Search Results - (( loading optimisation _ algorithm ) OR ( data optimization based algorithm ))
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Optimising cloud computing performance with an enhanced dynamic load balancing algorithm for superior task allocation
Published 2024“…This paper presents an Enhanced Dynamic Load Balancing (EDLB) algorithm designed to optimise task scheduling and resource allocation in cloud environments. …”
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Optimisation model for scheduling MapReduce jobs in big data processing / Ibrahim Abaker Targio Hashem
Published 2017“…With the fast development of Internet-based technologies, data generation has increased drastically over the past few years, coined as big data era. …”
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Distributed learning based energy-efficient operations in small cell networks
Published 2023“…To achieve these goals, a cell selection algorithm is proposed that overcomes the issues of conflicts and load imbalance while reducing energy consumption. …”
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Wireless network power optimization using relay stations blossoming and withering technique
Published 2017“…The effect of the rate of active relays, arrival rate and average load factor of relays on the total network power consumption is modelled. …”
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A self‐configured link adaptation for green LTE downlink transmission
Published 2015“…Then, a self‐configured link adaptation (SCLA) algorithm is developed to ensure that the priority weights related to EE and SE are adapted according to network load with the use of real‐time cross‐layer optimization. …”
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Modelling of optimal placement and sizing of battery energy storage system using hybrid whale optimization algorithm and artificial immune system for total system losses reduct...
Published 2023“…Lastly, the effectiveness of WOA and WOA-AIS in attaining optimal solutions was validated with other well-known optimisation algorithms, including particle swarm optimisation (PSO) and firefly algorithm (FA). …”
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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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Optimisation of PID controller for load frequency control in two-area power system using evolutionary particle swarm optimisation
Published 2016“…Hence, by implementing an optimisation method, the performance of the LFC can be optimised through optimising the PID controller parameters.…”
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Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network
Published 2022“…Finally, an AHP was integrated with FA to form Firefly Analytical Hierarchy Algorithm (FAHA) to automatically calculate the weight of each objective function based on the load flow outputs followed by the optimisation process. …”
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Optimisation of automatic generation control performance in two-area power system with pid controllers using mepso / Lu Li
Published 2018“…From the simulation results, it was found that with the same number of PID controllers, the performance of AGC optimised by using MEPSO-TVAC algorithm is better in terms of overshoot and fitness value than using EPSO and PSO algorithms. …”
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Embedded Meta evolutionary-firefly algorithm-ANN for multi dg planning in distribution system / Siti Rafidah Abdul Rahim
Published 2019“…Thus, a reliable optimisation technique is crucial to address this issue. …”
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A new optimisation framework based on Monte Carlo embedded hybrid variant mean–variance mapping considering uncertainties
Published 2024“…The MVMO-SH had the lowest APL index compared to genetic algorithm and particle swarm optimisation when the probabilistic power flow with PVDG was optimised under uncertainty. …”
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Metaheuristic multi-hop clustering optimization for energy-efficient wireless sensor network
Published 2020“…Based on the performance evaluation, GACS outperforms both Genetic Algorithm (GA)-based cluster optimization algorithm and Cuckoo Search (CS)-based multi-hop optimization algorithm.…”
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Immunized-evolutionary algorithm based technique for loss control in transmission system with multi-load increment
Published 2023“…This paper presents immunized-evolutionary algorithm based technique for loss control in transmission system with multi -load increment. …”
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Optimization of electrical wiring design in buildings using particle swarm optimization and genetic algorithm / Tuan Ahmad Fauzi Tuan Abdullah
Published 2017“…The electrical wiring system design includes sizing of cables and bus ducts, customers’ load and placement of load, cables and bus ducts. …”
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An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning
Published 2019“…BOCEDS clusters the data stream in a single stage. The algorithm summarizes the data from data stream in micro-clusters. …”
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