Optimal resource scheduling of multi-functional edge computing devices in digital distribution networks

With the massive access to sensing, measuring, and user-side intelligent terminal devices, the functionalities and applications at the edge-side of digital distribution networks have become significantly enriched. However, the limited computation resources of edge computing devices must be utilized efficiently to achieve various functions, presenting challenges to resource scheduling within digital distribution networks. To tackle these challenges, this paper proposes an optimal resource scheduling method for multi-functional edge computing devices. The collaborative processing relationships of multi-functional applications for edge computing devices in digital distribution networks are analyzed to achieve various functions. These applications are further abstracted into computational task models with different characteristics. On this basis, constraints for resource scheduling are established, including the logical relationships between tasks, the multi-core configuration, and the resource limitation of devices. With the proposed scheduling method, computation resources of the edge computing device can be optimally allocated to different tasks, achieving multiple objectives such as reducing the process latency, avoiding task abandonment, and maximizing resource backup. The results of the case study indicate that using the proposed method, the overall task completion time is reduced by 20%, the task processing success rate increases to 95%, and the adequate resource reservation ratio improves to 40%.