Chain Network Topology

The chain network topology is composed of 19 nodes. From left to right, the nodes are named BS, SS(1), SS(2), ..., and SS(18), respectively. On this chain network, each node runs a MAC-layer pseudo data scheduler to periodically establish data schedules with its neighboring nodes in a round-robin manner. The frequency is chosen to be one data schedule every 3 seconds. The duration of a minislot allocation is set to 32 frames.

As shown in Table 4.2(a), in the chain network, as the holdoff time value exponentially increases, the ATOUN value exponentially decreases and the ATHPT value exponentially increases. These results show that when the holdoff time value exponentially increases, the average transmission opportunity utilization significantly decreases and the average three-way handshake procedure time significantly increases. The reasons for these phenomena

Table 4.2: The performances of the evaluated schemes

(a) Chain Network Topology

MAC Application

ATOUN ATHPT (ms) NetUI TCP (KB/sec) UDP (KB/sec) Ping (ms)

Avg. Std.dev. Avg. Std.dev. Avg Std.dev. Avg. Std.dev. Avg. Std.dev. Avg Std.dev.

Dynamic 0.641 0.1140 14.295 12.2361 8.292 0.3353 381.812 160.7230 573.201 3.6810 390.030 224.1563 Static 0.494 0.0830 17.389 14.9974 18.140 3.553e-15 372.268 161.4577 569.606 4.4822 410.817 234.4550 HT-16 0.210 0.0330 24.184 5.4280 46.271 2.132e-14 235.043 171.8394 534.433 5.8250 825.176 466.1554 HT-32 0.110 0.0180 46.285 10.8420 66.365 1.421e-14 149.935 142.9734 472.869 8.5998 1430.85 810.8086 HT-64 0.057 0.0090 89.256 19.4830 86.929 1.499e-3 85.129 102.9986 401.746 13.1154 2609.386 1481.6938

(b) Grid Network Topology

MAC

ATOUN ATHPT (ms) NetUI

Avg. Std. dev. Avg. Std. dev. Avg. Std. dev.

Dynamic 0.725 0.0860 43.398 9.4300 9.661 0.1460 Static 0.559 0.0822 50.467 11.1090 59.303 0.0000 HT-16 0.530 0.0900 50.983 8.2110 70.313 0.0000 HT-32 0.405 0.0830 62.852 5.8381 116.974 0.0112 HT-64 0.245 0.0590 104.479 3.6402 199.009 0.0031

(c) Random Network Topology

MAC

ATOUN ATHPT (ms) NetUI

Avg. Std. dev. Avg. Std. dev. Avg. Std. dev.

Dynamic 0.718 0.1290 47.425 25.8386 14.896 0.5942 Static 0.543 0.1121 55.312 31.8472 66.718 1.9031 HT-16 0.481 0.1641 55.194 23.6402 95.336 6.0831 HT-32 0.363 0.1654 66.453 15.7061 150.262 8.2523 HT-64 0.237 0.1313 104.146 7.5184 226.507 10.0772

have been explained before. As for the static and dynamic approaches, one sees that they significantly outperform the three fixed-value holdoff time setting schemes on the ATOUN and ATHPT metrics. One also sees that the dynamic approach outperforms the static approach. This is because the former can dynamically adjust the holdoff time value to reduce the time interval between sending a request IE and sending a confirm IE. As such, the time required for completing a three-way handshake procedure (and thus for establishing a data schedule) can be greatly reduced. This also explains why the dynamic approach generates a higher utilization of transmission opportunity than the static approach.

For NetUI, when the holdoff time value decreases, the NetUI value decreases as well.

This result shows that using a smaller holdoff time value can achieve fairer and more efficient scheduling. One sees that the static and dynamic approaches achieve much smaller NetUI values than the fixed-value holdoff time setting schemes. The result is expected as in both approaches, the holdoff time of each node can be independently set to a different value to reflect the node density around it. In contrast, as discussed before,

a fixed-value holdoff time setting scheme cannot suit the scheduling needs of all nodes in a network. The dynamic approach outperforms the static approach on NetUI and the reason is explained below. To reduce the time required for the three-way handshake procedure, the dynamic approach uses an iterative algorithm to decrease a node’s holdoff time value. As such, the dynamic approach eliminates a part of contention time that the static approach cannot eliminate. This makes the dynamic approach perform more closely to the static optimal scheme than the static approach.

Regarding application performances, on this chain network, we conduct a different set of simulations using three different application-layer traffic: TCP, UDP, and ping. For a studied holdoff time setting scheme, its performances are evaluated on 16 simulation runs, each time using a different random number seed. In each run, a traffic flow (either TCP, UDP, or ping) is set up. The source node of the traffic flow is fixed at SS(2) node while the destination node of the traffic flow is chosen to be SS(i+2) in the ith run.

Fig. 4.8 shows the relationship between the TCP throughput and the hop count, Fig.

4.9 shows the relationship between the UDP throughput and the hop count, and Fig.

4.10 shows the relationship between the end-to-end round trip time measured by the ping program and the hop count, respectively. As shown in Fig. 4.8 and Fig. 4.9, the static and dynamic approaches achieve much higher throughputs than the fixed-value holdoff time setting schemes over all studied hop counts. The RTT results show that the static and dynamic approaches reduce the end-to-end round-trip packet delay significantly, when compared with the three fixed-value holdoff time setting schemes. The results also show that the dynamic approach generates a smaller round-trip packet delay than the static approach. This is expected as the dynamic approach can further reduce the time required for establishing a data schedule than the static approach.

Table 4.2(a) shows the TCP and UDP throughputs and round trip times averaged across all different hop counts for each scheme. According to the average TCP and UDP throughput results, the static and dynamic approaches on average achieve higher TCP and UDP throughputs than the fixed-value schemes. For example, the dynamic approach outperforms the “HT-16” scheme by a factor of 1.624 on TCP throughput and by a factor of 1.073 on UDP throughput, respectively. Regarding the round trip time, the dynamic approach on average reduces the round trip time of “ping” packets by a factor of 2.116 when compared to the “HT-16” scheme.

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Figure 4.8: TCP throughputs over different hop counts in chain networks

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Figure 4.9: UDP throughputs over different hop counts in chain networks

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Figure 4.10: The round trip time measured by the ping program in chain networks