Search Results - (( demand distributed database algorithm ) OR ( java adaptation optimization algorithm ))

Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

Optimize performance load balancing techniques using binary vote assignment grid quorum (BVAGQ): A systematic review by A., Fairuzullah, A., Noraziah, R. A., Arshah, T., Herawan

“…This replication generally referred as mechanism to improve availability and performance in distributed databases especially handling fragmented database replication becomes demanding issue. …”
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Performance evaluation of task scheduling using hybrid meta-heuristic in the heterogeneous cloud environment by Mohammed, Faten Ameen Saif

“…The essential role of cloud computing is enabling sharing of resources on-demand over the network (e.g. servers, applications, storage, services and database) to the end-users that are distributed geographically. …”
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Load demand analysis for high rise residentals of Petaling Jaya by Ng, Pik San

Re-engineering grid-based quorum replication into binary vote assignment on cloud: A scalable approach for strong consistency in cloud databases by Ainul Azila Che Fauzi, Ainul Azila, Noor Ashafiqa, Noor Ashafiqa, Asiah Mat, Asiah, Syerina Azlin Md Nasir, Syerina Azlin, A. Noraziah, Noraziah

“…The growth of cloud computing has heightened the demand for replication strategies that ensure strong consistency, high availability, and low communication cost across distributed infrastructures. …”
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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata by Md Shah, Wahidah, Othman, Mohd Fairuz Iskandar, Hussian Hassan, Ali Abdul, Talib, Mohammed Saad, Mohammed, Ali Abdul Jabbar

“…K Nearest Neighbor Joins (KNN join) are regarded as highly primitive and expensive operations in the data mining.The efficient use of KNN join has proven good results in finding the objects from two data sets prevailed in the huge databases.This has been achieved with the combination of K-Nearest Neighbor query and join operation to find the distinct objects from different data sets.MapReduce is a newly introduced program with the combination of Map Procedure method and Reduce Method widely used in BigData.MapReduce is enriched with parallel distributed algorithm to find the results on a cluster of data sets in BigData.In this paper,the combination of KNN join and MapReduce methods are utilized on the cluster of data sets in BigData for knowledge discovery.Exploring the pinpoint data from huge data sets stored in Big Data demands the distributed large scale data processing.The present research paper is focusing on generic steps for KNN joins exploration operations on MapReduce.The operations of KNN Join are targeted to perform the data partitioning and data pre-processing and necessary calculations.By utilizing the combination of KNN joins with MapReduce methods on BigData data sets will demonstrate a solution for complex computational analysis. …”
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Logistics center location-inventory-routing problem optimization: a systematic review using PRISMA method by Liu, Lihua, Lee, Lai Soon, Seow, Hsin Vonn, Chen, Chuei Yee

“…A total of 112 LIRP-related studies published between 2010 and 2021 are reviewed and classified based on 10 abstract and citation databases. The classification includes four aspects: problem characteristics, demand data types, model-based solutions, and application fields. …”
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