Online Simulation System for Cellular Core Network Performance Measurement

2017 ◽  
Vol 42 (12) ◽  
pp. 2307-2310
Author(s):  
Fery Andrian Kusuma ◽  
Kae Won Choi
Keyword(s):  
Performance Measurement ◽  
Network Performance ◽  
Simulation System ◽  
Core Network ◽  
Online Simulation

Design and Realization of Mine Water-Inrush Visualization Simulation System

2011 ◽  
Vol 383-390 ◽  
pp. 6632-6640 ◽  
Author(s):  
Yao Dong Zhou ◽  
Zhong Xue Li ◽  
Cui Ping Li ◽  
Zhi Guo Cao
Keyword(s):  
Mine Water ◽  
General Structure ◽  
Water Inrush ◽  
Processing System ◽  
Monitoring Network ◽  
Virtual Water ◽  
Original Data ◽  
Simulation System ◽  
Core Network ◽  
Mining Safety

There exists a high risk of water-inrush in mining activities. Therefore, it is critical to develop a conceptual model of Mine Water-inrush, especially for the underground environment. The general structure of Mine Water-inrush Simulation System consists of core network, the underground monitoring network, and the operational system. Through the application of data processing system, simulation system and the application system, the original data can be processed. The results is then passed to the operators and managers, which require them increase the understanding of factors leading to accidents and consequently take action to improve mining safety. This new water-inrush model captures three characteristics to regard the mine water-inrush: the inrush sources, inrush process, and submerging process. Virtual length has been applied to the model, which is combined with a Traversal Algorithm, can be used to calculate the area of increased influence over time for each process. Based on the collected data from a real mine, the underground excavations and a virtual water-inrush disaster process were simulated, which shows that the system operates reliably.

scholarly journals A Node-Regulated Deflection Routing Framework for Contention Minimization

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Bakhe Nleya ◽  
Andrew Mutsvangwa
Keyword(s):  
Wavelength Division Multiplexing ◽  
Network Performance ◽  
Cost Effective ◽  
Core Network ◽  
Network Resources ◽  
Deflection Routing ◽  
Wavelength Division ◽  
Backbone Networks ◽  
Candidate Solution ◽  
Data Burst

Optical Burst Switching (OBS) paradigm coupled with Dense Wavelength Division Multiplexing (DWDM) has become a practical candidate solution for the next-generation optical backbone networks. In its practical deployment only the edge nodes are provisioned with buffering capabilities, whereas all interior (core) nodes remain buffer-less. In that way the implementation becomes quite simple as well as cost effective as there will be no need for optical buffers in the interior. However, the buffer-less nature of the interior nodes makes such networks prone to data burst contention occurrences that lead to a degradation in overall network performance as a result of sporadic heavy burst losses. Such drawbacks can be partly countered by appropriately dimensioning available network resources and reactively by way of deflecting excess as well as contending data bursts to available least-cost alternate paths. However, the deflected data bursts (traffic) must not cause network performance degradations in the deflection routes. Because minimizing contention occurrences is key to provisioning a consistent Quality of Service (QoS), we therefore in this paper propose and analyze a framework (scheme) that seeks to intelligently deflect traffic in the core network such that QoS degradations caused by contention occurrences are minimized. This is by way of regulated deflection routing (rDr) in which neural network agents are utilized in reinforcing the deflection route choices at core nodes. The framework primarily relies on both reactive and proactive regulated deflection routing approaches in order to prevent or resolve data burst contentions. Simulation results show that the scheme does effectively improve overall network performance when compared with existing contention resolution approaches. Notably, the scheme minimizes burst losses, end-to-end delays, frequency of contention occurrences, and burst deflections.

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