## 5 Simulation Study
### Simulation Setup  
The network simulation parameters are presented in Table 3. The shadowing propagation model is adopted, and the dimension of space in the NAN network is set as 400 \(\times\) 400 m\({}^{2}\). A grid size of 25 smart meter nodes, separated 100 m apart, is simulated, sending their meter readings to a data concentrator. The User Datagram Protocol (UDP) constant bit rate (CBR) traffic was used to represent the application traffic types generated from each smart meter node in the network. The simulation setup illustrates the bi-directional flow of information between smart meters and the data concentrator using the WMN as the communication medium.  
Four application traffic models (EV charging data, meter reading, power quality and DR) are transmitted simultaneously between the smart meters and the data concentrator. A summary of the QoS requirements of the various AMI traffics types is presented in Table 4.  
Based on the traffic transmitted, the network is assessed for successful upload/download traffic in terms of latency and reliability. The packet size and data rate used for a particular traffic type is dependent on the SG application types. For example, EV charging information is treated as near real-time traffic, which strictly requires low latency (delay sensitive application traffic type). Therefore, a packet of size 40 bytes and data rate of 8 kbps (similar to Voice Over IP or VOIP traffic) is used to model the EV charging application traffic. In the case of DR, since peak price advertisement is a multicast traffic that does not elicit acknowledgement, it is simply modelled as UDP-based traffic, in which the data concentrator sends price signals to the UDP server installed on smart meter nodes. Meter reading traffic and power quality measurement data traffic are also modelled using UDP, and all of the nodes are connected to the data concentrator through the 802.11b WMN. The AHP multiple metrics implementation with OLSR is carried out only on the uplink (i.e., from smart meters to the data concentrator) and compared with other OLSR link metrics. This is because only a single traffic is transmitted in the downstream direction.  
The topology is varied by increasing the cluster size of smart meter nodes in the area and changing the position of the data concentrator, to measure and compare the performance at different  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**AMI Traffic Type** & **Network Requirement** & **Traffic Type** & **Latency** & **Criticality** \\ \hline EV & 9.6–56 kbps & Event/delay sensitive & 1–5 s & Medium \\ DR & 14–100 kbps & Event/delay sensitive & 0.1–2 s & High/medium \\ Meter Reading & 10–100 kbps & Periodic/delay tolerant & 2–15 s & Low \\ Power Quality & 9.6–100 kbps & Periodic/loss intolerant & \textless{}3 s & Medium \\ \hline \hline \end{tabular}
\end{table}
Table 4: Summary of the QoS requirements of AMI traffic types [5; 34; 35]. DR: demand response.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Simulator & ns-2.34 \\ Environment Size & 400 \(\times\) 400 m\({}^{2}\) \\ Simulation Time & 50 s (5 times a day) \\ Traffic Type & CBR \\ Transport Layer & UDP \\ CBRPacket sizes & 40, 60, 480 and 512 bytes \\ CBR Packet interval & 0.1, 1, 15 and 0.5 s \\ Routing Protocol & OLSR \\ Link Metric Type & ETX, ML, MD, \(OLSR_{MM}\) \\ Wireless Standard & 802.11b \\ Queue Size & 50 packets \\ Propagation Model & Shadowing dev = 54 dB, path loss = 2.7 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Network simulation parameters.  
instances. Performance indices such as packet loss, PDR, throughput and average delay are also used to evaluate performance.