**3.5 Results obtained from traffic model changes**

Figure 12 shows the behaviour of seven protocols when the number of origin nodes varies between 10, 20 and 30. In this case, energy consumption in DSDV is fixed without regard to traffic load, and in four on-demand protocols, i. e., CBRP, DSR, DSDV and TORA, changes in energy consumption are made more slowly than traffic changes.

When the number of origins changes from 10 to 20, routing energy increases to 7. 31% in DSR, 88. 97% in AODV and 4. 71% in TORA. During traffic increase from 20 to 30, this routing increases to 41. 73%, 15. 88% and 13. 37% for DSR, AODV and TORA, respectively.

 § IMEP

260 Real-Time Systems, Architecture, Scheduling, and Application

These comparisons show that the efficiency of DSR is better than that of AODV and DSDV. Although DSR uses origin routing and AODV uses hop-to-hop routing, it is seen that DSR is more efficient than AODV. This result may come about from the caching mechanism. It can help to save energy, time, and bandwidth. FSR falls between DSR and AODV protocols. CBRP and CGSR have shown higher energy consumption than DSR. TORA has the highest energy consumption due to the assembly of route detection packets and packet maintenance

In this section, a movement model is presented in the basic scenario changes, and the simulation is implemented for stop times of 30, 120, 600 and 900 s. These implementations provide an interval between discrete simulation (no stop time) and static simulation (stop

Figure 10 shows energy consumption with seven protocols. DSR shows the best result and TORA shows the worst result. For on-demand protocols, i. e., TORA, AODV, DSR and CBRP, we see considerable changes in energy consumption in the change in movement model [Cano. J. C et al 2000]; however, the energy consumption of table-driven protocols is not related to the movement model and keeps its state, in contrast to on-demand protocols [Sargolzaey. H et al 2009]. In this simulation, TORA shows the worst result due to its assembly of IMEP§ and TORA packets [Prakash. Sh et al 2011]. According to this scenario, it is observed that DSR and AODV have shown relatively similar behaviour in static networks, but when the movement of nodes is stable (low stop time), their behaviour will be different. In this movement model, DSR (using a caching mechanism as well as irregular nodes technique) and AODV (due to having low parasite during sending route detection packets)

Figure 11 shows results obtained by varying the maximum speed of nodes between 0, 1, 15 and 25 m/s. These values have been considered, respectively, as simulating a fixed network, a network for pedestrians, a network for cyclists, a network for drivers and a network for train travellers. The obtained results show fixed behaviour of DSDV even in movement with high speed but energy consumption has increased for four on-demand protocols with regard to increase in maximum speed of movement. Generally, when speed is added, DSDV

Figure 12 shows the behaviour of seven protocols when the number of origin nodes varies between 10, 20 and 30. In this case, energy consumption in DSDV is fixed without regard to traffic load, and in four on-demand protocols, i. e., CBRP, DSR, DSDV and TORA, changes

When the number of origins changes from 10 to 20, routing energy increases to 7. 31% in DSR, 88. 97% in AODV and 4. 71% in TORA. During traffic increase from 20 to 30, this routing increases to 41. 73%, 15. 88% and 13. 37% for DSR, AODV and TORA, respectively.

[Tuteja. A et al 2010].

time of 900).

 § IMEP

**3.4 Results obtained from movement model changes** 

could have shown the best result [Gupta. A. K et al 2010].

is better than AODV [Liu. Y et al 2004].

**3.5 Results obtained from traffic model changes** 

in energy consumption are made more slowly than traffic changes.

The main reason for this behaviour is that in on-demand routing protocols, nodes use the previous packets for receiving new route information and when traffic increases, so too does the activity of nodes [Sargolzaey. H et al 2009].

Fig. 10. Energy consumption as a function of stop time for seven protocols

Fig. 11. Energy consumption as a function of maximum speed for seven protocols
