# On Applicability of Network Coding Technique for 6 LoWPAN-based Sensor Networks
## 4 Performance of NC6 LoWPAN Mechanism
The results confirm that the decrease in the overall network load directly depends on the traffic volume that is generated by the nodes, and on NC buffers capacity. It means that network coding in WSNs gives better results for higher traffic volume in the network. Unfortunately, the memory that is allocated for NC buffer is limited due to the sensor nodes resource limitations, which in consequence limits coding opportunity. Furthermore, the allocation of the memory for NC buffers in the nodes with significant memory limitation can increase the packets loss ratio because of the lack of free space for routed packets in the intermediate nodes. The NC6 LoWPAN implementation in the WSNs may cause additional end-to-end packet delay, as shown in Figure 8.  
The number of buffered native packet does not significantly influence the packet end-to-end delay; however, it may decrease the packet loss ratio, as it is shown in Figure 9. This shows an impact of the nodes memory resources on the NC6 LoWPAN efficiency. The results presented in Figures 7-9 are derived from a relatively simple sensor network. A more complex WSN scenario that is composed of seven Tmote Sky motes, as shown in Figure 10, was examined to validate these results. Nodes from #3 up to #7 exchange IPv6 packets with the gateway (number of bidirectional packet streams varies from 1 to 7), with the same profile as in the simple scenario. Additionally, to demonstrate the influence of segmentation and reassembling processes that are given by the 6 LoWPAN standard on the network performance, nodes #3 and #1 exchange 1500B IPv6 packets every 1 s. As a consequence, the overall traffic volume in the air is increased, as it is shown in Figure 11.  
Figure 8: End-to-end packet delay (simple testing scenario). Figure 7: Overall traffic captured in the air (simple testing scenario)—number of buffered native packets = 0 means network without NC. Figure 11: Overall traffic captured in the air (extended testing scenario). Figure 10: Multihop WSN. Figure 9: Packet loss ratio (simple testing scenario). Both segmentation and reassembling actions require additional memory that is available in the nodes, which limits coding efficiency. The network coding operations reduce the overall traffic volume, but also they increase the packet loss ratio, as confirmed in Figure 6:0  
Many nodes are both source and relaying ones, so the lack of memory is a major reason of packets losses. This means that the proposed network coding technique can be used in sensor networks, but with moderate traffic level, and preferably in the nodes with relaying capabilities. We can decrease the packet loss ratio by limiting the number of packets that are stored in the NC buffer, but it also limits the NC efficiency through the overall traffic increase. Similar effect can be observed if the additional signalling will be provided to retransmit the lost packets. One of the method that can improve a packet loss ratio (keeping a traffic load decreased) can be the adaptive NC operations allowing for switch off the NC in the node or in a part of the WSN in the case of high traffic identified. To show the NC6 LoWPAN efficiency in terms of energy consumption, the overall energy that is consumed by the network were calculated. The energy consumed by the IEEE 802.15.4-based sensor modes that were used in the experiments were calculated according to the formula proposed in [40] for sent and received packets:  
Figure 6:1  
where, \(m_{send/receive}\)--the energy consumed by the sensor to send/receive 1B of the packet [J/B], \(b_{send/receive}\)--the energy consumed by the sensor to perform all of the operations to send/receive the data packet (transmission/ reception initialization, the IEEE 802.15.4 header transmission/reception, the IEEE 802.15.4 acknowledge reception/transmission) [J], _size_--the size of the data packets to be transmitted [B].