What kind of probability distribution would you use to model network queues

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SUMMARY

The discussion centers on modeling network queues using probability mass functions (pmf) in the context of queuing theory. Specifically, it examines a scenario where 10 computers share a single cable, each requiring an average of 12 minutes of network access per hour. Participants suggest that while this situation involves discrete random variables, traditional pmf models may not adequately represent the simultaneous demand for the network line. The conversation emphasizes the need for a tailored approach to accurately model such queuing scenarios.

PREREQUISITES
  • Understanding of discrete random variables
  • Familiarity with probability mass functions (pmf)
  • Basic knowledge of queuing theory
  • Concept of network traffic modeling
NEXT STEPS
  • Research specific probability distributions applicable to queuing systems, such as the Poisson distribution
  • Explore advanced queuing theory concepts, including Little's Law
  • Study network traffic modeling techniques and tools
  • Investigate simulation methods for modeling network queues
USEFUL FOR

Network engineers, data scientists, and anyone involved in optimizing network performance and understanding queuing dynamics in computer networks.

Ben1220
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As an example, say 10 computers are connected to the network through 1 cable, (and so only 1 can be connected at anyone time) and each computer needs to be on the network for 12 minutes an hour on average, then what kind of pmf would you use to model the number of computers that simultaneously need the line? It looks like a discrete random variable, but none of the ones I know seem to fit this situation exactly.
 
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