FOG–CLOUD HISOBLASH MUHITIDA VAZIFALARNI O‘TKAZISH VA RESURSLARNI TAQSIMLASHNING ARCHERY PUFFERFISH OPTIMIZATION ALGORITMIGA ASOSLANGAN GIBRID MODELI
DOI:
https://doi.org/10.5281/zenodo.23007687Abstract
The rapid growth in the number of Internet of Things (IoT) devices has significantly increased the volume of data-intensive tasks. Centralized cloud computing, however, is characterized by high latency and substantial network traffic, which may not always fully meet the requirements of real-time applications. The aim of this study is to develop an integrated model for task offloading and resource allocation in a fog–cloud computing environment by combining predictive workload management with hybrid metaheuristic optimization.Keywords
fog–cloud computing, task offloading, resource allocation, workload prediction, gated recurrent unit, hybrid metaheuristic optimization, energy efficiency, makespan, Internet of ThingsReferences
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