scholarly journals Diffusion Model of Preemptive-Resume Priority Systems and Its Application to Performance Evaluation of SDN Switches

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5042
Author(s):  
Tomasz Nycz ◽  
Tadeusz Czachórski ◽  
Monika Nycz
Keyword(s):  
Diffusion Approximation ◽  
Numerical Models ◽  
Software Defined Networks ◽  
Detailed Model ◽  
Preemptive Resume ◽  
Central Controller ◽  
Priority Systems ◽  
Primary Element ◽  
Preemptive Resume Priority ◽  
General Distributions

The increasing use of Software-Defined Networks brings the need for their performance analysis and detailed analytical and numerical models of them. The primary element of such research is a model of a SDN switch. This model should take into account non-Poisson traffic and general distributions of service times. Because of frequent changes in SDN flows, it should also analyze transient states of the queues. The method of diffusion approximation can meet these requirements. We present here a diffusion approximation of priority queues and apply it to build a more detailed model of SDN switch where packets returned by the central controller have higher priority than other packets.

On queueing systems by retrials

1983 ◽  
Vol 20 (02) ◽  
pp. 380-389 ◽  
Author(s):  
Vidyadhar G. Kulkarni
Keyword(s):  
General Result ◽  
Service Time ◽  
Queueing Systems ◽  
Single Server ◽  
Expected Number ◽  
Waiting Room ◽  
Second Moments ◽  
Different Types ◽  
General Distributions ◽  
Arbitrary Service Time

A general result for queueing systems with retrials is presented. This result relates the expected total number of retrials conducted by an arbitrary customer to the expected total number of retrials that take place during an arbitrary service time. This result is used in the analysis of a special system where two types of customer arrive in an independent Poisson fashion at a single-server service station with no waiting room. The service times of the two types of customer have independent general distributions with finite second moments. When the incoming customer finds the server busy he immediately leaves and tries his luck again after an exponential amount of time. The retrial rates are different for different types of customers. Expressions are derived for the expected number of retrial customers of each type.

Some properties of Rosen's MLE for general distributions

2001 ◽  
Vol 21 (3) ◽  
pp. 375-382
Author(s):  
Cui Hengjian ◽  
Chen Qiuhua
Keyword(s):  
General Distributions
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