Results 291 to 300 of about 19,754,425 (354)

Network performance evaluation

2018
In order to validate the effectiveness of a network design, its performance needs to be evaluated. In general, there are three approaches to evaluate the network performance, including benchmarking, simulation, and analytical modeling. In this chapter, the author will sequentially discuss these three approaches along with their merits and demerits as ...
Quoc-Tuan Vien
openaire   +2 more sources

SRCON: A Data-Driven Network Performance Simulator for Real-World Wireless Networks

IEEE Communications Magazine, 2023
Optimizing the performance of a real-world wireless network is extremely challenging because of the difficulty to predict the network performance as a function of network parameters, and the prohibitively large problem size.
Z. Luo   +8 more
semanticscholar   +1 more source

Measuring the network performance of Google cloud platform

ACM/SIGCOMM Internet Measurement Conference, 2021
Public cloud platforms are vital in supporting online applications for remote learning and telecommuting during the COVID-19 pandemic. The network performance between cloud regions and access networks directly impacts application performance and users ...
Ricky K. P. Mok   +5 more
semanticscholar   +1 more source

The Impact of Selfish Mining on Bitcoin Network Performance

IEEE Transactions on Network Science and Engineering, 2021
Selfish mining strategy allows miners to gain unfair advantage and excess revenue in Bitcoin network, but it also disrupts the normal operation of the network.
S. G. Motlagh, J. Misic, V. Mišić
semanticscholar   +1 more source

LSTM and GRU Neural Network Performance Comparison Study: Taking Yelp Review Dataset as an Example

2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI), 2020
Long short-term memory networks(LSTM) and gate recurrent unit networks(GRU) are two popular variants of recurrent neural networks(RNN) with long-term memory. This study compares the performance differences of these two deep learning models, involving two
Shudong Yang, Xueying Yu, Ying Zhou
semanticscholar   +1 more source

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