QoS-Aware Score-Based Edge Resource Allocation Model

Abstract

In edge computing, there are two fundamental targets that are in conflict with each other: ensuring a minimum level of Quality of Service (QoS) for an edge application, and at the same time, maximising the utilisation of the edge infrastructure for all applications requesting edge services. In this paper, an edge resource allocation model is proposed. The proposed model provides a solution for both targets and their inherent contradiction. To estimate the edge application QoS, End-to-End Latency (E2EL) as measured by the application is used. Throughout the paper, it is shown that this is a viable approach for many different real-world scenarios, as well as for a broad set of edge application categories. Furthermore, E2EL measurement is a simple concept for application developers to understand and implement. To maximise edge utilisation, a score-based approach is suggested. The approach dynamically determines the best edge node and network path combination for a given edge application. The two solutions are interconnected such that the model maximises the overall edge utilisation while maintaining an acceptable QoS level for each edge application. The proposed edge resource allocation model is implemented and tested on an emulated edge infrastructure with challenging edge scenarios. The experiments show that the model delivers good and robust results for both fundamental edge targets even in real-world edge environments with many uncertainties.