Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Poisson Probability Distribution01:09

Poisson Probability Distribution

9.9K
A Poisson probability distribution is a discrete probability distribution. It gives the probability of a number of events occurring in a fixed interval of time or space if these events happen at a known average rate and independently of the time since the last event. For example, a book editor might be interested in the number of words spelled incorrectly in a particular book. It might be that, on average, there are five words spelled incorrectly in 100 pages. The interval is 100 pages.
The...
9.9K
Noncompartmental Analysis: Mean Residence Time01:05

Noncompartmental Analysis: Mean Residence Time

314
According to statistical moment theory, mean residence time (MRT) is an important measure in pharmacokinetics. MRT can be defined as the expected mean of a probability density function distribution. It provides valuable insights into drug disposition in the body.
After the administration of a drug through intravenous bolus injection, the drug molecules are distributed throughout the body and remain there for varying periods. The MRT represents the average time these drug molecules stay in the...
314
Drug Accumulation During Multiple Dosing: Repetitive IV Injections01:21

Drug Accumulation During Multiple Dosing: Repetitive IV Injections

34
Calculating drug dosage and accumulation in multiple-dose regimens is crucial for achieving therapeutic efficacy while avoiding toxicity. This involves determining the plasma drug concentrations over time to optimize dosing schedules. The principle of superposition is fundamental in this process, allowing for the prediction of drug concentration in plasma following multiple doses based on single-dose data.The principle of superposition asserts that the plasma concentration-time curves from...
34
Compartment Models: Single-Compartment Model01:14

Compartment Models: Single-Compartment Model

2.6K
The single-compartment model serves as a simplified representation of the human body. This model assumes that the body functions as a single, well-mixed open compartment. When a drug is administered intravenously, it enters the body and quickly distributes uniformly. The drug then undergoes biotransformation and elimination, ultimately leaving the body. The volume of this compartment is referred to as the apparent volume of distribution into which the drug can uniformly distribute. In this...
2.6K
Model Approaches for Pharmacokinetic Data: Compartment Models01:14

Model Approaches for Pharmacokinetic Data: Compartment Models

255
Compartmental analysis is a widely adopted approach to characterizing drug pharmacokinetics. It uses compartment models that conceptualize the body as a collection of reversibly communicating compartments, each representing a group of tissues exhibiting similar drug distribution characteristics. The movement rate of the drug between these compartments is typically described by first-order kinetics.
Two primary types of compartment models are recognized: mammillary and catenary. The more...
255
Buffers: Buffer Capacity01:09

Buffers: Buffer Capacity

1.7K
Buffer capacity is the quantitative measure of a buffer to resist the change in pH. As shown in the following equation, the buffer capacity, denoted by 'beta', is expressed as the number of moles of acid or base needed to change the pH of a one-liter buffer solution by 1 unit. Here, Ca and Cb indicate the number of moles of acid and base, respectively. Note that dpH represents the change in pH.
In the graph, pH is plotted as a function of the number of moles of base (Cb) added to a weak...
1.7K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Intelligent Method of Identifying the Nonlinear Dynamic Model for Helicopter Turboshaft Engines.

Sensors (Basel, Switzerland)·2024
Same author

Cannabidiol Intervention for Muscular Tension, Pain, and Sleep Bruxism Intensity-A Randomized, Double-Blind Clinical Trial.

Journal of clinical medicine·2024
Same author

Transient Behavior of a Queueing Model with Hyper-Exponentially Distributed Processing Times and Finite Buffer Capacity.

Sensors (Basel, Switzerland)·2022
Same author

On Transient Queue-Size Distribution in a Model of WSN Node with Threshold-Type Power-Saving Algorithm.

Sensors (Basel, Switzerland)·2022
Same author

Model of Production System Evaluation with the Influence of FDM Machine Reliability and Process-Dependent Product Quality.

Materials (Basel, Switzerland)·2021
Same author

On the Time to Buffer Overflow in a Queueing Model with a General Independent Input Stream and Power-Saving Mechanism Based on Working Vacations.

Sensors (Basel, Switzerland)·2021

Related Experiment Video

Updated: Oct 12, 2025

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
14:55

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street

Published on: January 20, 2023

3.6K

Study on Transient Queue-Size Distribution in the Finite-Buffer Model with Batch Arrivals and Multiple Vacation

Wojciech M Kempa1, Rafał Marjasz2

  • 1Department of Mathematics Applications and Methods for Artificial Intelligence, Faculty of Applied Mathematics, Silesian University of Technology, 23 Kaszubska Str., 44-100 Gliwice, Poland.

Entropy (Basel, Switzerland)
|November 27, 2021
PubMed
Summary

This study analyzes finite-buffer queueing systems with batch arrivals and repeated vacations, crucial for energy-saving networks. Results offer insights into queue dynamics for optimizing system performance.

Keywords:
finite buffermultiple vacation policypotential methodqueue sizetransient state

More Related Videos

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
13:00

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

10.0K
Measuring Delay Discounting in Humans Using an Adjusting Amount Task
07:47

Measuring Delay Discounting in Humans Using an Adjusting Amount Task

Published on: January 9, 2016

15.6K

Related Experiment Videos

Last Updated: Oct 12, 2025

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
14:55

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street

Published on: January 20, 2023

3.6K
Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
13:00

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

10.0K
Measuring Delay Discounting in Humans Using an Adjusting Amount Task
07:47

Measuring Delay Discounting in Humans Using an Adjusting Amount Task

Published on: January 9, 2016

15.6K

Area of Science:

  • Operations Research
  • Queueing Theory
  • Performance Analysis

Background:

  • Finite-buffer queueing models are essential for systems like IoT and telecommunication networks.
  • Energy-saving mechanisms often involve cyclic monitoring, leading to vacation periods for servers.
  • Batch arrivals and generally distributed repeated vacations introduce complexity to transient analysis.

Purpose of the Study:

  • To analyze the transient behavior of a finite-buffer queueing model with batch arrivals and generally distributed repeated vacations.
  • To derive a time-dependent queue-size distribution, conditioned by the initial buffer state.
  • To provide a method for understanding system dynamics in applications like energy-efficient networks.

Main Methods:

  • Identification of renewal moments and application of the law of total probability.
  • Derivation of a system of Volterra-type integral equations for queue-size distribution.
  • Algebraic approach using Korolyuk's potential method for Laplace transforms.

Main Results:

  • A system of Volterra-type integral equations for the time-dependent queue-size distribution was derived.
  • A compact-form solution in Laplace transforms was obtained.
  • A numerical example demonstrated the impact of key parameters on queue-size distribution.

Conclusions:

  • The study provides a robust analytical framework for finite-buffer queueing systems with complex arrival and service patterns.
  • The derived solutions are applicable to performance analysis of energy-saving communication and production systems.
  • The findings enable better understanding and optimization of queue dynamics in practical applications.