The Experts below are selected from a list of 69 Experts worldwide ranked by ideXlab platform

Wu Chou - One of the best experts on this subject based on the ideXlab platform.

  • research challenges for traffic engineering in software defined Networks
    IEEE Network, 2016
    Co-Authors: Ian F Akyildiz, Pu Wang, Wu Chou
    Abstract:

    SDN is an emerging Networking paradigm that separates the Network control plane from the data forwarding plane with the promise to dramatically improve Network resource utilization, simplify Network management, reduce operating costs, and promote innovation and evolution. While traffic engineering techniques have been widely exploited for ATM and IP/MPLS Networks for performance optimization in the past, the promising SDN Networks require novel traffic engineering solutions that can exploit the Global Network View, Network status, and flow patterns/characteristics in order to achieve better traffic control and management. This article discusses the state-of-the-art in traffic engineering for SDN with attention to four cores including flow management, fault tolerance, topology update, and traffic analysis. Challenging issues for SDN traffic engineering solutions are discussed in detail.

  • a roadmap for traffic engineering in sdn openflow Networks
    Computer Networks, 2014
    Co-Authors: Ian F Akyildiz, Pu Wang, Wu Chou
    Abstract:

    Software Defined Networking (SDN) is an emerging Networking paradigm that separates the Network control plane from the data forwarding plane with the promise to dramatically improve Network resource utilization, simplify Network management, reduce operating cost, and promote innovation and evolution. Although traffic engineering techniques have been widely exploited in the past and current data Networks, such as ATM Networks and IP/MPLS Networks, to optimize the performance of communication Networks by dynamically analyzing, predicting, and regulating the behavior of the transmitted data, the unique features of SDN require new traffic engineering techniques that exploit the Global Network View, status, and flow patterns/characteristics available for better traffic control and management. This paper surveys the state-of-the-art in traffic engineering for SDNs, and mainly focuses on four thrusts including flow management, fault tolerance, topology update, and traffic analysis/characterization. In addition, some existing and representative traffic engineering tools from both industry and academia are explained. Moreover, open research issues for the realization of SDN traffic engineering solutions are discussed in detail.

Ian F Akyildiz - One of the best experts on this subject based on the ideXlab platform.

  • research challenges for traffic engineering in software defined Networks
    IEEE Network, 2016
    Co-Authors: Ian F Akyildiz, Pu Wang, Wu Chou
    Abstract:

    SDN is an emerging Networking paradigm that separates the Network control plane from the data forwarding plane with the promise to dramatically improve Network resource utilization, simplify Network management, reduce operating costs, and promote innovation and evolution. While traffic engineering techniques have been widely exploited for ATM and IP/MPLS Networks for performance optimization in the past, the promising SDN Networks require novel traffic engineering solutions that can exploit the Global Network View, Network status, and flow patterns/characteristics in order to achieve better traffic control and management. This article discusses the state-of-the-art in traffic engineering for SDN with attention to four cores including flow management, fault tolerance, topology update, and traffic analysis. Challenging issues for SDN traffic engineering solutions are discussed in detail.

  • a roadmap for traffic engineering in sdn openflow Networks
    Computer Networks, 2014
    Co-Authors: Ian F Akyildiz, Pu Wang, Wu Chou
    Abstract:

    Software Defined Networking (SDN) is an emerging Networking paradigm that separates the Network control plane from the data forwarding plane with the promise to dramatically improve Network resource utilization, simplify Network management, reduce operating cost, and promote innovation and evolution. Although traffic engineering techniques have been widely exploited in the past and current data Networks, such as ATM Networks and IP/MPLS Networks, to optimize the performance of communication Networks by dynamically analyzing, predicting, and regulating the behavior of the transmitted data, the unique features of SDN require new traffic engineering techniques that exploit the Global Network View, status, and flow patterns/characteristics available for better traffic control and management. This paper surveys the state-of-the-art in traffic engineering for SDNs, and mainly focuses on four thrusts including flow management, fault tolerance, topology update, and traffic analysis/characterization. In addition, some existing and representative traffic engineering tools from both industry and academia are explained. Moreover, open research issues for the realization of SDN traffic engineering solutions are discussed in detail.

Osamu Akashi - One of the best experts on this subject based on the ideXlab platform.

