Dissertação de Mestrado em Engenharia Informática apresentada à Faculdade de Ciências e Tecnologia da Universidade de Coimbra ; Software-De ned Networking (SDN) is a recent computer networking trend that allows a centralized management of network devices through a controller entity, responsible for processing incoming data, and assigning matching ows in the managed devices. When working in a SDN environment, it is possible to monitor the current state of a network and perform path calculation for new ows according to that state. In addition, when di erent paths are available, and using a constrained multiple path computation algorithm, numerous paths can be calculated, following up constrains imposed by the metrics collected from the network. Combined that with the usage of multi-homed network transport protocols, such as Multipath TCP (MPTCP), the multiple created sub- ows can be assigned to di erent paths, contributing to the increase of aspects such as resilience or throughput. This work presents a SDN controller application that calculates paths between network nodes by using di erent path computation algorithms. It features a Quality of Service (QoS) metrics monitoring module that adds link quality information to the existing topology data, used for calculating constrained QoS metrics paths through the usage of the Self-adaptive Multiple Constraints Routing Algorithm (SAMCRA) algorithm. When multiple paths are available, di erent ow pinning strategies can be used to select the next path. This application is evaluated along with the usage of MPTCP, allowing a cross-layer interaction between the transport and network layers. The main obtained results showed that the usage of a constrained multiple path algorithm improves the QoS metrics values measured in the established connections, while the usage of an algorithm that produces a larger set of available paths increases the overall ows throughput.


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    Title :

    Development of an OpenFlow controller application for enhanced path computation



    Publication date :

    2015-07-13


    Remarks:

    201538091


    Type of media :

    Theses


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



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