Chapter 3 Timely Backup Source Routing (TBSR) Protocol
3.3 Summary
The key improvement of TBSR is the reduction of the frequency of rediscovering backup route. TBSR has a flexible route maintenance mechanism to provide robust link connection under the mobile scenarios. We broadcast T-RREQ when source node detects the load of primary path is growing up in the Timely Backup Bound.
Therefore TBSR extends DSR by selecting a timely backup route to achieve more reliable load balance between each communicating mobile pair of nodes.
Chapter 4
Simulation Results and Discussion
To evaluate the performance of TBSR, we used a comprehensive simulation model based on ns-2 [55] to compare with Dynamic Source Routing (DSR) [2], which is a well-known and rival on-demand routing protocol. Another protocol compared is BSR, which copies TBSR but eliminates the timely characteristic. The source node broadcasts one RREQ to get both primary route and backup route in BSR. ns-2 includes CMU’s Monarch Group’s mobility extension for simulating the scenario of multi-hop wireless ad-hoc networks. For the DSR simulation, we used the latest available version from the VINT project with a full implementation of the update and enhanced technique.
We modeled our network interface with a transmission rate of 1 Mbps. The interface uses the IEEE 802.11 Distributed Coordination Function (DCF) as the medium access control (MAC) protocol. The 802.11 DCF uses Request-To-Send (RTS) and Clear-To-Send (CTS) control packets for “unicasting” data transmission to a neighbor node. The transmission of data packet is followed by an ACK. “Broadcast”
data packets and the RTS control packets are sent using physical carrier sensing. An unslotted carrier sense multiple access (CSMA) technique with collision avoidance (CSMA/CA) is used to transmit these packets. A detailed description for the models and the simulation environment is available in [55]. In the simulation of TBSR and DSR, the RREP and data packets are handled as unicast packets with a MAC destination. The RREQ and RERR packets are broadcast packets in the MAC. MAC layer can help TBSR and DSR with detecting link failures. Once link failure happens,
MAC layer would send a signal to notify the routing layer. The parameter values of TBSR and DSR are summarized in Table 4-1.
Table. 4-1. Parameters in the simulation of routing protocols.
Parameter TBSR DSR
Cache Size 94 94
Interface Queue Size 50 50
Reply to Requests From the Cache Off On
Backup Route Reply Wait Time 0.3 sec N/A
Bandwidth 1 Mbps
4.1 Traffic and Mobility Models
The mobile ad-hoc network experiments were performed with 50 mobile nodes moving in two physical areas of different size. One is 1,500 meters × 300 meters, the other is 1,000 meters × 1,000 meters. The rectangular scenario is to increase the average number of hops. The Constant Bit Rate (CBR) traffic is simulated in our scenario with 2 kinds of packet size, 512 and 1024 bytes. The source-destination pairs are selected randomly over the network, each with a sending rate of 5 packets / sec.
Each simulation shows the result of 32 data sessions. Each runs 500 seconds. The mobility pattern in our simulation is the random waypoint model [56]. In that model, each node begins at a random position, and it chooses a new position in the rectangular space. Then it starts a trip to the new position at a randomly selected speed (uniformly distributed between 0 ～ Max m/sec, Max = 20). After reaching its new position, a node will suspend for a period of time, called the “pause time”. The general mobility status depends on the pause time values (0/50/100/150/200/250
/300/350/400/450/500 s). The smaller pause time value stands for the more mobile status. Ten runs of different traffic and mobility scenarios are averaged to generate each statistical data. The details of simulated model are summarized in Table 4-2.
Table. 4-2. Parameters in the simulated model with respect to pause time.
Area (m2) 1500 x 300 1000 x 1000
Simulation time (s) 500
Mobile nodes 50
Sessions 32
Packet type CBR (Constant Bit Rate)
Packet sending rate (packets/s) 5
Packet size (bytes) 1024 / 512
Node max. speed (m/s) 20 (uniform distribution)
Pause time (s) 0, 50, 100, 150, 200, 250,
300, 350, 400, 450, 500
We also designed another kind of model to simulate in a physical area of 1,500 meters × 300 meters (see Table. 4-3). Nodes move at different maximum speeds (10/15/20/25/30 m/s, uniform distribution) with the zero value of the pause time. Only 1024 bytes data packet is tested.
