1. 1 / 21 Providing Differentiated Services from an Internet Server Xiangping Chen and Prasant Mohapatra Dept. of Computer Science and Engineering Michigan State University IEEE International Conference on Computer Communications and Networks, 1999 Computer Architecture Lab. Yoon Hye Young

2. 2 / 21 Contents Introduction Distributed Server Model Goal of experimental study Simulation Results Conclusion

3. 3 / 21 Introduction Performance challenge of an Internet Server Continuous increase of traffic Volume Tens of millions of requests per day Increased data processing. Workload burst higher request intensity in peak period

4. 4 / 21 Introduction Improving server response time High performance server and broad network bandwidth Load sharing and balancing Distributed server system Differentiated services Prioritized processing

5. 5 / 21 Distributed Server Model

6. 6 / 21 Distributed Server Model Four logical components S I : Initiator Q : Scheduler S i (i=1..N) : Task server N S : Communication channel Qos Admission control, scheduling and efficient task assignment

7. 7 / 21 Goal of the experimental study Need for service differentiation E-commerce Continuous Media data delivery The server needs to complement the QoS support of the NGI(Next Generation Internet) architecture. Implementation could be at the application layer or at any lower layer. Our goal here is to analyze the feasibility of the concept through a simplified model.

8. 8 / 21 Simulation An event driven simulator implementation Generate workload from real trace file ClarkNet HTMIMGAUDVDODYNOTH Req.Rat. (%)19.978.00.20.0071.20.69 Acc.Rat. (%)15.076.62.4 0.82.8 Tran Sz(KB)7.439.67135.13,5156.6337.12 Tran Cov.2.141.661.240.353.353.89

9. 9 / 21 Simulation Terms Mean response time the time between the acceptance of the request and the completion of the service Slowdown response time service time

10. 10 / 21 Effectiveness of Prioritized Scheduling

11. 11 / 21 Effectiveness of Prioritized Scheduling Results Increase in server utilization, response time increase much faster under high utilization High priority requests incur low delay even when the system approaches full utilization

12. 12 / 21 High Priority Task Response Time

13. 13 / 21 High Priority Task Response Time Results With the increase in high priority ratio, the curve gets closer to the original non-prioritized system curve That means, the margin of benefit obtained from differentiating service diminishes That is, we need a proper high priority ratio.

14. 14 / 21 Low Priority Task Response Time

15. 15 / 21 Low Priority Task Response Time Results With the increase in the high priority ratio, the system utilization decrease That is, low priority task is getting bad.

16. 16 / 21 Task Assignment Schemes

17. 17 / 21 Task Assignment Schemes Type of task assignment schemes RR(Round-Robin) SQF(Shortest_Queue_First) E_SQF(Enhanced SQF) Result E_SQF is the best, but there is no significant difference from SQF under high load

18. 18 / 21 Analysis Objective To derive a guideline for performance of high priority request By calculating a high priority task’s waiting time

19. 19 / 21 Analysis WhWh Mean waiting time for tasks in high priority group W1W1 Residual life of a task in service W2W2 Sum of execution time of queued tasks PhPh Probability of high priority tasks AhAh Arrival interval of high priority tasks XMean service time for tasks. X=X h =X l ThTh Mean system time for tasks in high priority group N qh The number of queued high priority tasks PlPl Probability of low priority tasks in service WlWl Mean waiting time for tasks in low priority group TlTl Mean system time for low priority tasks Notations used in the study

20. 20 / 21 Analysis W h = W 1 + W 2 W 1 = P h * X h + P l *X l W 2 = X*N qh N qh =A h * W h W h = W 1 + W 2 = X* A h * W h + W 1 1- X* A h W1W1 W h = = 1- X* A h P h * X+ P l *X 1- X* A h X The mean waiting time for high priority’s task is depend on the high priority system utilization, X* A h : proper high priority ratio is needed. The upper bound of W 1 is X

21. 21 / 21 Conclusions Service differentiation do improve the response time of high priority tasks significantly with comparatively low penalty to low priority tasks. The upper bound of waiting time depends on the task arrival rate with equal or higher priority and the service time. The combination of selective discard and priority queuing is necessary and sufficient to provide predictable services in an Internet server.