Minimizing End-to-End Latency in Edge Computing-Enabled IoT Networks Through Edge-to-Edge Resource Allocation
Mohit Saxena, Swapnil Srivastava, Vijay Kumar Dwivedi, Roshan Chitranshi, Pradeep Kumar Mishra · 2024
The emerging Internet of Things (IoT) applications in healthcare and smart homes need ultra-low latency in task processing. The IoT devices have limited computing power hence, they leverage the cloud servers to process their computational tasks. However, the far-located cloud server restricts the real-time response. Edge computing enables computing resources to be located near IoT devices. Hence, edge computing can minimize the dependency of IoT devices on cloud servers. However, the computing capacity of edge devices is less than that of cloud servers. Thus, edge computing-enabled IoT networks demand an efficient resource allocation strategy. This paper addresses the challenges in edge-to-edge resource distribution that minimizes the total latency in edge-enabled IoT networks. The proposed method enables the optimal resource provisioning of available edge devices. The numerical results indicate that the proposed method reduces the total latency significantly than the cloud-based solutions