Increasing Energy-Efficient Driving Using Uncertain Online Data of Local Traffic Management Centers

2017 ◽  
pp. 61-71
Author(s):  
Per Lewerenz ◽  
Günther Prokop
Keyword(s):  
Energy Efficient ◽  
Traffic Management ◽  
Online Data

Information-Oriented Traffic Management for Energy-Efficient and Loss-Resilient IoT Systems

2021 ◽  
pp. 1-1
Author(s):  
Abdallah Jarwan ◽  
Ayman Sabbah ◽  
Mohamed Ibnkahla
Keyword(s):  
Energy Efficient ◽  
Traffic Management

The Need for Traffic Based Virtualisation Management for Sustainable Clouds

2015 ◽  
Vol 5 (4) ◽  
pp. 8-19
Author(s):  
Kiran Voderhobli
Keyword(s):  
Cloud Computing ◽  
Energy Efficient ◽  
Traffic Management ◽  
Local Level ◽  
Work Load ◽  
Local Network ◽  
Energy Crisis ◽  
Power Efficient ◽  
Site Network ◽  
Data Centres

The subscription based model of cloud computing has allowed for users to migrate their processes to off-site network facilities. One of the motivations for deployment of cloud based services is to promote sustainability by reducing green-house emissions at a local level. Although some might argue that this model saves a lot of power at local network facilities, the problem of energy crisis caused by ICT is never-ending. Today, data-centres are bee-hives of exascale computing and high network dependant processing. Work-load on the cloud directly contributes to energy consumption to an extent that currently IT clouds are some of the worst contributors to CO2 emissions. This paper discusses why traffic-management on the cloud is vital to make it more power efficient and how it can be achieved by gathering live network statistics. The discussion fits with the context of “emerging clouds” as thought needs to be given on how to apply energy efficient schemes at various points including at the communication level.

scholarly journals Intelligent centralized traffic management of a rapid transit system under heavy traffic

Dependability ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 17-23
Author(s):  
L. A. Baranov ◽  
V. G. Sidorenko ◽  
E. P. Balakina ◽  
L. N. Loginova
Keyword(s):  
Genetic Algorithms ◽  
Energy Consumption ◽  
Control Theory ◽  
Traffic Safety ◽  
Energy Efficient ◽  
Traffic Management ◽  
Design Principles ◽  
Rapid Transit ◽  
Traffic Planning ◽  
Transit System

Aim. In today’s major cities, increased utilization and capacity of the rapid transit systems (metro, light rail, commuter trains with stops within the city limits) – under condi[1]tions of positive traffic safety – is achieved through smart automatic train traffic management. The aim of this paper is to choose and substantiate the design principles and architecture of such system.Methods. Using systems analysis, the design principles and architecture of the system are substantiated. Genetic algorithms allow automating train traffic planning. Methods of the optimal control theory allow managing energy-efficient train movement patterns along open lines, assigning individual station-to-station running times following the principle of mini[1]mal energy consumption, developing energy-efficient target traffic schedules. Methods of the automatic control theory are used for selecting and substantiating the train traffic algorithms at various functional levels, for constructing random disturbance extrapolators that minimize the number of train stops between stations.Results. Development and substantiation of the design principles and architecture of a centralized intelligent hierarchical system for automatic rapid transit traffic management. The distribution of functions between the hierarchy levels is described, the set of subsystems is shown that implement the purpose of management, i.e., ensuring traffic safety and comfort of passengers. The criteria are defined and substantiated of management quality under compensated and non-compensated disturbances. Traffic management and target scheduling automation algorithms are examined. The application of decision algorithms is demonstrated in the context of uncertainty, use of disturbance prediction and genetic algorithms for the purpose of train traffic planning automation. The design principles of the algorithms of traffic planning and management are shown that ensure reduced traction energy consumption. The efficiency of centralized intelligent rapid transit management system is demonstrated; the fundamental role of the system in the digitalization of the transport system is noted.Conclusion. The examined design principles and operating algorithms of a centralized intelligent rapid transit management system showed the efficiency of such systems that ensured by the following: increased capacity of the rapid transit system; improved energy efficiency of train traffic planning and management; improved train traffic safety; assurance of operational traffic management during emergencies and major traffic disruptions; improved passenger comfort.

scholarly journals Connectivity and Automation as Enablers for Energy-Efficient Driving and Road Traffic Management

2021 ◽  
pp. 1-40
Author(s):  
Bassel Othman ◽  
Giovanni De Nunzio ◽  
Antonio Sciarretta ◽  
Domenico Di Domenico ◽  
Carlos Canudas-de-Wit
Keyword(s):  
Energy Efficient ◽  
Traffic Management ◽  
Road Traffic

scholarly journals COMPACT ENERGY EFFICIENT ONLINE DATA LOGGER FOR REAL TIME GEOMAGNETIC MEASUREMENTS

2018 ◽  
Vol 28 (3) ◽  
pp. 05-13
Author(s):  
I. M. Aleshin ◽  
◽  
V. G. Getmanov ◽  
A. A. Grudnev ◽  
M. N. Dobrovolsky ◽  
...  
Keyword(s):  
Real Time ◽  
Energy Efficient ◽  
Data Logger ◽  
Online Data ◽  
Geomagnetic Measurements
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