NFV Orchestration over Disaggregated Metro Optical Networks with End-to-End Multi-Layer Slicing enabling Crowdsourced Live Video Streaming

Network infrastructure must support emerging applications, fulfill 5G requirements, and respond to the sudden increase of societal need for remote communications. Remarkably, crowdsourced live video streaming (CLVS) challenges operators' infrastructure with tides of users attending major sport or public events that demand high bandwidth and low latency jointly with computing capabilities at the networks' edge. The Metro-Haul project entered the scene proposing a cost-effective, agile, and disaggregated infrastructure for the metro segment encompassing optical and packet resources jointly with computing capabilities. Recently, a major Metro-Haul outcome took the form of a field trial of network function virtualization (NFV) orchestration over the multi-layer packet and disaggregated optical network testbed that demonstrated a CLVS use case. We showcased the average service creation time below 5 min, which met the key performance indicator as defined by the 5G infrastructure public private partnership. In this paper, we expand our field trial demonstration with a detailed view of the Metro-Haul testbed for the CLVS use case, the employed components, and their performance. The throughput of the service is increased from approximately 9.6 Gbps up to 35 Gbps per virtual local area network with high-performance VNFs based on single-root input/output virtualization technology

Functional Metrics to Evaluate Network Vulnerability to Disasters

Disasters can cause, intentionally or unintentionally, the failure of several network components at the same time. A vast body of literature focuses on understanding the impact of disasters on the network infrastructure to enable the design of more robust networks. However, these multiple failures also affect the applications running over the network infrastructure. Even when the impact of a disaster on the structural performance indicators is insignificant, the functional implications can be substantial. More importantly, a small degradation in network performance can result in severe disruptions of overlay applications, or even completely prevent their proper functioning. Therefore, it is essential to analyze the impact of a disaster on the functional aspects of the network, i.e. the Quality of Service (QoS) offered to the applications and the Quality of Experience (QoE) perceived by the users. In this chapter, we review the functional metrics for evaluating the impact of disasters on applications and users. We specify relevant packet- and network-based functional metrics as well as perceived subjective metrics, and demonstrate the impact of disasters on QoS and QoE metrics in a case study