The Experts below are selected from a list of 903 Experts worldwide ranked by ideXlab platform

Geir Hasle - One of the best experts on this subject based on the ideXlab platform.

  • Anticipating emission-sensitive Traffic management strategies for dynamic delivery routing
    Transportation Research Part D: Transport and Environment, 2018
    Co-Authors: Felix Köster, Marlin W. Ulmer, Dirk C. Mattfeld, Geir Hasle
    Abstract:

    Abstract Traffic pollution is an increasing challenge for cities. Emissions such as nitrogen dioxides pose a major health threat to the city’s inhabitants. These emissions often accumulate to critical levels in local areas of the city. To react to these critical emission levels, cities start implementing dynamic Traffic management systems (TMS). These systems dynamically Redirect Traffic flows away from critical areas. These measures impact the travel speeds within the city. This is of particular importance for parcel delivery companies. These companies deliver goods to customers in the city. To avoid long delivery times and higher costs, companies already adapt their routing with respect to changing Traffic conditions. Still, a communication with the TMS may allow anticipatory planning to avoid potentially critical areas in the city. In this paper, we show how communication between TMS and delivery companies results in benefits for both parties. To exploit the provided information, we develop a dynamic routing policy anticipating potential future measures of the TMS. We analyze our algorithm in a comprehensive case study for the TMS of the city of Braunschweig, Germany, a city often used as reference for a typical European city layout. We show that for the delivery company, integrating the TMS’ information in their routing algorithms reduces the driving times significantly. For the TMS, providing the information results in less Traffic in the polluted areas.

Lu Liu - One of the best experts on this subject based on the ideXlab platform.

  • An Efficient SDN Load Balancing Scheme Based on Variance Analysis for Massive Mobile Users
    Hindawi Limited, 2015
    Co-Authors: Hong Zhong, Qunfeng Lin, Jie Cui, Runhua Shi, Lu Liu
    Abstract:

    In a traditional network, server load balancing is used to satisfy the demand for high data volumes. The technique requires large capital investment while offering poor scalability and flexibility, which difficultly supports highly dynamic workload demands from massive mobile users. To solve these problems, this paper analyses the principle of software-defined networking (SDN) and presents a new probabilistic method of load balancing based on variance analysis. The method can be used to dynamically manage Traffic flows for supporting massive mobile users in SDN networks. The paper proposes a solution using the OpenFlow virtual switching technology instead of the traditional hardware switching technology. A SDN controller monitors data Traffic of each port by means of variance analysis and provides a probability-based selection algorithm to Redirect Traffic dynamically with the OpenFlow technology. Compared with the existing load balancing methods which were designed to support traditional networks, this solution has lower cost, higher reliability, and greater scalability which satisfy the needs of mobile users

  • An Efficient SDN load balancing scheme based on variance analysis for massive mobile users
    'Hindawi Limited', 2015
    Co-Authors: Zhong Hong, Lin Qunfeng, Cui Jie, Shi Runhua, Lu Liu
    Abstract:

    In a traditional network, server load balancing is used to satisfy the demand for high data volumes. The technique requires large capital investment while offering poor scalability and flexibility, which difficultly supports highly dynamic workload demands from massive mobile users. To solve these problems, this paper analyses the principle of software-defined networking (SDN) and presents a new probabilistic method of load balancing based on variance analysis. The method can be used to dynamically manage Traffic flows for supporting massive mobile users in SDN networks. The paper proposes a solution using the OpenFlow virtual switching technology instead of the traditional hardware switching technology. A SDN controller monitors data Traffic of each port by means of variance analysis and provides a probability-based selection algorithm to Redirect Traffic dynamically with the OpenFlow technology. Compared with the existing load balancing methods which were designed to support traditional networks, this solution has lower cost, higher reliability, and greater scalability which satisfy the needs of mobile users.The work was supported by the National Natural Science Foundation of China (no. 61173188, no. 61572001, and no. 61502008), the Research Fund for the Doctoral Program of Higher Education (no. 20133401110004), the Educational Commission of Anhui Province, China (no. KJ2013A017), the Natural Science Foundation of Anhui Province (no. 1508085QF132), the Tender Project of the Co-Innovation Center for Information Supply & Assurance Technology of Anhui University (no. ADXXBZ2014-7), and the Doctoral Research Startup Funds Project of Anhui University

Felix Köster - One of the best experts on this subject based on the ideXlab platform.

