Study on the Transmission Data Collection Technique of Network Applications

2012 ◽  
Vol 546-547 ◽  
pp. 1453-1458
Author(s):  
Hai Yan Liu ◽  
Zhao Hong Yang ◽  
Hong Liu Cai
Keyword(s):  
Data Collection ◽  
Large Scale ◽  
Original System ◽  
Application Layer ◽  
Analysis And Evaluation ◽  
Network Applications ◽  
Large Scale Network ◽  
Transmission Data ◽  
Scale Network ◽  
Data Collection Technique

In Large-scale network applications, transmission data collection is the basis for audit, analysis and evaluation of systems and users. Transmission data collection can be carried out either on the link line or on the host where the network application is running. Collecting at different locations, the types of data acquired are different, thus need different processing. This paper first analyzes the different transmission data collection methods, their advantages as well as disadvantages. Then analyzes the structure of those network applications that are basing on transmission dynamic linked library, promotes the intermediate DLL method. Finally through an example it shows how to define the intermediate DLL to collect transferred data on application layer without affecting the original system function.

scholarly journals Using Trellis software to enhance high-quality large-scale network data collection in the field

2021 ◽  
Vol 66 ◽  
pp. 171-184
Author(s):  
Alina Lungeanu ◽  
Mark McKnight ◽  
Rennie Negron ◽  
Wolfgang Munar ◽  
Nicholas A. Christakis ◽  
...  
Keyword(s):  
Data Collection ◽  
Large Scale ◽  
Network Data ◽  
High Quality ◽  
Large Scale Network ◽  
Scale Network

Construction and Calibration of a Large-Scale Microsimulation Model of the Salt Lake Area

1998 ◽  
Vol 1644 (1) ◽  
pp. 93-102 ◽  
Author(s):  
H. Rakha ◽  
M. Van Aerde ◽  
L. Bloomberg ◽  
X. Huang
Keyword(s):  
Data Collection ◽  
Large Scale ◽  
Salt Lake ◽  
Time Frame ◽  
Microscopic Model ◽  
Metropolitan Region ◽  
Sensitivity Analyses ◽  
Lake Area ◽  
Large Scale Network ◽  
Scale Network

The objective of this paper is threefold. First, the feasibility of modeling a large-scale network at a microscopic level of detail is presented. Second, the unique data collection challenges that are involved in constructing and calibrating a large-scale network microscopically are described. Third, the unique opportunities and applications from the use of a microscopic as opposed to a macroscopic simulation tool are described. The possibility and feasibility of modeling a large-scale network using a microscopic simulation model is demonstrated. The requirements of a validated microscopic model for large-scale modeling are: ( a) the model must be capable of modeling origin-destination demand tables, ( b) the model must be capable of modeling dynamic traffic routing, and ( c) the model must be capable of modeling the dynamic interaction of freeway/arterial facilities. The data collection and coding exercise for microscopic models is more intensive than for macroscopic models. The calibration exercise for a microscopic model to a large-scale network, although feasible, is by no means an easy task and does require expert assistance. The Salt Lake metropolitan region study has demonstrated that the data collection, coding, and calibration exercise is approximately a 4-person-year exercise. Model execution times during peak periods are still quite high (from 2 to 17 times the simulation time depending on the number of vehicles) for the PC platform (Pentium 200 with 64 megabytes of random-access memory). Consequently, tools that can extract portions of the large-scale network can allow the modeler to conduct various types of sensitivity analyses within a more realistic time frame.

scholarly journals Generic Framework for the Optimal Implementation of Flexibility Mechanisms in Large-Scale Smart Grids

2021 ◽  
Author(s):  
Alejandro J. del Real ◽  
Andrés Pastor ◽  
Jaime Durán
Keyword(s):  
Smart Grids ◽  
Large Scale ◽  
Mathematical Framework ◽  
Demand And Supply ◽  
Network Applications ◽  
Large Scale Network ◽  
Control Framework ◽  
Scale Network ◽  
The One ◽  
Optimal Implementation

This paper aims to provide the smart grid research community with an open and accessible general mathematical framework to develop and implement optimal flexibility mechanisms in large-scale network applications. The motivation of this paper is twofold. On the one hand, flexibility mechanisms are currently a hot topic of research, which is aimed to mitigate variation and uncertainty of electricity demand and supply in decentralised grids with a high aggregated share of renewables. On the other hand, a large part of such related research is performed by heuristic methods, which are generally inefficient (such methods do not guarantee optimality) and difficult to extrapolate for different use cases. Alternatively, this paper presents an MPC-based (Model Predictive Control) framework explicitly including a generic flexibility mechanism which is easy to particularise to specific strategies such as Demand Response, Flexible Production and Energy Efficiency Services. The proposed framework is benchmarked with other non-optimal control configurations to better show the advantages it provides. The work of this paper is completed by the implementation of a generic use case which aims to further clarify the use of the framework and thus, to ease its adoption by other researchers in their specific flexibility mechanisms applications.

scholarly journals Generic Framework for the Optimal Implementation of Flexibility Mechanisms in Large-Scale Smart Grids

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 8063
Author(s):  
Alejandro J. del Real ◽  
Andrés Pastor ◽  
Jaime Durán
Keyword(s):  
Smart Grids ◽  
Large Scale ◽  
Mathematical Framework ◽  
Demand And Supply ◽  
Network Applications ◽  
Large Scale Network ◽  
Control Framework ◽  
Scale Network ◽  
The One ◽  
Optimal Implementation

This paper aims to provide the smart grid research community with an open and accessible general mathematical framework to develop and implement optimal flexibility mechanisms in large-scale network applications. The motivation of this paper is twofold. On the one hand, flexibility mechanisms are currently a hot topic of research, which is aimed to mitigate variation and uncertainty of electricity demand and supply in decentralised grids with a high aggregated share of renewables. On the other hand, a large part of such related research is performed by heuristic methods, which are generally inefficient (such methods do not guarantee optimality) and difficult to extrapolate for different use cases. Alternatively, this paper presents an MPC-based (model predictive control) framework explicitly including a generic flexibility mechanism, which is easy to particularise to specific strategies such as demand response, flexible production and energy efficiency services. The proposed framework is benchmarked with other non-optimal control configurations to better show the advantages it provides. The work of this paper is completed by the implementation of a generic use case, which aims to further clarify the use of the framework and, thus, to ease its adoption by other researchers in their specific flexibility mechanism applications.

Large-Scale Network Analysis for Online Social Brand Advertising

MIS Quarterly ◽  
2016 ◽  
Vol 40 (4) ◽  
pp. 849-868 ◽  
Author(s):  
Kunpeng Zhang ◽  
◽  
Siddhartha Bhattacharyya ◽  
Sudha Ram ◽  
◽  
...  
Keyword(s):  
Network Analysis ◽  
Large Scale ◽  
Large Scale Network ◽  
Brand Advertising ◽  
Scale Network
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