Fuzzy C-Median Clustering Algorithm Using Spark for Big Data that can handle large datasets while maintaining high accuracy and scalability. …”
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”
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Implementation of Parallel K-Means Algorithm to Estimate Adhesion Failure in Warm Mix Asphalt
Published 2020“…The results showed that the PKIP algorithm decreases the execution time up to 30 to 46 if compared with the sequential k means algorithm when implemented using multiprocessing and distributed computing. …”
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Critical insight for MAPReduce optimization in Hadoop
Published 2014“…Cloud applications such as data storage, data retrieval and data portability have become significant requirements for cloud computing. …”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
Published 2009“…By the means of higher performance computing, the computation cannot be relying on just one single set of cluster. …”
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One-dimensional finite element discretization of crack propagation through parallel computation
Published 2010“…We have implemented one dimensional finite element discretization to solve crack propagation problem. The parallel algorithm with parallel computer system has been used in order to perform the computational analysis of finite element for this study. …”
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Adaptive resource allocation for reliable performance in heterogeneous distributed systems.
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Peningkatan halaju suapan maksimum penginterpolasi CNC dedenyut rujukan menggunakan pengaturcaraan selari
Published 2011“…This situation is also required in interpolator algorithm. The existing interpolator is not using parallel programming which every task have not been execute simultaneous in concurrent manner although using multi-cores processor computer, thus, the more time is needed for the iteration time especially for a complex and large scale of process. …”
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An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title
Published 2019“…The enhanced method combines three transformation methods for analyzing the iris image and extracting its local features. It uses a weighted K-means clustering algorithm based on the improved FA to optimize the initial clustering centers of K-means algorithm, known as Weighted K-means clustering-Improved Firefly Algorithm (WKIFA). …”
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Hybrid metaheuristics for QOS-aware service composition / Hadi Naghavipour
Published 2022“…Efficient QoS-aware service composition has been a challenging task in cloud computing. This challenge becomes more formidable in emerging resource-constrained computing paradigms such as the Internet of Things and Fog. …”
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