1. Streaming Stored Video Over Multi-Channel Wireless Systems: Scheduler Performance Evaluation
Ms. Sahar Ebadinezhad
Mr. Keivan Bahmani (presenter)
Assoc. Prof. Dr. Doğu Arifler
Assoc. Prof. Dr. Erhan A. İnce
Eastern Mediterranean University
9/20/2018

2. Outline : Introduction OFDMA-Based Systems Schedulers
Multi-User, Multi-Channel Wireless Systems
MPEG-4 Traffic Model and LRD
Performance Evaluation
Conclusions
Future Work
References

3. 4G and OFDMA
WiMaX
LTE

4. IEEE e Frame
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5. Multi-user Concept in OFDMA
OFDM Symbol n+1
OFDM Symbol n
OFDM Symbol n+2
Subchannels
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6. Scheduling Disciplines:
Frequency Selective Scheduling (User Diversity)
Frequency Diverse Scheduling (Frequency Diversity)
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7. Multi-User, Multi-Channel Wireless Systems
𝑄 𝑖 𝑡+1 = 𝑄 𝑖 𝑡 − 𝑗=1 𝐾 𝑋 𝑖𝑗 (𝑡)𝑌 𝑖𝑗 (𝑡) 𝐴 𝑖 (𝑡)
𝑎 + =max⁡(𝑎,0)
𝑖 𝑌 𝑖𝑗 𝑡 ≤1
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8. i.i.d ON-OFF random variable
Wireless Channel
i.i.d ON-OFF random variable
in each time slot
to model fading
[2]
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9. Frequency Selective Scheduling:
Evaluated Algorithms:
Round Robin Scheduling (RR)
Maximum-Throughput Scheduling (MT)
Maximum-Weight Scheduling (MW)
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10. Round Robin (RR)
Channel-unaware
Fairest
low complexity
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11. Maximum-Throughput (MT)
Channel-aware
Allocating each subchannel
Maximizing the over the air throughput
Starving users with bad channel
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12. Maximum-weight Scheduling:
The allocation is made by selection of the user with the largest weight.
Weight =( 𝑋 𝑖𝑗 (𝑡) 𝑄 𝑖 (𝑡))
𝑋 𝑖𝑗 𝑡 : 𝑎𝑐ℎ𝑖𝑒𝑣𝑎𝑏𝑙𝑒 𝑑𝑎𝑡𝑎 𝑟𝑎𝑡𝑒 𝑜𝑛 𝑗𝑡ℎ 𝑠𝑢𝑏𝑐ℎ𝑎𝑛𝑛𝑒𝑙 for i th user
𝑄 𝑖 𝑡 : queue length of i th user
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13. Synthetic Video Traffic :
MPEG-4 Traffic with IBBPBBPBBPBB GOP and 25 frame/sec
Exhibiting Long-Range Dependence (LRD)
Predominant video format for YouTube over Wireless Mobile Networks ( Itag 17 )[5]
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14. Synthetic Video Traffic :
Scene Length
Geometric (p=0.098)
I-frame Size
Lognormal(μ=9.65, σ=0.44)
P-frame Size
Lognormal(μ=8.90, σ=0.68)
B-frame Size
Lognormal(μ=8.59, σ=0.69)
AR(2) model parameters
[4]
𝑎 1 =0.39, 𝑎 2 =0.15, σ 𝑒 =4.36
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15. Stability comparison among RR, MT, MW Schedulers
(K=20, q=0.5, R=50 bytes/slot.)
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16. Effect of channel (K=20, N=4, R=50 bytes/slot .)
Note that for the channel on-probability in the range between there is a big difference between channel-aware and channel-unaware schedulers.
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17. Effect of Traffic Shaping
Max-Weight scheduler, Changing Inter-arrival time from 40-ms to
10-ms (K=20, N=4, q=0.5, R=50 bytes/slot.)
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18. Conclusion:
Performance of three scheduling algorithms (RR, MT, MW) has been evaluated for streaming stored video over multi-user, multi-channel wireless systems.
Adapting a traffic shaping mechanism in the source video server can greatly decrease the amount of lost bytes and I-frames in a finite buffer size scenario.
When the system is unstable with 5 users, the buffer occupancy with ON/OFF sources is about 1 megabyte (MB) less than that with MPEG sources
For channel on-probabilities in the range between using a channel-aware scheduler will provide much lower mean queue length in comparison to a that of channel-unaware schedulers.
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19. Future work
A more realistic channel can be adapted to make the results more appropriate for use in practice.
More complex scheduling algorithm such as SSG can be evaluated under the same condition.
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20. Thank you for your attention
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21. References
F. Capozzi, G. Piro, L. Grieco, G. Boggia, and P. Camarda, “Downlink packet scheduling in LTE cellular networks: Key design issues and a survey,” IEEE Communications Surveys Tutorials, vol. 15, no. 2, pp. 678–700, 2013.
S. Bodas, S. Shakkottai, L. Ying, and R. Srikant, “Low-complexity scheduling algorithms for multichannel downlink wireless networks,” IEEE/ACM Trans. Networking, vol. 20, no. 5, pp. 1608–1621, Oct
S. Kittipiyakul and T. Javidi, “Delay-optimal server allocation in multiqueue multiserver systems with time-varying connectivities,” IEEE Trans. Inform. Theory, vol. 55, no. 5, pp. 2319–2333, May 2009.
WiMAX Forum, “WiMAX system evaluation methodology v.2.1,” [Online]. Available: wimax_system_evaluation_methodology_v2_1.pdf
J. Ramos, J. Prados-Garzon, P. Ameigeiras, J. Navarro and J. Lopez “Characteristics of mobile YouTube traffic,” IEEE Wireless Communications, vol. 21, no. 1, pp , February 2014.
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