Search Results - (( its application cloud algorithm ) OR ( _ application based algorithm ))*
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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
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A Penalty-Based Genetic Algorithm For The Composite Saas Placement Problem In The Cloud
Published 2010“…This paper proposes a penalty-based genetic algorithm (GA) to the composite SaaS placement problem in the Cloud. …”
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Simulated annealing approach to cost-based multi- quality of service job scheduling in cloud computing enviroment
Published 2014“…The advent of cloud computing as a new model of service provisioning in distributed systems, encourages researchers to investigate its benefits and drawbacks in executing scientific applications such as workflows. …”
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Article -
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Implementing Location-Based Cryptography on Mobile Application Design to Secure Data in Cloud Storage
Published 2024journal::journal article -
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Impatient job scheduling under cloud computing
Published 2012“…The first part focuses on review- ing the previous immediate mode scheduling and adopting them on cloud paradigm. The limitations of those algorithms were addressed and this leads to the proposition of an algorithm that has the ability to map the impatient jobs to virtual machines near its input, output, application, or forth party. …”
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Thesis -
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Task scheduling in cloud computing using hybrid genetic algorithm and bald eagle search (GA-BES)
Published 2022“…The genetic algorithm was widely used because of its accuracy and simplicity. …”
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Academic Exercise -
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Energy and performance efficient resource allocation for cloud-based data centers
Published 2015“…The underlying concept of cloud computing isthe separation of applications from the operating systems and the hardware on which they run. …”
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Online Dynamic Replication and Placement Algorithms for Cost Optimization of Online Social Networks in Two-tier Multi-cloud
Published 2024journal::journal article -
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A new priority rule cloud scheduling technique that utilizes gaps to increase the efficiency of jobs distribution
Published 2023“…These limitations lead to the poor performance of cloud-based mobile applications and other cloud services. …”
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Quantum Particle Swarm Optimization Technique for Load Balancing in Cloud Computing
Published 2013“…Researches on data Cloud Computing become the necessary trend in the distributed Cloud Computing system domain since the sources and application of the data are distributed and the scale of the applications enlarges quickly. …”
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Efficient task scheduling strategies using symbiotic organisms search algorithm for cloud computing environment
Published 2022“…The SOS and its variants Discrete Symbiotic Organisms Search (DSOS) algorithm have been used to solve different optimisation problems including tasks scheduling in cloud computing environment where results obtained are promising in comparison with stateof- the-art metaheuristic algorithms. …”
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Designing a new E-Commerce authentication framework for a cloud-based environment
Published 2024Conference Paper -
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Enhancing user authentication for cloud web-based application / Detar Beqo
Published 2018“…We have developed a cloud-based application that adapts the enhanced authentication method, and its security measurement were evaluated using IBM Application Security on Cloud tool. …”
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Efficient DNS based Load Balancing for Bursty Web Application Traffic
Published 2012“…This research proposes a new efficient load balancing algorithm which applies to the local Domain Name Service (DNS) server for web based applications and services to ease the sudden increase in demand for the services. …”
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Article -
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Fog-cloud scheduling simulator for reinforcement learning algorithms
Published 2023“…Due to its decentralized architecture, fog computing offers low latency processing and ensures the preservation of information between the source and the cloud resources. …”
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IOT-based fertigation system / Mohamad Amir Furqan Darus
Published 2024“…These sensors provide real-time data about the crops’ environment, which is then sent to a central hub or cloud platform. Advanced algorithms and machine learning processes this data to determine the ideal irrigation and fertilization needs. …”
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