## 4 Evolution of the Smart Grid Infrastructure: SDN-Enabled Smart Grid
### Candidate SDN Application for the Smart Grid
The SDN controller periodically monitors the network device, and constructs the network topology and route information between devices in the network. In addition, a SDN4 smart grid controller can maintain multiple routing paths between source and destination devices to provide DiffServ QoS routing between flows. If an AMI device, which has no route for incoming flow packets, requests the forwarding direction of the packet to the SDN controller, the SDN controller responds with the forwarding direction (next hop) to the requester. The experimental result of the end-to-end smart grid traffic delay shows that SDN4 smart grid routing outperforms open shortest path first (OSPF). * Load balancing: SDN load balancing applications are flow information-based stateless control service applications that allow systems to bypass the limitations of traditional stateful hardware appliances, such as load balancers and firewalls [35]. In particular, load-balancing features must be considered for use in resource-constrained substation automation domains, such as wireless smart grid AMI networks. For example, if the emergency power-quality alert message from the AMI device is transmitted to the HES, end-to-end transmission needs to be guaranteed, but traditional network systems cannot detect specific flow priorities, because application profile information is not shared between application network layers. Therefore, the network cannot suspend low-priority flow transmission, even if the network capacity is overloaded. While traditional per packet-based admission control algorithms can be utilized to process network control message exchange, they need to be extended for application-flow identification. [PERSON] et al. proposed flow-based admission control for SDN [36]. In this algorithm, the SDN application creates two virtual network interfaces to isolate high-priority and best-effort flow transmission. The data rate of the developed virtual interfaces can be dynamically configured using queue-size management, which enables us to control the volume of the flow traffic in each network. This algorithm can be effectively utilized to protect the minimum bandwidth requirements of the high-priority data flow as emergency power quality traffic when a large volume of the best-effort data traffic, such as firmware and diagnostics flows, coexists on the network. The experimental result shows that the SDN controller can provide per flow-based service differentiation using a smart grid service profile. * QoS management: The smart grid communication infrastructure must simultaneously support a wide range of QoS requirements for numerous smart grid and legacy applications. To satisfy the delay requirement of the smart grid traffic, the SDN controller uses both the context-awareness and load-balancing SDN applications. In the traditional network infrastructure, cross-layer-based QoS algorithms are widely utilized, but their use increases the network-system complexity [37]. However, in SDN, cross-layer information is easily shared using OpenFlow and OVS, which are operated without any direct information exchange between different network layers [29]. [PERSON], [PERSON] et al. proposed a heuristic flow scheduling-based QoS algorithm for smart grid devices [38]. In this algorithm, the authors assumed that SDN can detect the flow information and real-time flow status using an SDN flow monitoring application. The SDN controller assigns flow priority depending on a calculus-based queue model that considers the flow-traffic arrival rate, delay requirement of the flow and the available network bandwidth of the device. Each application flow of the AMI device can be assigned a different virtual interface depending on the smart grid service profile. The interface configuration can also be dynamically changed using the calculated flow priority of the SDN controller to optimize the network capacity and service QoS.