Scenario II: Available bandwidth 12Mbits/sec

In the second scenario, the available bandwidth is set to 12 Mbits/sec. And two cases are simulated in this scenario. One is by assuming only rtPS connections become greedy after five seconds and the other one is by assuming all connections are able to become greedy after five seconds as long as they find out their previous allocation quality is good and try to send more data in purpose of better throughput.

When using Strict Priority Scheduling, the three types of services were originally allocated with their Maximum Sustained Rate, Fig.3-5, Fig.3-6, because the available bandwidth (12Mbits) is larger than the summation of all the connections’ Maximum Sustained Rates. And the remaining bandwidth becomes residual bandwidth.

(12 ), in the first five

seconds, the stable state of fairness degree has been remained, Fig. 3-7. But in the later five seconds, rtPS started grabbing bandwidth and made nrtPS and rtPS seriously damaged. Sooner or later, the nrtPS and BE will be starved. In Fig.3-7, the fairness degree downs to almost zero at the end, which means it is a very unfair state. No matter in which case, starvation of nrtPS and BE will happen. However, if using 2TSA, in the first five seconds, each service gained their Maximum Sustained Rate.

And in this scenario, the spare bandwidth (12-10.32=1.68Mbits) is not used and become residual bandwidth. When simulation time went over five seconds, in Case 1, see Fig.3-5, the rtPS connections attempted to gain the residual bandwidth and successfully be allocated. But the difference between Strict Priority Scheduling is that, when rtPS overcharges, nrtPS and BE will not be damaged. And in Case 2, see Fig.3-6, because all the connections are able to become greedy, the residual bandwidth will be fairly allocated to the connections which request more. The residual allocation of each connection is also different based on its QoS requirement.

0.3(UGS) 4.95(rtPS) 3.51(nrtPS) 1.56(BE) 10.32Mbits

> + + + =

And it is resulted from the design of QoS_Fac, connections with higher QoS requirement are assigned with a higher QoS_Fac and generated a lower PF. As a result, we can see the residual bandwidth allocation is rtPS>nrtPS>BE. Then in the evaluation of the fairness degree in Fig 3-6, when after five seconds, fairness will surely be affected by the rtPS in Case 1 either SPS or 2TSA. But the damage of fairness in 2TSA is obviously much less than that in SPS. If in Case 2, owing to all the connections will be able to become greedy after five seconds, the fairness degree of 2TSA outperforms the Case 1 in 2TSA. No matter which case we run. The fairness degree of SPS decreases seriously once rtPS connections starve nrtPS and BE ones.

And in Fig 3-8 is the long term(100 seconds) of observation. Even the fairness degree of 2TSA decreases in the first few seconds, it will converge at the end and again remain a stable state.

0

Figure 3-5: Average throughput in Scenario II-Case 1

0

Figure 3-6: Average throughput in Scenario II-Case 2

0

Figure 3-7: Fairness degree in Scenario II-10 seconds

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Figure 3-8: Fairness degree in Scenario II-100 seconds

The average delays of Scenario II are shown in Fig. 3-9 and Fig. 3-10. In case 1, only rtPS become greedy, and rtPS lengthens its average delay after five seconds

owing to some of the rtPS may also be affected by other greedy rtPS, no matter in SPS or 2TSA. The connections of nrtPS and BE in SPS remain the same after five seconds owing to all the bandwidth are deprived by rtPS and became starved. Thus, no more packets can be sent after five seconds in nrtPS or BE. On the other hand, though rtPS performs longer delay in 2TSA than in SPS, the nrtPS and BE performs shorter delay in 2TSA than those in SPS, which is also following our fairness prediction. In the second case of the scenario, all services performed longer delay in 2TSA after five seconds. This is because everyone is greedy and generated more.

However, the fairness mechanism manages no one can deprive others bandwidth. In consequence, some of the generated packets have to wait for longer time. In both scenario and the two cases in scenario II, average delay is rtPS< nrtPS < BE. This outcome shows 2TSA supports QoS requirement in delay issue. At the end, Table.3-5, 3-6, and 3-7 show the throughput of each connection.

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Figure 3-9: Average delay in Scenario II- case 1

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Figure 3-10: Average delay in Scenario II- case 2

Table 3-5: Throughput of rtPS in 2TSA Scenario II

Table 3-6: Throughput of ntPS in 2TSA Scenario II

Table 3-7: Throughput of BE in 2TSA Scenario II

Chapter 4.

Conclusion & Future Work

In this thesis, first a brief introduction of WiMAX was made. Then an overview of WiMAX was presented. WiMAX is defined as IEEE 802.16 and is also named as Broadband Wireless Network. And the scope discussed here is focused on Uplink Service Scheduling in TDD transmission mode. The three important parameters play important roles in service management. Then we brought out a new proposed structure illustrating the interaction between connections and BS with explaining why to make the services classified into three. The Unsatisfied category, the Satisfied category, and the Over-satisfied category. Then this thesis proposed a new uplink scheduling algorithm based on the computation from Minimum Reserved Rate and Maximum Sustained Rate. After that, the evaluation the fairness degree by a fairness index was designed. Through some different settings of simulation, results show that the proposed algorithm really outperforms the Strictly Priority Scheduling in the fairness issue. And in addition to efficiently prevent starvation, this proposed algorithm can also manage the greedy connections.

In the future work, we will investigate bandwidth allocation considering other QoS metrics, such as delay or delay jitter, for WiMax networks. Though we made no adaptation relating to the Max Latency, the delay issue may be another critical point.

When in the high QoS requirement services, such as real time video, the generated size is not constant. And maybe in some times, very urgent and large data need to be sent. So how to reduce the delay and at the same time guarantees the fairness is another goal needs to be achieved.

Reference

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[3] Hamed S. Alavi, Mona Mojdeh, Nasser Yazdani, “A Quality of Service Architecture for IEEE 802.16 Standards”, 2005 Asia-Pacific Conference on Communications, Perth, Western Australia, Page(s):249 – 253, 03-05 Oct. 2005

[4] Kitti Wongthavarawat, Aura Ganz, “IEEE 802.16 BASED LAST MILE BROADBAND WIRELESS MILITARY NETWORKS WITH QUALITY OF SERVICE SUPPORT”, Military Communications Conference, 2003. MILCOM 2003.

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