Table. 4-3. Parameters in the simulated model with respect to node max. speed.
Area (m2) 1500 x 300
Simulation time (s) 500
Mobile nodes 50
Sessions 32
Packet type CBR (Constant Bit Rate)
Packet sending rate (packets/s) 5
Packet size (bytes) 1024
Node max. speed (m/s) 10, 15, 20, 25, 30 (uniform distribution)
Pause time (s) 0
4.2 Results
We used three key performance metrics to evaluate TBSR and DSR as follows：
1) Packet delivery ratio：the percentage of data packets delivered to their destination nodes of those originated by the sources.
2) Average end-to-end delay of the data packets：the interval from the time a packet is sent from the source until the time it is received at the destination.
3) Control message overhead ratio：the ratio of routing control packets transmitted to data packets delivered.
4.2.1 Packet Delivery Ratio
Fig 4-1 and Fig 4-2 compare the performance of packet delivery ratio under various simulated mobility scenarios. TBSR outperforms DSR and BSR, and TBSR generally has significant improvement in each mobility rate. These results are due to fact that TBSR attempted to utilize the timely backup route when two conditions happen：1.
distributing the traffic when the primary route is going to be congested. 2. packet recovery in the presence of the primary link failure. In the former case, TBSR can enhance the utilization of bandwidth and reduce the congested regions. Although the backup route may costs more delay slightly, it has the largest available bandwidth to share the load. To fit the requirement of on-demand time constraint, we have used the stringent reply waiting time-window (0.3 s). In the latter case, TBSR can salvage more packets and reduce more control overhead because the intermediate nodes only send RERR back to the source when both the primary route and the backup route break. In the higher mobility, the improvement is more prominent because TBSR discovers a backup route in a timely manner and can utilize the usable backup route to salvage packets and to continue the data session (see Fig. 4-3). The difference in the delivery ratio between the two packet sizes is the magnitude of enhancement (see Fig.
4-1 (a), (b) and Fig. 4-2 (a), (b)). Since we set the same packet sending rate for both scenarios, there is a bigger chance to utilize the backup route for load-balance where the packet size is larger. The shape of area can also affect the performance. The increasing trend of curve in the square area is smoother than the one in the rectangular area.
4
Fig. 4-1. Packet delivery ratio with respect to pause time (a)1024 bytes CBR packet and (b) 512 bytes CBR packet scenarios in a 1,500 m × 300 m area.
0
Fig. 4-2. Packet delivery ratio with respect to pause time (a)1024 bytes CBR packet and (b) 512 bytes CBR packet scenarios in a 1,000 m × 1,000 m area.
4 6 8 10 12 14 16
10 15 20 25 30
Max. Moving Speed (m/s)
Packet Delivery Ratio (%)
TBSR DSR BSR
Fig. 4-3. Packet delivery ratio with respect to maximum moving speed.
4.2.2 Average End-to-end Delay
Fig. 4-4 and Fig 4-5 shows how the average end-to-end delay varies as the pause time changes. TBSR also surpasses DSR and BSR, and the improvement is especially outstanding when the mobile nodes are moving faster (see Fig. 4-6). As the mobility increases, TBSR will have a more reliable data session and less end-to-end delay because it can use the backup route to keep on packet transmission and reduce the probability of yielding a much longer delay in route re-discoveries.
In the lower mobility, TBSR may have slightly longer delay than DSR because the delays are measured for those packets that safely reach the destination, and the backup route that takes charge of load-balance may have taken longer delay within a limited bound. It is a tolerable tradeoff and worthy.
1.5
Fig. 4-4. Average end-to-end delay with respect to pause time (a)1024 bytes CBR packet and (b) 512 bytes CBR packet scenarios in a 1,500 m × 300 m area.
0
Fig. 4-5. Average end-to-end delay with respect to pause time (a)1024 bytes CBR packet and (b) 512 bytes CBR packet scenarios in a 1,000 m × 1,000 m area.
1.5 2 2.5 3 3.5 4 4.5
10 15 20 25 30
Max. Moving Speed (m/s)
Avg. End-to-end Delay (sec) TBSR DSR BSR
Fig. 4-6. Average end-to-end delay with respect to maximum moving speed.
