Using GI-G-1 queuing model for rtPS performance evaluation in 802.16 networks

2011 ◽  
Vol 25 (3) ◽  
pp. 314-327 ◽  
Author(s):  
Shang-Juh Kao ◽  
Chia-Chuan Chuang
2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Jie Wang ◽  
Kai Cui ◽  
Kuanjiu Zhou ◽  
Yanshuo Yu

Due to the limited resources of wireless sensor network, low efficiency of real-time communication scheduling, poor safety defects, and so forth, a queuing performance evaluation approach based on regular expression match is proposed, which is a method that consists of matching preprocessing phase, validation phase, and queuing model of performance evaluation phase. Firstly, the subset of related sequence is generated in preprocessing phase, guiding the validation phase distributed matching. Secondly, in the validation phase, the subset of features clustering, the compressed matching table is more convenient for distributed parallel matching. Finally, based on the queuing model, the sensor networks of task scheduling dynamic performance are evaluated. Experiments show that our approach ensures accurate matching and computational efficiency of more than 70%; it not only effectively detects data packets and access control, but also uses queuing method to determine the parameters of task scheduling in wireless sensor networks. The method for medium scale or large scale distributed wireless node has a good applicability.


2021 ◽  
Vol 25 (1) ◽  
pp. 65-70
Author(s):  
I. Adaji ◽  
A. Lawal ◽  
A. Abdullahi ◽  
A. Abdulkadir

In this paper, performance evaluation of outpatient department waiting line system in a city hospital in Nigeria has been studied using a multiple server queuing model. The relevant data used in the research were collected for a period of four weeks through direct observations and interviews. The results of the research showed that with Two Doctors for the morning session patients spent an average of 1.0233hours in the system, out of which 0.932hours are spent on the queue with 95.45% Doctor Utilization. When the numbers of the Doctors were increased to 3, 4 and 5, it was found that a patient will spend an average of 0.125hours, 0.0975 hours and 0.0924hours in the system respectively. In each of the 3, 4 and 5 Doctors increased, the system will have 63.64%, 47.73% and 38.18% Doctors utilization respectively. With one Doctor for the evening session, the system has 54.55% Doctor Utilization and patient spent0.2hours in the system. The overall results showed that there is need to increase the number of Doctors to 3 or 4 for the morning session to achieved optimal service delivery while one Doctor in the evening session should be maintained. The results from the research could serves as important information to the management of the hospital for better services delivery. Keywords: Doctors, Patient, Doctor Utilization, Queuing model, Evaluation


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