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AN ENERGY-EFFICIENT SCHEDULING FOR MULTIPLE MSSS IN IEEE 802.16E BROADBAND WIRELESS

AN ENERGY-EFFICIENT SCHEDULING FOR MULTIPLE MSSS IN IEEE 802.16E BROADBAND WIRELESS. Shih-Chang Huang, Chien Chen, and Rong-Hong Jan, and Cheng-Chung Hsieh IEEE 19 th Personal, Indoor and Mobile Radio Communications, 2008. (PIMRC 2008). Outline. Introduction MWT and feasible slot allocation

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AN ENERGY-EFFICIENT SCHEDULING FOR MULTIPLE MSSS IN IEEE 802.16E BROADBAND WIRELESS

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  1. AN ENERGY-EFFICIENT SCHEDULING FOR MULTIPLE MSSS INIEEE 802.16E BROADBAND WIRELESS Shih-Chang Huang, Chien Chen, and Rong-Hong Jan, and Cheng-Chung Hsieh IEEE19th Personal, Indoor and Mobile Radio Communications, 2008. (PIMRC 2008)

  2. Outline • Introduction • MWT and feasible slot allocation • Energy efficiency scheduling for multiple MSSs • Simulation • Conclusion

  3. Introduction • The MSS simply sleeps for a predefined period of time and then returns to normal operation to save power. • We first focus our efforts on finding the minimum wakeup time and arrange for multiple MSSs to achieve maximum bandwidth utilization.

  4. Minimum wakeup time

  5. Minimum wakeup time OFDM Frame Delay Constraint of C1 C1 3 4 1 2 5 6 7 8 9 0 Delay Constraint of C2 C2 a b c d e Minimum Delay Constraint

  6. Feasible slot allocation OFDM Frame Delay Constraint of C1 C1 3 4 1 2 5 6 7 8 9 0 Delay Constraint of C2 C2 a b c d e 1 2 3 a 5 6 b 4 7 d 8 c Minimum Delay Constraint Data ready Feasible slots

  7. Scheduling for multiple MSSs

  8. Ford-Fulkerson Algorithm a /2 0 /2 0 1 S D /1 0 1 1 0 /2 2 1 0 /2 b

  9. Scheduling for multiple MSSs OFDM Frame MSS A A MSS B B Feasible slots MWTblocks OFDM frames 1 A 0/1 0/1 0/1 1/1 1/1 S 1/1 0/1 2 D 0/1 B 1/1 1/1 0/1 0/1 1/1 0/1 3

  10. Scheduling for multiple MSSs MWT Cycle = 8 MWT Cycle = 2 LCM(8,2) = 8

  11. Scheduling for multiple MSSs MWTblocks OFDM frames A1 1 2 A2 3 A3 4 S B1 D 5 B2 6 B3 7 B4 8

  12. Scheduling for multiple MSSs • If MWT blocks is larger than OFDM frames, we know that there are no feasible schedules. • If the feasible slot size is large, it is possible that the blocks of a MSS may lose the order of their generation sequence. However, this problem will not influence the schedule result.

  13. The Time Complexity • The time complexity of the Ford-Fulkerson maximum flow algorithm is known as O(n3) • Nodes in the schedule graph is • Total time complexity is

  14. Simulation • Traffic arrival time: 20ms to 40ms • QoS delay constraint: 200ms to 400ms • Generated packet size: 250 Bytes to 400 Bytes • Maximal data rate that BS offers to all MSSs is 2 Mbps

  15. The sleeping ratios

  16. Number of scheduled MSSs

  17. Bandwidth utilization

  18. Conclusion • We propose an energy-efficient traffic scheduling approach for multiple MSSs in 802.16e broadband wireless networks. • We let all MSSs achieve a goal to minimize the wakeup time and apply the Ford-Fulkerson maximum flow algorithm to obtain a feasible schedule.

  19. Scheduling for multiple MSSs

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