  • rethinking packet classification for Global Network View of software defined Networking
    International Conference on Network Protocols, 2014
    Co-Authors: Takeru Inoue, Toru Mano, Kimihiro Mizutani, Shinichi Minato, Osamu Akashi
    Abstract:

    In software-defined Networking, applications are allowed to access a Global View of the Network so as to provide sophisticated functionalities, such as quality-oriented service delivery, automatic fault localization, and Network verification. All of these functionalities commonly rely on a well-studied technology, packet classification. Unlike the conventional classification problem to search for the action taken at a single switch, the Global Network View requires to identify the Network-wide behavior of the packet, which is defined as a combination of switch actions. Conventional classification methods, however, fail to well support Network-wide behaviors, since the search space is complicatedly partitioned due to the combinations. This paper proposes a novel packet classification method that efficiently supports Network-wide packet behaviors. Our method utilizes a compressed data structure named the multi-valued decision diagram, allowing it to manipulate the complex search space with several algorithms. Through detailed analysis, we optimize the classification performance as well as the construction of decision diagrams. Experiments with real Network datasets show that our method identifies the packet behavior at 20.1 Mpps on a single CPU core with only 8.4 MB memory, by contrast, conventional methods failed to work even with 16 GB memory. We believe that our method is essential for realizing advanced applications that can fully leverage the potential of software defined Networking.

Pu Wang - One of the best experts on this subject based on the ideXlab platform.

  • research challenges for traffic engineering in software defined Networks
    IEEE Network, 2016
    Co-Authors: Ian F Akyildiz, Pu Wang, Wu Chou
    Abstract:

    SDN is an emerging Networking paradigm that separates the Network control plane from the data forwarding plane with the promise to dramatically improve Network resource utilization, simplify Network management, reduce operating costs, and promote innovation and evolution. While traffic engineering techniques have been widely exploited for ATM and IP/MPLS Networks for performance optimization in the past, the promising SDN Networks require novel traffic engineering solutions that can exploit the Global Network View, Network status, and flow patterns/characteristics in order to achieve better traffic control and management. This article discusses the state-of-the-art in traffic engineering for SDN with attention to four cores including flow management, fault tolerance, topology update, and traffic analysis. Challenging issues for SDN traffic engineering solutions are discussed in detail.

  • a roadmap for traffic engineering in sdn openflow Networks
    Computer Networks, 2014
    Co-Authors: Ian F Akyildiz, Pu Wang, Wu Chou
    Abstract:

    Software Defined Networking (SDN) is an emerging Networking paradigm that separates the Network control plane from the data forwarding plane with the promise to dramatically improve Network resource utilization, simplify Network management, reduce operating cost, and promote innovation and evolution. Although traffic engineering techniques have been widely exploited in the past and current data Networks, such as ATM Networks and IP/MPLS Networks, to optimize the performance of communication Networks by dynamically analyzing, predicting, and regulating the behavior of the transmitted data, the unique features of SDN require new traffic engineering techniques that exploit the Global Network View, status, and flow patterns/characteristics available for better traffic control and management. This paper surveys the state-of-the-art in traffic engineering for SDNs, and mainly focuses on four thrusts including flow management, fault tolerance, topology update, and traffic analysis/characterization. In addition, some existing and representative traffic engineering tools from both industry and academia are explained. Moreover, open research issues for the realization of SDN traffic engineering solutions are discussed in detail.

Takeru Inoue - One of the best experts on this subject based on the ideXlab platform.

  • rethinking packet classification for Global Network View of software defined Networking
    International Conference on Network Protocols, 2014
    Co-Authors: Takeru Inoue, Toru Mano, Kimihiro Mizutani, Shinichi Minato, Osamu Akashi
    Abstract:

    In software-defined Networking, applications are allowed to access a Global View of the Network so as to provide sophisticated functionalities, such as quality-oriented service delivery, automatic fault localization, and Network verification. All of these functionalities commonly rely on a well-studied technology, packet classification. Unlike the conventional classification problem to search for the action taken at a single switch, the Global Network View requires to identify the Network-wide behavior of the packet, which is defined as a combination of switch actions. Conventional classification methods, however, fail to well support Network-wide behaviors, since the search space is complicatedly partitioned due to the combinations. This paper proposes a novel packet classification method that efficiently supports Network-wide packet behaviors. Our method utilizes a compressed data structure named the multi-valued decision diagram, allowing it to manipulate the complex search space with several algorithms. Through detailed analysis, we optimize the classification performance as well as the construction of decision diagrams. Experiments with real Network datasets show that our method identifies the packet behavior at 20.1 Mpps on a single CPU core with only 8.4 MB memory, by contrast, conventional methods failed to work even with 16 GB memory. We believe that our method is essential for realizing advanced applications that can fully leverage the potential of software defined Networking.