Towards distributed emergency flow prioritization in software‐defined networks. Issue 1 (14th July 2020) - Moeyersons, Jerico; Farkiani, Behrooz; Wauters, Tim; Volckaert, Bruno; De Turck, Filip
Summary: Emergency services must be able to transfer data with high priority over different networks. With 5G, slicing concepts at mobile network connections are introduced, allowing operators to divide portions of their network for specific use cases. In addition, Software‐Defined Networking (SDN) principles allow to assign different Quality‐of‐Service (QoS) levels to different network slices. This paper proposes a microservices‐based framework, able to run both centralized and distributed, that guarantees the required bandwidth for the emergency flows and maximizes the best‐effort flows over the remaining bandwidth based on their priority. The proposed framework consists of an offline linear model, allowing to optimize the problem for a batch of flow requests. For dynamic situations, an online approach is also required in the framework to handle new incoming flows by calculating the path with a shortest path algorithm and utilizing a greedy approach in assigning bandwidth to the intermediate flows. In this article, the linear model is evaluated through simulation, the distributed architecture is evaluated through emulation while the online approach is validated through physical experiments with SDN switches. The results show that the linear model is able to guarantee the resource allocation for the emergency flows while optimizing the best‐effort flows with a sub‐second execution time. The distributed architecture is able to split up the managed network into different parts, allowing division of work between controllers. As a proof‐of‐concept, a prototype with Zodiac switches validates the feasibility of the centralized framework. Abstract : This research article proposes a microservices‐based framework, able to run both in a centralized and distributed manner, that guarantees bandwidth for emergency flows and maximizes best‐effort flows over any leftover bandwidth. It consists of an offline linear programming model, allowing to optimize the problem for a batch of flow requests. An online approach handles newly incoming flows by calculating the shortest path utilizing a heuristic approach in assigning bandwidth to these intermediate flows.