4.2.3. Control Message Overhead Ratio
As expected, TBSR also outperformed DSR and BSR in the control message overhead ratio (see Fig. 4-7 and Fig. 4-8). We can see that the higher level of mobility, the higher the difference in reduced overhead ratio between TBSR and DSR. The reason is that more route re-discovery is invoked by DSR through its salvaging procedure because DSR has no backup route to use. In the more stable condition, TBSR would broadcast slightly more routing control messages to construct the backup route for preventing the occurrence of congested areas.
2
Fig. 4-7. Control message overhead ratio with respect to pause time (a)1024 bytes CBR packet and (b) 512 bytes CBR packet scenarios in a 1,500 m × 300 m area.
0
Fig. 4-8. Control message overhead ratio with respect to pause time (a)1024 bytes CBR packet and (b) 512 bytes CBR packet scenarios in a 1,000 m × 1,000 m area.
0 2 4 6 8 10 12 14 16 18
10 15 20 25 30
Max. Moving Speed (m/s)
Control Message Overhead Ratio (%)
TBSR DSR BSR
Fig. 4-9. Control message overhead ratio with respect to maximum moving speed.
4.3 Discussion
The performance results in this simulation have shown that TBSR provides a significant improvement for each key metric (see Table. 4-2 and Table. 4-3). In all cases of mobile scenarios, TBSR outperforms BSR and DSR. This achieves our goal and confirms that the intuition of utilizing backup route is advantageous for applications transmitting CBR data flow in the mobile wireless ad-hoc networks. The system consumes less battery power in the network device hardware because TBSR reduces the amount of control message overhead.
Table. 4-4. Simulation results of 1024 bytes CBR packet scenario.
Area Size (m2) 1500×300 1000×1000
Metric Protocol TBSR BSR DSR TBSR BSR DSR Packet Delivery Ratio (%) 12.64 12.5 11.09 7.74 6.38 5.12 Avg. End-to-end delay (s) 3.09 3.19 3.43 3.06 3.22 3.2 Control message
overhead Ratio (%)
5.72 5.76 8.65 7.8 8.39 13.61
Table. 4-5. Simulation results of 512 bytes CBR packet scenario.
Area Size (m2) 1500×300 1000×1000
Metric Protocol TBSR BSR DSR TBSR BSR DSR Packet Delivery Ratio (%) 19.29 18.43 18.46 9.21 8.3 8.63 Avg. End-to-end delay (s) 2.46 2.49 2.51 2.93 3.3 3.08 Control message
overhead Ratio (%)
8.54 8 13.46 11.15 11.64 21.44
Chapter 5
Conclusion and Future Work 5.1 Conclusion
Timely Backup Source Routing (TBSR) is a novel on-demand routing protocol which explores the least-load backup route in a timely manner in the wireless ad-hoc network. Through simulation, it is proved that TBSR considerably gains better performance in packet delivery ratio, average delay and control overhead compared with BSR and DSR. Our analysis indicates that TBSR has backup routes to provide robustness to mobility, and it is really effective in case of a link failure in the primary route because of reducing the frequency of route re-discovery. On the other hand, TBSR balances the traffic load among the network nodes and avoids the creation of congested areas by selecting backup routes based on load metric. In order to implement this idea practically, we propose an estimation algorithm to measure the rout load metric approximately and to select the least-load route by a heuristic function. Measuring the traffic in bytes makes the measurement of route load more accurately. We validate this algorithm via simulation under diverse mobile scenarios.
5.1 Future Work
Further improvements could be focused on the framework construction of mobile multimedia communication system in the wireless ad-hoc networks. We could integrate the video codec into this mobile system and implement multi-stream coding with multi-route transport. Using multiple description coding to generate multiple equivalently important sub-streams from one video stream, a high-quality reconstruction is decoded from all sub-streams together. More sophisticated Timely
Backup Route Search (TBRS) algorithm can be deployed to improve the performance.
We can combine multiple types of packets in the simulation of the mobile scenario to see how the performance changes. These are interesting and open research issues that are worth further investigating in the future.
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