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<p> The rapid proliferation of Internet of Things (IoT) devices, coupled with the growing demand for computing resources, poses significant challenges for energy-efficient resource allocation. Due to the limited computational capabilities of IoT devices, offloading tasks to nearby fog nodes is a promising solution, particularly for time-sensitive applications. This paper proposes a novel energy- and deadline-aware, double auction-based incentive mechanism, namely Priority-Based Enhanced Energy Savings (PBEES), to address the IoT task offloading problem and resource allocation in a fog computing environment. PBEES incorporates a priority-based reward system for fog nodes and users. Additionally, PBEES includes an energy management system for fog nodes. The theoretical analysis demonstrates that PBEES is a computationally efficient incentive mechanism that satisfies key economic properties including truthfulness, individual rationality, and strong budget balance. Extensive simulation experiments validate the superior performance of PBEES in reducing energy consumption and enhancing user satisfaction with offloading services.</p>

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Priority-based and energy-aware incentive mechanism for IoT task offloading in a fog environment

  • 期刊论文

  • 发表日期：

    2026年6月3日

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  • Branka Mikavica,
  • Aleksandra Kostic-Ljubisavljevic

摘要

The rapid proliferation of Internet of Things (IoT) devices, coupled with the growing demand for computing resources, poses significant challenges for energy-efficient resource allocation. Due to the limited computational capabilities of IoT devices, offloading tasks to nearby fog nodes is a promising solution, particularly for time-sensitive applications. This paper proposes a novel energy- and deadline-aware, double auction-based incentive mechanism, namely Priority-Based Enhanced Energy Savings (PBEES), to address the IoT task offloading problem and resource allocation in a fog computing environment. PBEES incorporates a priority-based reward system for fog nodes and users. Additionally, PBEES includes an energy management system for fog nodes. The theoretical analysis demonstrates that PBEES is a computationally efficient incentive mechanism that satisfies key economic properties including truthfulness, individual rationality, and strong budget balance. Extensive simulation experiments validate the superior performance of PBEES in reducing energy consumption and enhancing user satisfaction with offloading services.