scholarly journals Challenges for obtaining a system-optimal traffic distribution by giving route advice due to the biased memory of congestion

2021 ◽  
Vol 52 ◽  
pp. 396-403
Author(s):  
Susanne Grüner ◽  
Mark Vollrath
Keyword(s):  
Traffic Distribution ◽  
System Optimal

Design and Simulation of Smart Control System for Internet Traffic Distribution on Servers by Using Fuzzy Logic System

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Raid Daoud ◽  
Yaareb Al-Khashab
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Input Parameter ◽  
Traffic Density ◽  
The Internet ◽  
Linguistic Variables ◽  
Internet Service ◽  
Traffic Distribution ◽  
Smart Control ◽  
High Level

The internet service is provided by a given number of servers located in the main node of internet service provider (ISP). In some cases; the overload problem was occurred because a demand on a given website goes to very high level. In this paper, a fuzzy logic control (FLC) has proposed to distribute the load into the internet servers by a smart and flexible manner. Three effected parameters are tacked into account as input for FLC: link capacity which has three linguistic variables with Gaussian membership function (MF): (small, medium and big), traffic density with linguistic variables (low, normal and high) and channel latency with linguistic variables (empty, half and full); with one output which is the share server status (single, simple and share). The proposed work has been simulated by using MATLAB 2016a, by building a structure in the Fuzzy toolbox. The results were fixed by two manners: the graphical curves and the numerical tables, the surface response was smoothly changed and translates the well-fixed control system. The numerical results of the control system satisfy the idea of the smart rout for the incoming traffics from the users to internet servers. So, the response of the proposed system for the share of server ratio is 0.122, when the input parameter in the smallest levels; and the ratio is 0.879 when the input parameters are in highest level. The smart work and flexible use for the FLC is the main success solution for most of today systems control.

Algorithms of Mobile Traffic Distribution Forecasting Based on Simulated Annealing

2011 ◽  
Vol 30 (9) ◽  
pp. 2225-2228
Author(s):  
Juan-juan Sun ◽  
Zong-pan Huang ◽  
Da-cheng Yang
Keyword(s):  
Simulated Annealing ◽  
Traffic Distribution

scholarly journals Semi-Continuous Spatial Statistical Analysis Using AIS Data for Vessel Traffic Flow Characteristics in Fairway

2021 ◽  
Vol 9 (4) ◽  
pp. 378
Author(s):  
Jong Kwan Kim
Keyword(s):  
Statistical Analysis ◽  
Traffic Flow ◽  
Flow Characteristics ◽  
Automatic Identification ◽  
Identification System ◽  
Spatial Statistical Analysis ◽  
Traffic Characteristics ◽  
Traffic Distribution ◽  
Traffic Flow Characteristics ◽  
Marine Accidents

As high vessel traffic in fairways is likely to cause frequent marine accidents, understanding vessel traffic flow characteristics is necessary to prevent marine accidents in fairways. Therefore, this study conducted semi-continuous spatial statistical analysis tests (the normal distribution test, kurtosis test and skewness test) to understand vessel traffic flow characteristics. First, a vessel traffic survey was conducted in a designated area (Busan North Port) for seven days. The data were collected using an automatic identification system and subsequently converted using semi-continuous processing methods. Thereafter, the converted data were used to conduct three methods of spatial statistical analysis. The analysis results revealed the vessel traffic distribution and its characteristics, such as the degree of use and lateral positioning on the fairway based on the size of the vessel. In addition, the generalization of the results of this study along with that of further studies will aid in deriving the traffic characteristics of vessels on the fairway. Moreover, these characteristics will reduce maritime accidents on the fairway, in addition to establishing the foundation for research on autonomous ships.

Where are you taking me?Understanding Abusive Traffic Distribution Systems

2021 ◽  
Author(s):  
Janos Szurdi ◽  
Meng Luo ◽  
Brian Kondracki ◽  
Nick Nikiforakis ◽  
Nicolas Christin
Keyword(s):  
Distribution Systems ◽  
Traffic Distribution

scholarly journals System-Optimal Routing of Traffic Flows with User Constraints in Networks with Congestion

2005 ◽  
Vol 53 (4) ◽  
pp. 600-616 ◽  
Author(s):  
Olaf Jahn ◽  
Rolf H. Möhring ◽  
Andreas S. Schulz ◽  
Nicolás E. Stier-Moses
Keyword(s):  
Optimal Routing ◽  
Traffic Flows ◽  
System Optimal

scholarly journals Iterative LP water system optimal operation including headloss, leakage, total head and source cost

2013 ◽  
Vol 15 (4) ◽  
pp. 1203-1223 ◽  
Author(s):  
Eyal Price ◽  
Avi Ostfeld
Keyword(s):  
Energy Consumption ◽  
Water System ◽  
Pump Energy ◽  
Optimal Operation ◽  
Water Levels ◽  
Water Leakage ◽  
Pump Operation ◽  
Total Head ◽  
System Optimal ◽  
Water Tanks

Linear water balance optimal operation models are common with relative short solution times but suffer from a lack of certainty whether the given solution is at all hydraulically feasible. Introducing hydraulic headloss, water leakage and changing pump energy consumption, effect the resulting system optimal operation but also create a non-linear problem due to the convex relation between flow, headloss, water leakage and total head. This study utilizes a methodology published by the authors for linearization of convex or concave equations. An iterative linear programming (LP) minimal cost optimal operation supply model is solved including the Hazen–Williams headloss equation, pressure related water leakage equation, changing pump energy consumption and source cost. The model is demonstrated using an example application. ‘Greater than’ or ‘less than’ water head constraints at nodes may force the system to maintain certain water levels in water tanks reducing the available operating volume forcing pumping stations to operate in peak tariff periods as less storage is available in low tariff periods. Operationally, reducing water leakage may be achieved by reducing water heads along the system by means of shifting pump operation periods and maintaining low water levels in water tanks. Source costs may serve as penalties or rewards discouraging or encouraging the use of certain water sources.

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