Collaborative Cloud - Edge: A Declarative API orchestration model for the NextGen 5G Core

Abstract

As the edge computing era matures, it encompasses a broader range of applications that will be able to opportunistically use both the edge and the cloud mainly determined by the location constraints or the mission-critical reasons. Moreover, the convergence of verticals with the next generation mobile network will lead to an imminent edge-cloud collaboration that needs to be carefully addressed by Mobile Network Operators (MNOs). This paper proposes a novel approach to orchestrate the next-generation 5G core running as Cloud-Native Network Functions (CNFs) closer to the edge network while offloading the computation power required to ensure on-demand processing to a central cloud infrastructure. In this manner, full service isolation and network segmentation can be achieved independently from the geographical region with a high degree of scalability. Our main objective is to automate the CNFs provisioning in a declarative API-style in order to easily manage the deployment of applications and services across multiple clusters. Therefore, in our setup we considered crucial to assess the benefits of running the 5G Service-Based Architecture (SBA) in the cloud with multitenancy capabilities and evaluate the performance in terms of latency, while keeping the network control at the edge.

Deep-Deterministic Policy Gradient Based Multi-Resource Allocation in Edge-Cloud System: A Distributed Approach

“…Interference isolation is also achieved in directional beamforming, which, as a result, reduces the adjacent-cell interference. Therefore, in our case, we ignore path-loss, channel noise and interference factors, and manage resources at the application layer through well-defined APIs [11], which provides a fine-grained control of the wireless bandwidth.…”

“…As our proposed TFLAN-based model is not very complicated and it can easily fit in the memory of a single device. However, a massive amount of traffic is expected from enormous devices in an EC environment [11]. Additionally, a single device may not be sufficient to schedule a large number of concurrent user requests on the EC and BC servers.…”

“…Edge-cloud (EC) architecture is a stepping stone to meet the above compute and real-time constraints by reducing the network latency and providing the computational resources at the edge of the network [10]. Furthermore, A three-tier hierarchical EC system integrated with the back-end cloud (BC) provides support for a broadrange of applications with varying QoS requirements in greater extent [11].…”

“…Edge clouds (ECs) possess a limited amount of computational resources [11] and back-end clouds (BCs) experience the same in the case of pay-as-you go model. B5G supports dynamic Radio Access Network (RAN) and a wider frequency spectrum landscape [12].…”