gorithms can be tried, such as core pinning and adaptive core scheduling. Different deployment scenarios can also be a configurable option, for example, deploying on a single powerful VM or on mul- tiple VMs. Finally, to reveal the actual performance that one will experience in the real network, we need to test with different network traffic, not only using plain dummy traffic to test throughput but also application-aware traffic. 3.4.2 NFV Performance Improvements Telcos have transitioned most of their communications to standard IP networks and are now starting to migrate most of their computing to industry standard servers. In addition, with the advent of 5G technology, there is a push toward developing novel real-time services in the areas of augmented reality, autonomous driving, and IoT. In NFV environments, monolithic complex network functions running on specialized hardware are decomposed into smaller functional units and dynamically orchestrated onto a virtualized cloud and edge infrastructure. These network functions include both control plane processing (signaling, authentication, etc.) and data plane processing (routing, firewalling, etc.) and are encapsulated in a VM as a VNF. Service chaining defines routing instructions that direct network packets through a pipeline of VNFs. A core component of the NFV infrastructure is a highly agile network that enables efficient and dynamic service chaining. While the NFV transformation is under way, another trend is the move toward using large pools of compact, power-efficient compute nodes/SoCs that are integrated with large stores of fast persistent memory and custom high-speed interconnects. These computing architectures span from rack scale to datacenter scale and are expected to impose unprecedented scale, bandwidth, and latency requirements on future data center networks. This architecture is usually composed of a large number of nodes; each node is composed of a tightly coupled set of processor cores and some local memory. Each node acts like a traditiona