  • Anticipating emission-sensitive Traffic management strategies for dynamic delivery routing
    Transportation Research Part D: Transport and Environment, 2018
    Co-Authors: Felix Köster, Marlin W. Ulmer, Dirk C. Mattfeld, Geir Hasle
    Abstract:

    Abstract Traffic pollution is an increasing challenge for cities. Emissions such as nitrogen dioxides pose a major health threat to the city’s inhabitants. These emissions often accumulate to critical levels in local areas of the city. To react to these critical emission levels, cities start implementing dynamic Traffic management systems (TMS). These systems dynamically Redirect Traffic flows away from critical areas. These measures impact the travel speeds within the city. This is of particular importance for parcel delivery companies. These companies deliver goods to customers in the city. To avoid long delivery times and higher costs, companies already adapt their routing with respect to changing Traffic conditions. Still, a communication with the TMS may allow anticipatory planning to avoid potentially critical areas in the city. In this paper, we show how communication between TMS and delivery companies results in benefits for both parties. To exploit the provided information, we develop a dynamic routing policy anticipating potential future measures of the TMS. We analyze our algorithm in a comprehensive case study for the TMS of the city of Braunschweig, Germany, a city often used as reference for a typical European city layout. We show that for the delivery company, integrating the TMS’ information in their routing algorithms reduces the driving times significantly. For the TMS, providing the information results in less Traffic in the polluted areas.

Dirk C. Mattfeld - One of the best experts on this subject based on the ideXlab platform.

  • Anticipating emission-sensitive Traffic management strategies for dynamic delivery routing
    Transportation Research Part D: Transport and Environment, 2018
    Co-Authors: Felix Köster, Marlin W. Ulmer, Dirk C. Mattfeld, Geir Hasle
    Abstract:

    Abstract Traffic pollution is an increasing challenge for cities. Emissions such as nitrogen dioxides pose a major health threat to the city’s inhabitants. These emissions often accumulate to critical levels in local areas of the city. To react to these critical emission levels, cities start implementing dynamic Traffic management systems (TMS). These systems dynamically Redirect Traffic flows away from critical areas. These measures impact the travel speeds within the city. This is of particular importance for parcel delivery companies. These companies deliver goods to customers in the city. To avoid long delivery times and higher costs, companies already adapt their routing with respect to changing Traffic conditions. Still, a communication with the TMS may allow anticipatory planning to avoid potentially critical areas in the city. In this paper, we show how communication between TMS and delivery companies results in benefits for both parties. To exploit the provided information, we develop a dynamic routing policy anticipating potential future measures of the TMS. We analyze our algorithm in a comprehensive case study for the TMS of the city of Braunschweig, Germany, a city often used as reference for a typical European city layout. We show that for the delivery company, integrating the TMS’ information in their routing algorithms reduces the driving times significantly. For the TMS, providing the information results in less Traffic in the polluted areas.

Marlin W. Ulmer - One of the best experts on this subject based on the ideXlab platform.

  • Anticipating emission-sensitive Traffic management strategies for dynamic delivery routing
    Transportation Research Part D: Transport and Environment, 2018
    Co-Authors: Felix Köster, Marlin W. Ulmer, Dirk C. Mattfeld, Geir Hasle
    Abstract:

    Abstract Traffic pollution is an increasing challenge for cities. Emissions such as nitrogen dioxides pose a major health threat to the city’s inhabitants. These emissions often accumulate to critical levels in local areas of the city. To react to these critical emission levels, cities start implementing dynamic Traffic management systems (TMS). These systems dynamically Redirect Traffic flows away from critical areas. These measures impact the travel speeds within the city. This is of particular importance for parcel delivery companies. These companies deliver goods to customers in the city. To avoid long delivery times and higher costs, companies already adapt their routing with respect to changing Traffic conditions. Still, a communication with the TMS may allow anticipatory planning to avoid potentially critical areas in the city. In this paper, we show how communication between TMS and delivery companies results in benefits for both parties. To exploit the provided information, we develop a dynamic routing policy anticipating potential future measures of the TMS. We analyze our algorithm in a comprehensive case study for the TMS of the city of Braunschweig, Germany, a city often used as reference for a typical European city layout. We show that for the delivery company, integrating the TMS’ information in their routing algorithms reduces the driving times significantly. For the TMS, providing the information results in less Traffic in the polluted areas.