## 5 Performance Evaluation
### Simulation Results
More explicitly, higher value of BER raises the number of retransmissions  
Figure 3: Performance comparisons for varying traffic loads- **(a)** average end-to-end delay of all data packets, **(b)** on-time packet delivery ratio _i.e._, the achieved reliability, **(c)** average delay of CP traffic and **(d)** reliability of CP traffic. required for each packet (at each hop) prolonging the per-hop packet delay and thereby the end-to-end delay. A packet is dropped by an intermediate node if the number of retransmissions exceeds its limit, diminishing the packet delivery ratio. However, by comparing the graphs in Figures 3 and 4, we find that the effect of bit error rate is much higher on the end-to-end delay than that on the packet delivery ratio. The reason is that, at moderate traffic loads, the contention in the wireless medium does not grow up that much, and thus, even though the packet delivery delay increases due to packet retransmissions, it can prevent the effect of bit error rates keeping the packet delivery ratio at an acceptable level. From the results of Figure 4, we also observe that our DMQoS is more robust to the wireless link bit error rates compared to other approaches. This result is characterized by several facts: (i) DARA's aggregate routing metric (_i.e._, weighted-linear combination of three sub-metrics) fails to select the most appropriate next-hop node for the traffic classes, _i.e._, it uses the same metric for CP, DP or RP traffic flows, (ii) excessive duplicate packets toward fixed number of sinks generated by LOCALMOR  
Figure 4: Performance comparisons for varying bit error rates- **(a)** average end-to-end delay of all data packets, **(b)** on-time packet delivery ratio, **(c)** average delay of CP traffic and **(d)** reliability of CP traffic. and MMSPEED cause high media contention and packet drops, and (iii) MMSPEED suffers most since its exponentially generated duplicated packets (along with the original packets) converge together somewhere near the single sink causing many packet drops due to collisions and buffer overflows. However, our DMQoS optimizes the number of duplicate packets, selects the most appropriate next-hop node using separate metrics for different packet classes and disperses the source traffic toward sinks offering lightly-loaded paths. Impacts of Traffic Load and BER on Energy ConsumptionIn this experiment, we calculate the total amount of energy consumed for transmission and reception of a packet by source and forwarder nodes until it is received by a sink and average the values for all packets. Figures 5(a) and 5(b) show the average energy consumption per packet for varying source traffic loads and bit error rates in DMQoS and DARA, respectively. We observe that, in both approaches, the energy consumption rises up linearly for increasing source traffic loads and exponentially for increasing bit error rates. However, the rate of increase in DMQoS is slightly less than that in DARA. Our in-depth look into the simulation results reveals that this is mainly due to the reduced amount of packet collisions and retransmissions in DMQoS compared to those in DARA. As the source traffic load increases, the media contention increases as well and the data packets have to travel longer paths (for load-balancing) to reach their destinations and thus the per packet energy consumption is also increased. BER has more impacts on energy consumption since it forces packets to be retransmitted many times at each hop. Protocol Operation OverheadOne further issue to consider is the amount of energy overheads due to transmission and reception of routing control packets in different approaches for varying traffic loads and  
Figure 5: Average energy consumption per packet in **(a)** DMQoS and **(b)** DARA for varying traffic loads and bit error rates. bit error rates.