meQ: Selecting MEC Resources by Considering Service Communication Requirements

The Multi-Access Edge Computing (MEC) paradigm enables services that have strict network requirements like a maximum tolerable latency or a minimum bandwidth requirement. This consequently leads to a tight coupling of networks and computing, since the service can only function correctly if its communication requirements are met. Numerous existing strategies for MEC service deployment or resource selection put the characteristics of computing demands correlated with the free capacity of nodes or inter-service dependencies in their focus. In contrast, our work is a complementary attempt to enable especially the consideration of the strict communication needs of MEC services. It shows how edge features, i.e., knowledge of edge network conditions and service requirements, can be used to support resource selection and orchestration strategies. We consider and discuss how our model meQ can be applied in real communication systems as well as in heterogeneous networks, where clients may have multiple uplink connections. To enable communication-optimized selection strategies, meQ consists of two major components. A sharable, graph-based network representation and online searches to determine resources. The model benefits from existing work and limits the search space with the use of edge features. A performed simulation study demonstrates the benefits of meQ. The results show that it is possible to significantly reduce the search space, leading to lower search efforts also in large network graphs. An additional system-level simulation proves integration and applicability under realistic conditions.