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Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering...

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Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering University of California, Santa Cruz [email protected]
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Page 1: Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering University of California, Santa Cruz alexb@cse.ucsc.edu.

Finite-Source Multiserver Queue with Preemptive Priorities

Alexandre BrandwajnSchool of Engineering

University of California, Santa [email protected]

Page 2: Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering University of California, Santa Cruz alexb@cse.ucsc.edu.

Plan

Motivation System considered Simple recurrent analysis Alternative method Classes on several priority levels Conclusions

Page 3: Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering University of California, Santa Cruz alexb@cse.ucsc.edu.

Motivation

Priority service computer application

Finite number of request sources Multiple servers Arbitrary number of classes

Page 4: Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering University of California, Santa Cruz alexb@cse.ucsc.edu.

System considered

Page 5: Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering University of California, Santa Cruz alexb@cse.ucsc.edu.

Assumptions

M servers c classes exponentially

distributed idle times service demands

1 class / priority level

Page 6: Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering University of California, Santa Cruz alexb@cse.ucsc.edu.

Assumptions

Class i, i = 1,…c

Ni sources

1/i mean idle time

1/i mean service demand

Class 1 highest priority

Page 7: Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering University of California, Santa Cruz alexb@cse.ucsc.edu.

Simple recurrent analysis

Page 8: Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering University of California, Santa Cruz alexb@cse.ucsc.edu.

Simple recurrent analysis

One class at a time state description (ni,li)

ni users of class i

li servers unavailable

servers vanish i(ni,li)

reappear i(ni,li)

Page 9: Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering University of California, Santa Cruz alexb@cse.ucsc.edu.

Simple recurrent analysis

Approximation i(ni,li) i(li)

i(ni,li) i(li)

two-dimensional birth & death p(ni,li)

starting with class 1

Page 10: Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering University of California, Santa Cruz alexb@cse.ucsc.edu.

Simple recurrent analysis

i+1(li+1) = l

l

i

i

0

1

p(ni=li+1-li,li)[i(li)+(Ni-ni)i]/ p(li+1),

for li+1 = 0,…,min(M-1,

i

j1

Nj)

Page 11: Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering University of California, Santa Cruz alexb@cse.ucsc.edu.

Simple recurrent analysis

i+1(li+1) = l

l

i

i

0

1

p(ni=li+1-li,li)[i(li)+s(ni,li)i]/p(li+1)

for li+1 = 1,…,min(M, j

i

1

Nj)

Page 12: Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering University of California, Santa Cruz alexb@cse.ucsc.edu.

Results with 3 serversSet Solution Method Class Throughput +- Mean Number +-3 exact 1 0.521 0.787

2 7.394 16.303recurrence 1 0.521 0.787

2 7.394 16.303

5 simulation 1 0.524 0.007 0.792 0.0022 14.402 0.067 2.119 0.0103 0.387 0.007 8.452 0.044

recurrence 1 0.521 0.7872 14.409 2.1183 0.389 8.445

6 simulation 1 0.464 0.011 0.452 0.0152 19.527 0.035 1.105 0.0073 1.506 0.024 5.490 0.1054 0.492 0.045 9.434 0.069

recurrence 1 0.455 0.4552 19.488 1.1023 1.527 5.4194 0.440 9.560

Page 13: Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering University of California, Santa Cruz alexb@cse.ucsc.edu.

Results with 2 servers

Set Solution Method Class Throughput +- Mean Number +-4 exact 1 0.516 0.841

2 10.116 2.977recurrence 1 0.516 0.841

2 10.117 2.977

7 simulation 1 0.274 0.006 0.282 0.0072 11.510 0.039 0.705 0.0033 0.786 0.007 1.627 0.0314 1.209 0.024 2.789 0.0355 0.905 0.023 4.542 0.017

recurrence 1 0.273 0.2742 11.500 0.7003 0.809 1.5734 1.440 2.5605 0.532 4.734

Page 14: Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering University of California, Santa Cruz alexb@cse.ucsc.edu.

Parameter sets

SetNumber of

ClassesClass

Number of Sources

Mean Source Idle Time

Mean Service Time

1 2 1 6 10 1.52 18 5 3

2 2 1 6 10 1.52 18 0.5 0.3

3 2 1 6 10 1.52 20 0.5 0.3

4 2 1 6 10 1.52 10 0.2 0.1

5 3 1 6 10 1.52 5 0.2 0.13 10 4 2

6 4 1 5 10 12 5 0.2 0.053 10 3 14 10 1 0.01

7 5 1 3 10 12 3 0.2 0.053 4 3 14 4 1 0.25 5 0.5 0.1

Page 15: Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering University of California, Santa Cruz alexb@cse.ucsc.edu.

Set 5 with 3 servers

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

Simulation Recurrence

Class 1Class 2Class 3

Page 16: Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering University of California, Santa Cruz alexb@cse.ucsc.edu.

Set 6 with 3 servers

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

Simulation Recurrence

Class 1Class 2Class 3Class 4

Page 17: Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering University of California, Santa Cruz alexb@cse.ucsc.edu.

Set 7 with 2 servers

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Simulation Recurrence

Class 1Class 2Class 3Class 4Class 5

Page 18: Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering University of California, Santa Cruz alexb@cse.ucsc.edu.

Simple recurrent analysis

Generally within confidence intervals occasionally more significant errors

more likely with longer service at higher priority

not systematic growth with ratio of service times

– peak and vanish

Page 19: Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering University of California, Santa Cruz alexb@cse.ucsc.edu.

Alternative method

Page 20: Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering University of California, Santa Cruz alexb@cse.ucsc.edu.

Alternative method

Page 21: Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering University of California, Santa Cruz alexb@cse.ucsc.edu.

Alternative approach

Pair (i, i+1) State description

(ni,ni+1,li)

ni, ni+1 users of class i and i+1

li servers unavailable to pair

Page 22: Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering University of California, Santa Cruz alexb@cse.ucsc.edu.

Alternative approach

Servers vanishi(ni,li)

reappeari(ni,li)

Pair (1,2) keep

other (i,i+1) keep results for i+1

Page 23: Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering University of California, Santa Cruz alexb@cse.ucsc.edu.

Set 6 with 3 servers

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

Simulation Recurrence Pairwise

Class 1Class 2Class 3Class 4

Page 24: Finite-Source Multiserver Queue with Preemptive Priorities Alexandre Brandwajn School of Engineering University of California, Santa Cruz alexb@cse.ucsc.edu.

Set 7 with 2 servers

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Simulation Recurrence Pairwise

Class 1Class 2Class 3Class 4Class 5


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