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A Self-Adaptive Scheduling Algorithm of On-Demand Broadcasts

MSWiM 2001 Rome. A Self-Adaptive Scheduling Algorithm of On-Demand Broadcasts. W. Sun, W. Shi, B. Shi, W. Ji and Y. Yu Department of Compute Science, Fudan University, Shanghai, China Presented by: Yijun Yu (now in Ghent University, Belgium). Presentation. On-demand broadcasts

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A Self-Adaptive Scheduling Algorithm of On-Demand Broadcasts

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  1. MSWiM2001Rome A Self-Adaptive Scheduling Algorithm of On-Demand Broadcasts W. Sun, W. Shi, B. Shi, W. Ji and Y. Yu Department of Compute Science, Fudan University, Shanghai, China Presented by: Yijun Yu (now in Ghent University, Belgium)

  2. Presentation • On-demand broadcasts • Previous studies • New metrics of performance • The LDCF algorithm • Experiments • Conclusion

  3. A typical on-demand broadcast system

  4. Characteristics of an On-Demand Broadcast System Versus a pull-based broadcast system: • Uplink channel is necessary for sending requests from users to the server • The server would not know the access profiles of mobile users • Time out requests should be considered

  5. Previous work First-Come-First-Serve ( FCFS ) Most-Request-First ( MRF ) Long- Wait-First ( LWF ) How to … • Reduce the average access time of mobile users? • Handle a failure request that have waitedfor “quite” a long time?

  6. New metrics of performance The average costs composed of • Access Time cost ( CAT ) • Tuning Time cost ( CTT ) • Failure request handling cost (CF)

  7. Largest Delay Cost-First algorithm Input: a request sequenceOutput: a broadcast schedulewhile true do receive new requests; for each delayed data item D, compute the cost; broadcast the items with the largest delay cost;end while

  8. The LDCF Parameters Constants • Average costs: CAT, CTT, CF • broadcast period: BP= index + data • response time limit RTL: T1 T0 + RTL Variables for access requestQ(D,Treq) • popularity factor of Data at Time: PF(D,T) • safety factor: SF(Q,T)=(Treq+RTL-T) / BP • Fail rate: FR(SF) = RR(SF) / R(SF) * FR(SF-1)

  9. The LDCF Cost Function Delay cost for request Q:DC(Q) = BP*CAT+CTT+FR(SF(Q,T))*CF Cost function for data D: Cost(D) = SUMQ(D,T){DC(Q)} = PF(D,T)*(BP*CAT+CTT) +SUMQ(D,T) {FR(SF(Q,T))*CF}

  10. Experiment settings The following parameters are assumed: • M: number of data items for broadcast=1000 • Data: number of data items in one BP unit • Index: length of index = 6 • Received request number per time slot • Zipf(k): skewness of the access distribution • RTL: Response time Limit • CAT=1, CTT=20, CF=2000

  11. 1. Average Cost when fail rate of request is low

  12. 2. Average Cost when fail rate is high

  13. 3. Average Cost vs BP

  14. 4. Average Cost vs RTL

  15. 5. Average Cost vs skewness of data access distribution

  16. Conclusion • When discussing the performance of a scheduling algorithm, we should take into account not only AT, but also TT and request failure. • LDCF was compared with LWF, FCFS and MRF via several experiments, indicating the average cost of LDCF scheduling is the least.

  17. Thanks MSWiM 2001 Program Committee

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