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Performance evaluation and enhancement of EDCA protocol to improve the voice capacity in wireless network
Published 2017“…The OPNET simulator and the mathematical model were used to evaluate the performance for the proposed algorithm. …”
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Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems
Published 2014“…The designed algorithms are implemented for EHD equations and their performance is evaluated by using different performance indicators. …”
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DESIGN AND EVALUATION OF RESOURCE ALLOCATION AND JOB SCHEDULING ALGORITHMS ON COMPUTATIONAL GRIDS
Published 2012“…The issue is not only to develop new algorithms, but also to evaluate them on an experimental computational grid, using synthetic and real workload traces, along with the other existing job scheduling algorithms. …”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
Published 2017“…In the preliminary study, the algorithm is evaluated on the four different peak models of the three EEG signals using the artificial neural network (ANN) with particle swarm optimization (PSO) as learning algorithm. …”
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Quality of service management algorithms in WiMAX networks
Published 2015“…Simulation have been extensively used to evaluate the proposed algorithm. …”
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A comparative study for parameter selection in online auctions
Published 2009“…Self adaptation genetic algorithm is the last model that will be used to evolve the bidding strategy. …”
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Replica Creation Algorithm for Data Grids
Published 2012“…The new Data Replica Creation Algorithm (DRCM) improves performance of data grid systems by reducing job execution time and making the best use of data grid resources (network bandwidth and storage space). …”
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Performance evaluation of load balancing algorithm for virtual machine in data centre in cloud computing
Published 2018“…Cloud computing has become biggest buzz in the computer era these days.It runs entire operating systems on the cloud and doeverything on cloud to store data off-site.Cloud computing is primarily based on grid computing, but it’s a new computational model.Cloud computing has emerged into a new opportunity to further enhance way of hosting data centre and provide services.The primary substance of cloud computing is to deal the computing power,storage,different sort of stages and services which assigned tothe external users on demand through the internet.Task scheduling in cloud computing is vital role optimisation and effective dynamic resource allocation for load balancing.In cloud, the issue focused is under utilisation and over utilisation of the resources to distribute workload of multiple network links for example,when cloud clients try to access and send request tothe same cloud server while the other cloud server remain idle at that moment, leads to the unbalanced of workload on cloud data centers.Thus, load balancing is to assign tasks to the individual cloud data centers of the shared system so that no single cloud data centers is overloaded or under loaded.A Hybrid approach of Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm is combined in order to get effective response time.The proposed hybrid algorithm has been experimented by using CloudSim simulator.The result shows that the hybrid load balancing algorithm improves the cloud system performance by reducing the response time compared to the Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm.…”
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A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network
Published 2023“…The dataset development for both algorithms is carried out via simulations in Graphical Network Simulator 3 (GNS3). …”
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Simulation model to improve QoS performance over fixed WiMAX using OPNET
Published 2013“…The design has been evaluated using the simulation tool OPNET modeler 16.0. …”
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Impatient job scheduling under cloud computing
Published 2012“…The proposed system is evaluated via simulation using synthetic data. F rom the results, the proposed algorithm improved the jobs throughput by reducing jobs waiting time by 8 1 .5 % , allowing more jobs to meet their deadlines.…”
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Q-learning based vertical handover decision algorithm in LTE-A two-tier macrocell-femtocell systems / Ammar Bathich
Published 2019“…The proposed handover algorithms are validated using the LTE-Sim simulator under an urban environment. …”
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A federated usage control framework with ontology-based policy and elimination of irrelevant rules set algorithm for grid computing authorization
Published 2019“…This thesis aims at providing solutions to the problem by introducing an authorization framework, namely the Federated Grid Usage Control (FGUC) with a new ontology-based policy model, namely, the UCON based Access Control Ontology (UBACO), and a new grid authorization algorithm, namely, the Elimination of the Irrelevant Authorization Rules Set (EIARS). …”
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15
Detection of multiple outliners in linear regression using nonparametric methods
Published 2004“…REFERENCES Agullo, J. (2000). New Algorithms for Computing the Least Trimmed Squares Regression Estimator. …”
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Furniture form innovation and human–machine comfort evaluation model based on genetic algorithm
Published 2024“…Afterward, a mathematical version is used to symbolize the layout preference problems, and the layout scheme selection method is simulated. …”
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3D virtual modelling and stabilization control of triple links inverted pendulum on two-wheeled system using enhanced interval type-2 fuzzy logic control
Published 2020“…This modelling technique also allow provides visualization for user to evaluate the performance of the system. The completed model system is further incorporated with Matlab/Simulink for analysis, control design and evaluation purposes. …”
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Improving Adaptive Quality of Service for Multimedia Wireless Networks Using Hierarchical Networks Approach
Published 2004“…Scenario A represents an area with 80% slow speed users and 20% fast speed users, Scenario B represents an area with a population of 40% slow speed users and 60% fast speed users while Scenario C represents an area with 20% slow speed users and 80% fast speed users. …”
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State-Aware re-configuration model for multi-radio wireless Mesh Networks
Published 2017“…The ns-2 simulator is used as simulation tool and various metrics are evaluated. …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis
