Simulation Results

Performance of wake-up time schedules without applying updating

We first investigate both the performance of energy saving and system throughput for the wake-up time schedules without applying the distributed updating algorithm. The successful transmission probability is set to 0.9. For convenience, schedule without pre-delay and sched-ule with pre-delay are denoted by Schedsched-ule 1 and Schedsched-ule 2, respectively. The performance of energy saving is measured by both the overhearing time and the reduced proportion of overhearing time when compared with that of Schedule 1.

As shown in Figures 6.3 (a) and (b), one can see that simply applying Schedule 1 to the TSMP scheme will make STAs suffer from overhearing under the given erroneous condition.

On the other hand, the STAs of later orders can benefit from the schedules with pre-delay considerations to eliminate larger proportions of unnecessary overhearing.

Note that STA 2 has the largest percentage of improvement when α = 1. For our studied simulation scenario, we have Wi,1 = (i − 1)µ + α√

i − 1σ for STA i ( i > 1 ). Consequently, Wi,1− Wi−1,1 = µ + α(√

i − 1 −√

i − 2)σ decreases as i increases and larger value of raises the decreasing rate. Hence, when α = 1, what is special for STA 2 is that the preceding STA 1 is not delayed by the schedule while W_2,1− W_1,1 = µ + σ is larger than that of succeeding STAs. It therefore benefits from the setting of schedule to have better improvement. For such a conservative schedule for STA 2, STA 3 wakes up relatively earlier when compared with the situation of STA 2 and thus has larger overhearing time and less improvement

0 2 4 6 8 10 12 14 16 18 20

Figure 6.3: The improvement on energy saving for both schedules without the updating algorithm.

percentage than STA 2 does. Nevertheless, since C_i(W_i,1) = (i − 1)(1 − p)µ + α√ i − 1σ increases with i, more eliminated overhearing time for STAs with increasing order can still be expected. Therefore, the percentage of improvement for STA i increases as i increases.

The performance of system throughput is shown in Figures 6.4 (a) and (b). The through-put is defined as the required time for data transmission over total transmission finish time for the first i STAs. The degradation in throughput of Schedule 2 is measured by the dif-ference of throughput compared with that of Schedule 1. Note that the system throughput of Schedule 1 is the same as that of the original TSMP scheme. It can also be explained by W_i,1− W_i−1,1 = µ + α(√

i − 1 −√

i − 2)σ that the degradation mitigates with increasing order since STAs wake up and finish their transmission earlier. As can be seen from Figures 6.3 and 6.4, for a system tolerating 3% degradation of system throughput for 20 STAs, it

should choose α = 1 to save more energy of STAs.

Figure 6.4: System throughput performance of our proposed schedules.

Performance of wake-up time schedules applying updating

The performances of energy saving when applying the distributed wake-up time updating algorithm are shown in Figures 6.5 (a) and (b). With the updating algorithm, the improve-ment in energy saving is significant for Schedule 1. However, there is only slight improveimprove-ment for Schedule 2. This is because Schedule 2 has eliminated large proportion of overhearing by pre-delaying the initial access attempts. Since the proposed updating algorithm does not alter the actual access start time for both Schedule 1 and Schedule 2, the system throughputs are the same as those shown in Figure 6.4 and thus are not shown here again.

0 2 4 6 8 10 12 14 16 18 20

Figure 6.5: The improvement on energy saving for both schedules with the updating algo-rithm.

6.4 Summary

In this chapter, we proposed wake-up time schedules and an update algorithm for the TDMA-like TSMP scheme to improve its performance on energy saving when the immediate re-transmission is adopted for error recovery. According to the simulation results, the proposed schemes can effectively alleviate the problem of overhearing under the erroneous wireless environment to prolong the usage time of wireless devices. The impact of incorporating the wake-up time schedule into the TSMP scheme on system throughput is also studied. For our proposed schedule with pre-delay, the wake-up time schedule can be adjusted by selecting a suitable parameter value to achieve better energy saving and meet a predetermined loss of system throughput. Since the proposed wake-up time schedules and the updating algorithm are simple, we believe they are feasible to be implemented in real systems.

Chapter 7 Conclusions

In this dissertation, we study the important energy saving issues regarding the shared medium, infrastructure wireless LAN. Under the multi-user scenario, the overhearing problem is highlighted and thoroughly studied for different medium access mechanisms.

We propose an algorithm to schedule the service start time of TSs belonging to different applications for the IEEE 802.11e S-APSD mechanism. Simulation results show that the proposed scheduling algorithm can achieve similar performance as [38] in preventing the overlapping of SPs while the implementation complexity is largely reduced by utilizing the proven periodicity of service schedules and the limited number of traffic classes. Since the scheduling optimality of Chapter 3 and [38] depend on the joining order of TSs, they could be unsatisfactory in some cases. To improve the energy saving performance, we also studied the problem of rearranging existing scheduled events to enlarge the minimum distance of the system. We show that the maximum of minimum distance between two periodic scheduled events is closely related to the greatest common divisor of their periods. Taking advantage of this observation and scheduling TSs according to the ascending order of period, we devise the GMD greedy scheduling to increase the tractability while improving the energy saving performance.

Regarding the low overhead multi-polling mechanism, especially for serving uplink VBR traffic, we propose several ideas for the goal of energy saving and a wake-up time schedule

is presented to achieve the best energy saving with a tolerable sacrifice of system bandwidth utilization. Both analytical and simulation results show that the overhearing problem can be effectively mitigated with the proposed EE-Multipoll mechanism especially when there are a lot of STAs and STAs are heavily loaded. Since the wireless environment could cause transmission error more likely than wired scenario, the energy saving issue induced from error recovery is also studied in this dissertation. Without altering the transmission order while achieving the goal of energy saving, the settings of wake-up time schedule and the renewal algorithm are studied for the TDMA-like multi-polling mechanism.

The most significant conclusion of this dissertation is that, under a tolerable performance tradeoff, the focus of the energy conservation should try to put as more STAs into low power state as possible and as long as possible. The proposed scheduling algorithms and wake-up time schedules can direct STAs not involved in a transmission going into Doze state and reduce the coordination effort for them when they are ready to accessing the channel.

Moreover, the information contained in the overheard transmission can also aid the STAs going to the Doze state if appropriate. The performance of energy conservation is expected to be more significant for a larger network since a greater percentage can use low power state by the coordination and scheduling.

Extensions of our design can be done in several directions. An interesting topic is to con-sider the duration and the randomness of the service period when concon-sidering the scheduling in S-APSD mechanism. Another interesting topic is the scheduling algorithm for the Power Save Multiple Poll mechanism (PSMP) in IEEE 802.11n [3]. This mechanism is different from our proposed EE-Multipoll in channel accessing and handling of the traffic burst. The specific scheduling algorithm for PSMP and the control of power states for Multiple-Input Multiple-Output (MIMO) transceiver are still open issues.

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