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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

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Contents Introduction Distributed Server Model Goal of experimental study

Simulation Results

Conclusion

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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

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Introduction Improving server response time

High performance server and broad network bandwidth

Load sharing and balancing Distributed server system

Differentiated services Prioritized processing

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Distributed Server Model

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Distributed Server Model Four logical components

SI : Initiator Q : Scheduler Si(i=1..N) : Task server NS : Communication channel

Qos Admission control, scheduling and efficient task as

signment

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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.

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Simulation An event driven simulator implementation

Generate workload from real trace file ClarkNet

HTM IMG AUD VDO DYN OTH

Req.Rat. (%)

19.9 78.0 0.2 0.007 1.2 0.69

Acc.Rat. (%)

15.0 76.6 2.4 2.4 0.8 2.8

Tran Sz(KB) 7.43 9.67 135.1 3,515 6.63 37.12

Tran Cov. 2.14 1.66 1.24 0.35 3.35 3.89

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Simulation Terms

Mean response time the time between the acceptance of the request

and the completion of the service Slowdown

response time

service time

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Effectiveness of Prioritized Scheduling

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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

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High Priority Task Response Time

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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.

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Low Priority Task Response Time

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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.

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Task Assignment Schemes

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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

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Analysis Objective

To derive a guideline for performance of high priority request

By calculating a high priority task’s waiting time

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Analysis

Wh Mean waiting time for tasks in high priority group

W1 Residual life of a task in service

W2 Sum of execution time of queued tasks

Ph Probability of high priority tasks

Ah Arrival interval of high priority tasks

X Mean service time for tasks. X=Xh=Xl

Th Mean system time for tasks in high priority group

Nqh The number of queued high priority tasks

Pl Probability of low priority tasks in service

Wl Mean waiting time for tasks in low priority group

Tl Mean system time for low priority tasksNotations used in the study

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Analysis

Wh = W1+ W2

W1= Ph* Xh+ Pl*Xl

W2= X*Nqh

Nqh=Ah* Wh

Wh = W1+ W2

= X* Ah* Wh + W1

1- X* Ah

W1Wh =

=1- X* Ah

Ph* X+ Pl*X

1- X* Ah

X

The mean waiting time for high priority’s task is depend on the high priority system utilization, X* Ah

: proper high priority ratio is needed.

The upper bound of W1 is X

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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.