Fog Computing(FC)provides processing and storage resources at the edge of the Internet of Things(IoT).By doing so,FC can help reduce latency and improve reliability of IoT *** energy consumption of servers and computi...
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Fog Computing(FC)provides processing and storage resources at the edge of the Internet of Things(IoT).By doing so,FC can help reduce latency and improve reliability of IoT *** energy consumption of servers and computing resources is one of the factors that directly affect conservation costs in fog *** consumption can be reduced by efficacious scheduling methods so that tasks are offloaded on the best possible *** deal with this problem,a binary model based on the combination of the Krill Herd algorithm(KHA)and the Artificial hummingbird algorithm(AHA)is introduced as Binary KHA-AHA(BAHA-KHA).KHA is used to improve ***,the BAHA-KHA local optimal problem for task scheduling in FC environments is solved using the dynamic voltage and frequency scaling(DVFS)*** Heterogeneous Earliest Finish Time(HEFT)method is used to discover the order of task flow *** goal of the BAHA-KHA model is to minimize the number of resources,the communication between dependent tasks,and reduce energy *** this paper,the FC environment is considered to address the workflow scheduling issue to reduce energy consumption and minimize makespan on fog *** results were tested on five different workflows(Montage,CyberShake,LIGO,SIPHT,and Epigenomics).The evaluations show that the BAHA-KHA model has the best performance in comparison with the AHA,KHA,PSO and GA *** BAHA-KHA model has reduced the makespan rate by about 18%and the energy consumption by about 24%in comparison with *** is a preview of subscription content,log in via an institution to check access.
Meeting low-carbon objectives requires a heightened emphasis on adopting novel energy technologies. Among these,microgrid technology has gained considerable prominence for integrating renewable energy sources into dai...
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ISBN:
(数字)9789887581581
ISBN:
(纸本)9798350366907
Meeting low-carbon objectives requires a heightened emphasis on adopting novel energy technologies. Among these,microgrid technology has gained considerable prominence for integrating renewable energy sources into daily life. This paper introduces a novel multi-objective optimal dispatching model tailored for grid-connected microgrids. Initially, a comprehensive microgrid system incorporating photovoltaic(PV), wind turbine(WT), diesel generator(DE), micro gas turbine(MT), and energy storage device(ESS) is thoroughly examined. Subsequently, this paper innovatively applies the Multi-Objective Artificial hummingbird Optimisation algorithm(MOAHA) to the field of microgrids, based on which a hybrid microgrid system model is established and processed to solve the optimal scheduling problem of a hybrid microgrid system. Notably, by comparing with the Multi-Objective Particle Swarm algorithm(MOPSO), the simulation verifies that the proposed optimisation scheme can significantly reduce the operating costs and pollutant emissions, while effectively meeting the crucial environmental and economic objectives of microgrids.
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