Queuing Network Performance Model for Evaluation of CMP-Based VoIP SPS

2008 ◽  
Author(s):  
Jiuzhen Jin ◽  
Jianmin Pang ◽  
Zheng Shan ◽  
Rongcai Zhao
Keyword(s):  
Network Performance ◽  
Performance Model ◽  
Queuing Network

Multi-physics circuit network performance model for CPV modules/systems

2011 ◽  
Author(s):  
Etienne Menard ◽  
Wolfgang Wagner ◽  
Bruce Furman ◽  
Kanchan Ghosal ◽  
John Gabriel ◽  
...  
Keyword(s):  
Network Performance ◽  
Performance Model

An analytical network performance model for SIMD processor CSX600 interconnects

2011 ◽  
Vol 57 (1) ◽  
pp. 146-159
Author(s):  
Yuri Nishikawa ◽  
Michihiro Koibuchi ◽  
Masato Yoshimi ◽  
Kenichi Miura ◽  
Hideharu Amano
Keyword(s):  
Network Performance ◽  
Performance Model

scholarly journals Capacity-Constrained Network Performance Model for Urban Rail Systems

2020 ◽  
Vol 2674 (5) ◽  
pp. 59-69 ◽  
Author(s):  
Baichuan Mo ◽  
Zhenliang Ma ◽  
Haris N. Koutsopoulos ◽  
Jinhua Zhao
Keyword(s):  
Smart Card ◽  
Network Performance ◽  
Performance Monitoring ◽  
Optimization Method ◽  
Performance Model ◽  
Railway Network ◽  
Rail Systems ◽  
Smart Card Data ◽  
Urban Rail ◽  
General Network

This paper proposes a general network performance model (NPM) for monitoring the performance of urban rail systems using smart card data. NPM is a schedule-based network loading model with strict capacity constraints and boarding priorities. It distributes passengers over the network given origin-destination demand, operations, route choice, and effective train capacity. A Bayesian simulation-based optimization method for calibrating the effective train capacity is introduced, which explicitly recognizes that capacity may be different at different stations depending on congestion levels. Case studies with data from the Mass Transit Railway network in Hong Kong are used to validate the model and illustrate its applicability. NPM is validated using survey data on left-behind passengers and exiting passenger flow extracted from smart card data. The use of NPM for performance monitoring is demonstrated by analyzing the spatial-temporal crowding patterns in the system and evaluating dispatching strategies.

A PERFORMANCE MODEL OF DISHA ROUTING IN K-ARY N-CUBE NETWORKS

2007 ◽  
Vol 17 (02) ◽  
pp. 213-228 ◽  
Author(s):  
A. KHONSARI ◽  
A. SHAHRABI ◽  
M. OULD-KHAOUA
Keyword(s):  
Network Performance ◽  
Routing Algorithm ◽  
Adaptive Routing ◽  
Routing Algorithms ◽  
Performance Model ◽  
Analytical Models ◽  
Traffic Conditions ◽  
Proposed Model ◽  
Fully Adaptive ◽  
Wormhole Routed

A number of analytical models for predicting message latency in k-ary n-cubes have recently been reported in the literature. Most of these models, however, have been discussed for adaptive routing algorithms based on deadlock avoidance, e.g. Duato's routing. Several research studies have empirically demonstrated that routing algorithms based on deadlock recovery offer maximal adaptivity that can result in considerable improvement in network performance. Disha is an example of a true fully adaptive routing algorithm that uses minimal hardware to implement a simple and efficient progressive method to recover from potential deadlocks. This paper proposes a new analytical model of Disha in wormhole-routed k-ary n-cubes. Simulation experiments confirm that the proposed model exhibits a good degree of accuracy for various networks sizes and under different traffic conditions.

scholarly journals Performance Evaluation of Message Routing Strategies in the Internet of Robotic Things Using the D/M/c/K/FCFS Queuing Network

Electronics ◽  
2021 ◽  
Vol 10 (21) ◽  
pp. 2626
Author(s):  
Leonel Feitosa ◽  
Glauber Gonçalves ◽  
Tuan Anh Nguyen ◽  
Jae Woo Lee ◽  
Francisco Airton Silva
Keyword(s):  
Performance Evaluation ◽  
System Performance ◽  
Performance Metrics ◽  
Performance Model ◽  
Edge Computing ◽  
Evaluation Methodology ◽  
The Internet ◽  
Queuing Network ◽  
System Components ◽  
The Impact

The Internet of Robotic Things (IoRT) has emerged as a promising computing paradigm integrating the cloud/fog/edge computing continuum in the Internet of Things (IoT) to optimize the operations of intelligent robotic agents in factories. A single robot agent at the edge of the network can comprise hundreds of sensors and actuators; thus, the tasks performed by multiple agents can be computationally expensive, which are often possible by offloading the computing tasks to the distant computing resources in the cloud or fog computing layers. In this context, it is of paramount importance to assimilate the performance impact of different system components and parameters in an IoRT infrastructure to provide IoRT system designers with tools to assess the performance of their manufacturing projects at different stages of development. Therefore, we propose in this article a performance evaluation methodology based on the D/M/c/K/FCFS queuing network pattern and present a queuing-network-based performance model for the performance assessment of compatible IoRT systems associated with the edge, fog, and cloud computing paradigms. To find the factors that expose the highest impact on the system performance in practical scenarios, a sensitivity analysis using the Design of Experiments (DoE) was performed on the proposed performance model. On the outputs obtained by the DoE, comprehensive performance analyses were conducted to assimilate the impact of different routing strategies and the variation in the capacity of the system components. The analysis results indicated that the proposed model enables the evaluation of how different configurations of the components of the IoRT architecture impact the system performance through different performance metrics of interest including the (i) mean response time, (ii) utilization of components, (iii) number of messages, and (iv) drop rate. This study can help improve the operation and management of IoRT infrastructures associated with the cloud/fog/edge computing continuum in practice.

scholarly journals Performance Model for Factory Automation in 5G Networks

2021 ◽  
Author(s):  
jiao wang ◽  
Jay Weitzen ◽  
Oguz Bayat ◽  
Volkan Sevindik ◽  
Mingzhe Li
Keyword(s):  
Mobile Networks ◽  
Data Exchange ◽  
Network Performance ◽  
Access Network ◽  
Service Level Agreement ◽  
Service Level ◽  
Performance Model ◽  
Factory Automation ◽  
Public Network ◽  
Radio Access

Abstract The fifth generation (5G) of mobile networks is emerging as a key enabler of modern factory automation (FA) applications that ensure timely and reliable data exchange between network components. Network slicing (NS), which shares an underlying infrastructure with different applications and ensures application isolation, is the key 5G technology to support the diverse quality of service requirements of modern FA applications. In this article, an end-to-end NS solution is proposed for FA applications in a 5G network. Regression approaches are used to construct a performance model for each slice to map the service level agreement to the network attributes. Interference coordination approaches for switched beam systems are proposed to optimize radio access network performance models. A case study of a non-public network is used to show the proposed NS approach.

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