articleSensorsMar 30, 2025GOLD OA

Federated Reinforcement Learning-Based Dynamic Resource Allocation and Task Scheduling in Edge for IoT Applications

SMSaroj MaliFZFeng ZengDADeepak AdhikariIUInam UllahMAMahmoud Ahmad Al‐Khasawneh

Central South University · University of Electronic Science and Technology of China · +4 more institutions

PubMed
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Abstract

Using Google cluster traces, the research presents a task offloading algorithm and a hybrid forecasting model that unites Bidirectional Long Short-Term Memory (BiLSTM) with Gated Recurrent Unit (GRU) layers along an attention mechanism. This model predicts resource usage for flexible task scheduling in Internet of Things (IoT) applications based on edge computing. The suggested algorithm improves task distribution to boost performance and reduce energy consumption. The system's design includes collecting data, fusing and preparing it for use, training models, and performing simulations with EdgeSimPy. Experimental outcomes show that the method we suggest is better than those used in best-fit, first-fit, and…

Citation impact

78
total citations
FWCI
93.10
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100%
References
42
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Authors

7

Topics & keywords

Topics
Keywords
  • Reinforcement learning
  • Computer science
  • Scheduling (production processes)
  • Distributed computing
  • Internet of Things
  • Task (project management)
  • Enhanced Data Rates for GSM Evolution
  • Human–computer interaction
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