ork functions (VNFs), as well as the control plane managing the VNFs. Nevertheless, beyond the additional data collected in the Network Cloud, it is important to keep in mind the "data stack" needed to characterize the full end-to-end experience. This is shown in Table 8.1. Device data are important as they provide the best view of the overall experience from the cus- tomer standpoint. For instance, it is the only data that covers the performance for when the device is on the network, off the network, or which network; it also captures device-specific attributes such as "resets," "battery," "memory," "software configuration," etc. issues. Collecting some of this data requires software on the device interfacing with either public or private APIs such as the Android APIs [Andr16], or the iOS developer library [iOS16]. The Missing Instrumentation Layer Virtualized Network State SDN Controller Performance Assurance Control Plane Director Performance Assurance Controller VNF Controller Instrumentation Layer Smart Modules Data Plane Center Standards-Based PM Reflectors Real-Time, Ubiquitous, Open Visibility Brings Data Plane performance Instrumentation Utilization I Available Capacity I Packet Loss to the Control Plane Latency I Delay Variation I QoS/E KPIs FIGURE 8.1 The instrumentation layer of big data and advanced analytics in SDN/NFV. (From Light Reading's Big Telecom Event, The Role of Big Data and Advanced Analytics in SDN/NFV, https://accedian. com/wp-content/uploads/2015/06/BTE15_The-Role-of-Big-Data-and-Advanced-Analytics-in-SDN-NFV pdf.) Network Data and Optimization TABLE 8.1 Unique Data Contributions per Data Stack Layer with Traditional Network Data Collection and Network Cloud Data Collection Examples Additional "Network Data Collection Unique Data Contribution to Traditional Data Cloud" Data Layers End-to-End View Collection Examples Collection Examples Application data Application perspective: Website logs Access stats across all networks (wireless, wireline, multiple operators, etc.) Internet cloud da