Performance evaluation of NGN reference model for a queuing network

2010 ◽  
Author(s):  
B. K. Mishra ◽  
S. K. Singh
Keyword(s):  
Performance Evaluation ◽  
Reference Model ◽  
Queuing Network

Development of a Hybrid Reference Model for Performance Evaluation of Resolvers

2021 ◽  
Vol 70 ◽  
pp. 1-8
Author(s):  
MohammadSadegh KhajueeZadeh ◽  
Hamid Saneie ◽  
Zahra Nasiri-Gheidari
Keyword(s):  
Performance Evaluation ◽  
Reference Model

Performance Evaluation of MPTCP Incast Based on Queuing Network

2021 ◽  
pp. 1-1
Author(s):  
Jiamin Yao ◽  
Shanchen Pang ◽  
Joel J. P. C. Rodrigues ◽  
Zhihan Lv ◽  
Shuyu Wang
Keyword(s):  
Performance Evaluation ◽  
Queuing Network

scholarly journals Performance Evaluation of Copper and Stainless-steel Electrodes in Electrical Tomographic Imaging

2021 ◽  
Vol 32 (3) ◽  
pp. 13-29
Author(s):  
Adedibu Sunny Akingboye ◽  
◽  
Andy Anderson Bery ◽  
◽  
Keyword(s):  
Stainless Steel ◽  
Performance Evaluation ◽  
Reference Model ◽  
Electrode Spacing ◽  
Percentage Error ◽  
Data Inversion ◽  
Copper Electrodes ◽  
Rms Error ◽  
Conventional Stainless Steel ◽  
Steel Electrodes

Geophysicists use electrical methods to investigate and characterise the earth’s subsurface geology. This study aims to evaluate the performance of copper and conventional stainless-steel electrodes in subsurface tomographic investigations using electrical resistivity tomography (ERT) and induced polarisation (IP) at two sites in Penang, Malaysia. Site 1 and Site 2 employed profile lengths of 200 m and 100 m, with electrodes spacing of 5.0 m and 2.5 m, respectively. In the results of the final data inversion, it was observed that the ERT and IP tomographic models of Site 1 have the best convergence limits with percentage relative differences (copper as reference model) ranging from –70% to 70%, while Site 2 recorded –8% to 8%. The electrodes performance evaluation showed that population root mean square (RMS) error and population mean absolute percentage error (MAPE) of data points between copper and stainless-steel electrodes yielded large values for Site 1 with values above 28% and that of Site 2 was less than 4%. Hence, copper (good electrical conductivity and non-polarisable) electrodes have improved the quality and quantity of infield data which give low values of population RMS error and population MAPE compared to conventional stainless-steel electrodes, especially for large unit electrode spacing surveys. Most notably, this work has contributed to the understanding of the capability of copper electrodes in providing precise and reliable inversion models for subsurface tomographic investigations in pre- and post-land uses (engineering work), hydrogeology/groundwater, environmental studies, etc.

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 Assessment of RISC-V Architecture

2020 ◽  
Vol 8 (6) ◽  
pp. 4576-4581
Keyword(s):  
Performance Evaluation ◽  
Performance Analysis ◽  
Performance Assessment ◽  
Execution Time ◽  
Reference Model ◽  
Simulation Models ◽  
Branch Prediction ◽  
Cache Memory ◽  
Data Cache ◽  
Verification Methodology

This paper presents the performance evaluation of RISC – V architecture based processor using Gem5 simulator. The performance analysis metrics such as bandwidth, latency, throughput, branch prediction, pipeline stages and memory hierarchy of the processor architecture are studied using Gem5 simulator. Different simulation models are carried out to arrive the best reference model for RISC-V architecture design and development. In this reference model cache memory functionality feature is verified with the verification methodology called Universal Verification Methodology (UVM). From simulations it is found that both the program and data cache provides optimum performance in terms of execution time, hit rates, miss rate and miss latencies.

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