Fig 3.9: Comparison of throughput in NAN for SM data Fig 3.10: Comparison of throughput in NAN for EV control data Throughput is defined as average of data traffic in bits/sec, successfully delivered from the source node to the destination node through the network. This does not include the frames that were received previously but transportation was not successful because of errors like incomplete frame. From Fig. 3.9, we can conclude that the smart meter data that was put in the best effort class has a higher throughput than the data that was put in the background class. But as time passes the gap seems to decrease. From Figure 3.10, we can conclude that the electric vehicle data that was put in the voice class has a higher amount of throughput than the data that was put in the video class. Therefore, we can best effort class to transport SM data and voice class to transport the EV data. 3.4 Chapter Summary Smart grid data can be carried over using a number of wireless technologies as described previously: WSN, WAN, WiMax and LTE. In this chapter, we have thoroughly evaluated the performance of 2 potential candidates of NAN: WSN (zigbee) and WLAN (Wifi). Both the measurements demonstrate our design guideline will efficiently manage the data of smart meter and electric vehicle using zigbee or WLAN in NAN. Zigbee is cheaper, it also suffices our data rate, throughput and latency requirement but doesn’t have a well defined QoS. On the
Fig 3.9: Comparison of throughput in NAN for SM data Fig 3.10: Comparison of throughput in NAN for EV control data Throughput is defined as average of data traffic in bits/sec, successfully delivered from the source node to the destination node through the network. This does not include the frames that were received previously but transportation was not successful because of errors like incomplete frame. From Fig. 3.9, we can conclude that the smart meter data that was put in the best effort class has a higher throughput than the data that was put in the background class. But as time passes the gap seems to decrease. From Figure 3.10, we can conclude that the electric vehicle data that was put in the voice class has a higher amount of throughput than the data that was put in the video class. Therefore, we can best effort class to transport SM data and voice class to transport the EV data. 3.4 Chapter Summary Smart grid data can be carried over using a number of wireless technologies as described previously: WSN, WAN, WiMax and LTE. In this chapter, we have thoroughly evaluated the performance of 2 potential candidates of NAN: WSN (zigbee) and WLAN (Wifi). Both the measurements demonstrate our design guideline will efficiently manage the data of smart meter and electric vehicle using zigbee or WLAN in NAN. Zigbee is cheaper, it also suffices our data rate, throughput and latency requirement but doesn’t have a well defined QoS. On the
Msc%20Mohammad%20Shams%20Yazdi%202013.docx