Edge computing brings down storage, computation, and communication services from the cloud server to the network edge, resulting in low latency and high availability. The Internet of things (IoT) devices are resource-constrained, unable to process compute-intensive tasks. The convergence of edge computing and IoT with computation offloading offers a feasible solution in terms of performance. Besides these, computation offload saves energy, reduces computation time, and extends the battery life of resource constrain IoT devices. However, edge computing faces the scalability problem, when IoT devices in large numbers approach edge for computation offloading requests. This research article presents a three-tier energy-efficient framework to address the scalability issue in edge computing. We introduced an energy-efficient recursive clustering technique at the IoT layer that prioritizes the tasks based on weight. Each selected task with the highest weight value offloads to the edge server for execution. A lightweight client–server architecture affirms to reduce the computation offloading overhead. The proposed energy-efficient framework for IoT algorithm makes efficient computation offload decisions while considering energy and latency constraints. The energy-efficient framework minimizes the energy consumption of IoT devices, decreases computation time and computation overhead, and scales the edge server. Numerical results show that the proposed framework satisfies the quality of service requirements of both delay-sensitive and delay-tolerant applications by minimizing energy and increasing the lifetime of devices.

边缘计算将存储、计算和通信服务从云服务器带到网络边缘，从而实现低延迟和高可用性。物联网 (IoT) 设备资源受限，无法处理计算密集型任务。边缘计算和物联网与计算卸载的融合在性能方面提供了一个可行的解决方案。除此之外，计算卸载可以节省能源，减少计算时间，并延长资源受限物联网设备的电池寿命。然而，当大量物联网设备接近边缘计算卸载请求时，边缘计算面临可扩展性问题。这篇研究文章提出了一个三层节能框架来解决边缘计算中的可扩展性问题。我们在物联网层引入了一种节能递归聚类技术，它根据权重对任务进行优先级排序。每个具有最高权重值的选定任务卸载到边缘服务器以执行。轻量级的客户端 - 服务器架构肯定会减少计算卸载开销。为物联网算法提出的节能框架在考虑能量和延迟约束的同时做出了高效的计算卸载决策。节能框架最大限度地减少了物联网设备的能耗，减少了计算时间和计算开销，并扩展了边缘服务器。数值结果表明，所提出的框架通过最小化能量和增加设备的寿命来满足延迟敏感和延迟容忍应用程序的服务质量要求。