In the rapidly evolving landscape of the Internet of Things (IoT), edge computing has emerged as a critical paradigm to process data closer to the source—IoT devices. This proximity to data generation reduces latency, conserves bandwidth and enables real-time decision-making. However, managing distributed workloads across various edge nodes in a scalable and efficient manner is a complex challenge. In this article, we will delve into the concept of orchestration in IoT edge computing, exploring how coordination and management of distributed workloads can be enhanced through the integration of Artificial Intelligence (AI).

Understanding Edge Computing Orchestration

Edge computing orchestration is the art and science of managing the deployment, coordination, and scaling of workloads across a network of edge devices. It plays a pivotal role in ensuring that tasks are distributed effectively, resources are optimized, and the overall system operates efficiently. In IoT environments, orchestrating edge computing is particularly challenging due to the heterogeneity of devices, intermittent connectivity, and resource constraints.

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