Devising a method for balancing the load on a territorially distributed foggy environment
Keywords:decentralized platform, cloud environment, Internet of Things, virtual cluster, iterative algorithm
This study solves the task to redistribute the load on a geographically distributed foggy environment in order to achieve a load balance of virtual clusters. The necessity and possibility of developing a universal and at the same time scientifically based approach to load balancing has been determined. Object of study: the process of redistribution of load in a foggy environment between virtual, geographically distributed clusters. A load balancing method makes it possible to reduce delays and decrease the time for completing tasks on foggy nodes, which brings task processing closer to real time. To solve the task, a mathematical model of the functioning of a separate cluster in a foggy environment has been built. As a result of modeling, the problem of finding the optimal distribution of tasks across the nodes of the virtual cluster was obtained. The limitations of the problem take into account the characteristics of the physical nodes of support for the virtual cluster. The process of distributing the additional load was also simulated through the graph representation of tasks entering virtual clusters. The task to devise a method for load transfer between virtual clusters within a foggy environment is solved using the proposed iterative algorithm for finding a suitable cluster and placing the load. The simulation results showed that the balance of the foggy environment when using the proposed method increases significantly provided the network load is small. The scope of application of the results includes geographically distributed foggy systems, in particular the foggy layer of the industrial Internet of Things. A necessary practical condition for using the proposed results is the non-exceeding the specified limit of the total load on the foggy medium, usually 70 %
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Copyright (c) 2023 Nina Kuchuk, Oleksandr Mozhaiev, Serhii Semenov, Andrii Haichenko, Heorhii Kuchuk, Serhii Tiulieniev, Mykhailo Mozhaiev, Viacheslav Davydov, Oksana Brusakova, Yurii Gnusov
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