l computer and it has its own operating system. All the nodes are connected using a high-speed memory fabric, called next-generation memory interconnect (NGMI). Such a memory fabric with high bandwidth and low latency could be used to speed up internal communications of NFV applications and expedite the packet passing between VNFs. It has a large pool of CPUs and memory and enables a flexible binding of memory to CPU. This can 3 Network Function Virtualization provide better load adaptation, where computing can be dynamically reconfigured to scale up or down based on the network traffic load and patterns seen in telco networks. 3.5 NF Modeling Given the widespread deployment of proprietary network functions (NFs), many network management functions (e.g., testing, policy com- pliance, and vendor interoperability) need accurate models of NFs to ensure correctness and reliability. However, due to their proprietary and complex nature, there is a lack of standardized behavior model of these NFs. In the following, we review existing NF models and survey several approaches to generate NF models. In the NFV architecture, each NF is often viewed as a black box that processes traffic arbitrarily. However, as more NFs are developed by diverse vendors and deployed in richer scenarios, the "box" view of NFs has already hindered its more advanced application and devel- opment. For example, if NFs are viewed as boxes without knowing its internal logic, there is no way to reason about their forwarding behaviors; thus, NFV operators cannot troubleshoot if they are misbehaving and cannot verify network-wide policy compliance such as reachability. Knowing NF's behavior can also help monitor the policy compliance by generating meaningful testing traces. Thus, having a forwarding model of individual NF that describes its internal forwarding logic is important for NFV network management tasks. Figure 3.5 shows the important role that NF models play in the whole NFV ecosystem. NF models connect NFV applications and NF imple- mentation.