Online-scheduling using past and real-time data. An assessment by discrete event simulation using exponential smoothing

2017 ◽  
Vol 19 ◽  
pp. 158-163 ◽  
Author(s):  
Jens Heger ◽  
Sebastian Grundstein ◽  
Michael Freitag
Keyword(s):  
Real Time ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Exponential Smoothing ◽  
Online Scheduling ◽  
Time Data ◽  
Event Simulation ◽  
Real Time Data

Real-time data-driven discrete-event simulation for garment production lines

2020 ◽  
pp. 1-12 ◽  
Author(s):  
Woo-Kyun Jung ◽  
Hyungjung Kim ◽  
Young-Chul Park ◽  
Jae-Won Lee ◽  
Eun Suk Suh
Keyword(s):  
Real Time ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Data Driven ◽  
Time Data ◽  
Production Lines ◽  
Event Simulation ◽  
Real Time Data

scholarly journals Supporting Real-Time Data Transmissions in Cognitive Radio Networks Using Queue Shifting Mechanism

2021 ◽  
Vol 12 (1) ◽  
pp. 1-18
Author(s):  
B. Seetha Ramanjaneyulu ◽  
K. Annapurna
Keyword(s):  
Cognitive Radio ◽  
Real Time ◽  
Cognitive Radio Networks ◽  
Discrete Event ◽  
Radio Networks ◽  
Time Data ◽  
Event Simulation ◽  
Blocking Probabilities ◽  
Real Time Data ◽  
Packet Delays

As cognitive radio networks are conceptualized to make use of the opportunistic spectrum access, the users of these networks may face problems in satisfying their quality of service (QoS) requirements. Some services of users like real-time audio and video which cannot tolerate inter-packet delays will be affected more due to this. The problem occurs due to the non-availability of channels to these applications at some instants. This problem can be addressed if the available channels are judiciously distributed among the competing users. One such mechanism that dynamically allocates the competing users to multiple queues, and shifting the users to higher-level queues as the time elapses is introduced in this work. This is found to help the users of cognitive radio networks to communicate reasonably well even when fewer channels are available for opportunistic use. Results are indicated in terms of blocking probabilities of real-time data. Markov chain-based analysis and discrete event simulation studies are carried out.

Discrete Event Simulation and Real Time Locating Systems

2012 ◽  
Vol 4 (4) ◽  
pp. 16-28
Author(s):  
T. Eugene Day ◽  
Ajit N. Babu ◽  
Steven M. Kymes ◽  
Nathan Ravi
Keyword(s):  
Health Care ◽  
Real Time ◽  
Discrete Event Simulation ◽  
Medical Center ◽  
Discrete Event ◽  
Healthcare Delivery ◽  
The United States ◽  
Careful Consideration ◽  
Health Administration ◽  
Event Simulation

The Veteran’s Health Administration (VHA) is the largest integrated health care system in the United States, forming the arm of the Department of Veterans Affairs (VA) that delivers medical services. From a troubled past, the VHA today is regarded as a model for healthcare transformation. The VA has evaluated and adopted a variety of cutting-edge approaches to foster greater efficiency and effectiveness in healthcare delivery as part of their systems redesign initiative. This paper discusses the integration of two health care analysis platforms: Discrete Event Simulation (DES), and Real Time Locating systems (RTLS) presenting examples of work done at the St. Louis VA Medical Center. Use of RTLS data for generation and validation of DES models is detailed, with prescriptive discussion of methodologies. The authors recommend the careful consideration of these relatively new approaches which show promise in assisting systems redesign initiatives across the health care spectrum.

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