Stability Behavior of FIFO Protocol in the Adversarial Queuing Model

2003 ◽  
pp. 464-479 ◽  
Author(s):  
Dimitrios K. Koukopoulos ◽  
Sotiris E. Nikoletseas ◽  
Paul G. Spirakis
Keyword(s):  
Queuing Model ◽  
Stability Behavior ◽  
Adversarial Queuing

A Characterization of Universal Stability in the Adversarial Queuing Model

2004 ◽  
Vol 34 (1) ◽  
pp. 41-66 ◽  
Author(s):  
Carme Àlvarez ◽  
Maria Blesa ◽  
Maria Serna
Keyword(s):  
Queuing Model ◽  
Adversarial Queuing ◽  
Universal Stability

Queuing Model Based Data Centers: A Review

2019 ◽  
Vol 123 ◽  
pp. 11-20 ◽  
Author(s):  
N. Thirupathi Rao ◽  
Debnath Bhattacharyya ◽  
S. Naga Mallik Raj
Keyword(s):  
Data Centers ◽  
Queuing Model ◽  
Model Based

Optimalisasi Pekerjaan Pemindahan Tanah Pada Proyek Embung Begawan Kota Tarakan Dengan Model Antrian

2017 ◽  
Vol 1 (2) ◽  
pp. 75
Author(s):  
Budi Setiawan ◽  
Hermanto Hermanto
Keyword(s):  
Soil Removal ◽  
Production Capacity ◽  
Optimal Time ◽  
Dump Truck ◽  
Queuing Model ◽  
Soil Movement ◽  
Transportation Equipment ◽  
Model Method ◽  
Mechanical Devices ◽  
Time Required

The Embung Bengawan Project in Tarakan City has several jobs requiring heavy equipment including mechanical soil removal activities. Activity of mechanical soil movement is a series in work of loading and transportation equipment. In order to achieve optimal mechanical soil removal targets, it is necessary to know the performance of the machine during the mechanical soil removal process. The optimization of production is the way to obtain production that is in accordance with optimal conditions of mechanical devices. This paper discusses the optimization of dump truck queue time and the number of dump trucks. Performance calculation tool using the method of production capacity of the tool, and calculate the optimal queue using the Queue Model method. Calculation using queuing model method obtained by result of time required by 3 excavator unit and with combined amount of dump truck will give result of cost equal to Rp 48,097,711 / day, and dump truck waiting time in queue to 1 minute. Then the optimal time is obtained by operating 3 units of excavators with a cost difference of Rp 3,572,826 / day from the real condition of the field that operates 2 excavator units

Evaluation of subway passengers transfer hub congestion based on queuing model and TOPSIS method

2021 ◽  
pp. 1-22
Author(s):  
Xiaokun Wang ◽  
Dong Ni
Keyword(s):  
Queuing Theory ◽  
Evaluation Model ◽  
Flow Characteristics ◽  
Distribution Area ◽  
Flow Density ◽  
Topsis Method ◽  
Queuing Model ◽  
Service Facility ◽  
Passenger Flow ◽  
Topsis Technique

To scientifically and reasonably evaluate and pre-warn the congestion degree of subway transfer hub, and effectively know the risk of subway passengers before the congestion time coming. We analyzed the passenger flow characteristics of various service facilities in the hub. The congested area of the subway passenger flow interchange hub is divided into queuing area and distribution area. The queuing area congestion evaluation model selects M/M/C and M/G/C based on queuing theory. The queuing model and the congestion evaluation model of the distribution area select the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method. Queue length and waiting time are selected as the evaluation indicators of congestion in the queuing area, and passenger flow, passenger flow density and walking speed are selected as the evaluation indicators of congestion in the distribution area. And then, K-means cluster analysis method is used to analyze the sample data, and based on the selected evaluation indicators and the evaluation model establishes the queuing model of the queuing area and the TOPSIS model of the collection and distribution area. The standard value of the congestion level of various service facilities and the congestion level value of each service facility obtained from the evaluation are used as input to comprehensively evaluate the overall congestion degree of the subway interchange hub. Finally we take the Xi’an Road subway interchange hub in Dalian as empirical research, the data needed for congestion evaluation was obtained through field observations and questionnaires, and the congestion degree of the queue area and the distribution area at different times of the workday was evaluated, and the congestion of each service facility was evaluated. The grade value is used as input, and the TOPSIS method is used to evaluate the degree of congestion in the subway interchange hub, which is consistent with the results of passenger congestion in the questionnaire, which verifies the feasibility of the evaluation model and method.

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