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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. - PowerPoint PPT Presentation
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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.
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