plane, control plane, signal processing, storage). Identification of traffic models and performance metrics for each workload. Benchmark identified performance metrics for each VNF workload and its defined traffic model in a controlled lab environment. VNF efficiency can be computed as a function of the efficiency of the VMs that implement it. An average/max/min over the formulated efficiency of the VM would define the VNF efficiency. 16.12 VNF MEASUREMENTS FOR OPTIMAL PLACEMENT AND SIZING Virtualized networking functions are usually implemented as a single VM or as a disaggregated group of reusable components, each of which is implemented as a VM. In a cloud-computing model, resources are abstracted at the VM level-the abstraction ensures limited control by the VNF regarding which specific host the VM would be located in or what kind of coresident VMs would be along with this VNF. AT&T's VNF guidelines [22] specify that each VNF must contain at least the following informa- tion to support instantiation of the VF in the virtualized environment: VF package layout (captures basic network and application connectivity between VF com- ponents, clustering/high availability design, scaling capabilities of each component, etc.) vCPUs, memory/RAM, disk Bandwidth profile VF software images Multitenant/single tenant Placement policy and constraints (including affinity, anti-affinity, latency considerations), redundancy, external/persistent storage, virtual network interface cards (vNICs), and networking Vendor affinity or anti-affinity rules must be consistent with AT&T's desire for no single point of failure The process of selecting which virtual machines should be located and executed on which physi- cal machine or cluster in a cloud environment or zone, is referred to as virtual machine optimal placement [24]. The need for optimal VM placement to maximize resource utilization calls for plac- ing VMs over a minimal set of physical hosts within specified constraints with minimal overhead. The problem is generally divided i