Network Performance Measurements as Part of Feasibility Studies on Moving an ATLAS Event Filter to Off-Site Institutes

2004 ◽  
pp. 206-213 ◽  
Author(s):  
Krzysztof Korcyl ◽  
Razvan Beuran ◽  
Bob Dobinson ◽  
Mihail Ivanovici ◽  
Marcia Losada Maia ◽  
...  
Keyword(s):  
Network Performance ◽  
Feasibility Studies ◽  
Performance Measurements

scholarly journals Social Distancing and the Internet: What Can Network Performance Measurements Tell Us?

2020 ◽  
Author(s):  
Jessica De Oliveira Moreira ◽  
Amey Pasarkar ◽  
Wenjun Chen ◽  
Wenkai Hu ◽  
Jan Janak ◽  
...  
Keyword(s):  
Network Performance ◽  
The Internet ◽  
Performance Measurements ◽  
Social Distancing

scholarly journals Network performance measurements for NASA’s Earth Observation System

2004 ◽  
Vol 46 (3) ◽  
pp. 299-320 ◽  
Author(s):  
Joe Loiacono ◽  
Andy Germain ◽  
Jeff Smith
Keyword(s):  
Network Performance ◽  
Earth Observation ◽  
Observation System ◽  
Performance Measurements ◽  
Earth Observation System

scholarly journals Towards Sustainable Cities: Utilizing Floating Car Data to Support Location-Based Road Network Performance Measurements

2020 ◽  
Vol 12 (19) ◽  
pp. 8145
Author(s):  
Maximilian Braun ◽  
Jan Kunkler ◽  
Florian Kellner
Keyword(s):  
Traffic Congestion ◽  
Road Network ◽  
Network Performance ◽  
Service Providers ◽  
Traffic Information ◽  
Performance Measurements ◽  
Real World Data ◽  
Network Characteristics ◽  
Navigation Service ◽  
German Cities

Road network performance (RNP) is a key element for urban sustainability as it has a significant impact on economy, environment, and society. Poor RNP can lead to traffic congestion, which can lead to higher transportation costs, more pollution and health issues regarding the urban population. To evaluate the effects of the RNP, the involved stakeholders need a real-world data base to work with. This paper develops a data collection approach to enable location-based RNP analysis using publicly available traffic information. Therefore, we use reachable range requests implemented by navigation service providers to retrieve travel times, travel speeds, and traffic conditions. To demonstrate the practicability of the proposed methodology, a comparison of four German cities is made, considering the network characteristics with respect to detours, infrastructure, and traffic congestion. The results are combined with cost rates to compare the economical dimension of sustainability of the chosen cities. Our results show that digitization eases the assessment of traffic data and that a combination of several indicators must be considered depending on the relevant sustainability dimension decisions are made from.

scholarly journals Estimating Spectral Efficiency Curves from Connection Traces in a Live LTE Network

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Matías Toril ◽  
Rocío Acedo-Hernández ◽  
Almudena Sánchez ◽  
Salvador Luna-Ramírez ◽  
Carlos Úbeda
Keyword(s):  
Spectral Efficiency ◽  
Network Performance ◽  
Base Stations ◽  
Performance Measurements ◽  
Large Dataset ◽  
Multiple Factors ◽  
Term Evolution ◽  
Commercial Network ◽  
Key Parameter

In cellular networks, spectral efficiency is a key parameter when designing network infrastructure. Despite the existence of theoretical model for this parameter, experience shows that real spectral efficiency is influenced by multiple factors that greatly vary in space and time and are difficult to characterize. In this paper, an automatic method for deriving the real spectral efficiency curves of a Long Term Evolution (LTE) system on a per-cell basis is proposed. The method is based on a trace processing tool that makes the most of the detailed network performance measurements collected by base stations. The method is conceived as a centralized scheme that can be integrated in commercial network planning tools. Method assessment is carried out with a large dataset of connection traces taken from a live LTE system. Results show that spectral efficiency curves largely differ from cell to cell.

scholarly journals Optimising Self-Similarity Network Traffic for Better Performance

2020 ◽  
pp. 164-176
Author(s):  
Ikharo A. B. ◽  
Anyachebelu K. T. ◽  
Blamah N. V. ◽  
Abanihi V. K.
Keyword(s):  
Network Traffic ◽  
Network Performance ◽  
Computer Network ◽  
Ann Model ◽  
Performance Measurements ◽  
Self Similarity ◽  
Traffic Modelling ◽  
Backpropagation Network ◽  
Self Similar

Given the ubiquity of the burstiness present across many networking facilities and services, predicting and managing self-similar traffic has become a key issue owing to new complexities associated with self-similarity which makes difficult the achievement of high network performance and quality of service (QoS). In this study ANN model was used to model and simulate FCE Okene computer network traffic. The ANN is a 2-39-1 Feed Forward Backpropagation network implemented to predict the bursty nature of network traffic. Wireshark tools that measure and capture packets of network traffic was deployed. Moreover, variance-time method is a log-log scale plot, representing variance versus a non-overlapping block of size m aggregate variance level engaged to established conformity of the ANN approach to self-similarity characteristic of the network traffic. The predicted series were then compared with the corresponding real traffic series. Suitable performance measurements used were the Means Square Error (MSE) and the Regression Coefficient. Our results showed that burstiness is present in the network across many time scales. The study also established the characteristic property of a long-range dependence (LRD). The work recommended that network traffic observation should be longer thereby enabling larger volume of traffic to be capture for better accuracy of traffic modelling and prediction.

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