International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
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Volume 8 Issue 4
July-August 2026
Indexing Partners
Evaluating Dynamic and Energy-Efficient Task Offloading Mechanisms in Heterogeneous Fog Computing Systems
| Author(s) | Mr. Ashish Bagla, Dr. Deepak Dagar, Dr. Pratik Srivastava |
|---|---|
| Country | India |
| Abstract | The rapid growth of Internet-of-Things (IoT) devices has increased the need for computing support close to end users, particularly for applications that cannot tolerate long processing delays or excessive energy consumption. Fog computing has emerged as a practical extension of the cloud to address these requirements, yet real deployments often involve a mix of devices with different processing abilities, communication characteristics, and power constraints. These differences make it difficult to decide when and where tasks should be offloaded. This study introduces a task-offloading approach that adapts to changing conditions in a heterogeneous fog environment. The method continuously observes factors such as processor utilization, task size, communication delay, and the remaining energy of participating devices. Using this information, the system determines whether a task should run on the originating device, a nearby fog node, or the cloud. The approach aims to limit unnecessary transfers while striking a balance between energy use and execution delay. Simulation experiments conducted in iFogSim indicate that the proposed strategy consistently improves performance over conventional static or energy-unaware schemes. The results show notable reductions in overall energy usage and significant improvements in task-completion success under varying network loads. These findings suggest that integrating real-time monitoring with adaptive decision-making can strengthen the efficiency and responsiveness of fog-based IoT systems. |
| Keywords | task offloading, fog computing, energy efficiency, heterogeneous systems, dynamic mechanism, real-time monitoring, adaptive resource allocation. |
| Field | Computer |
| Published In | Volume 8, Issue 4, July-August 2026 |
| Published On | 2026-07-31 |
| DOI | https://doi.org/10.36948/ijfmr.2026.v08i04.84873 |
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E-ISSN 2582-2160
CrossRef DOI prefix of IJFMR is 10.36948/ijfmr
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