Virtualization-enabled Adaptive Routing for QoS-aware Software-Defined Networks

Virtualization-enabled Adaptive Routing for QoS-aware Software-Defined Networks
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Book Synopsis Virtualization-enabled Adaptive Routing for QoS-aware Software-Defined Networks by : Alba Xifra Porxas

Download or read book Virtualization-enabled Adaptive Routing for QoS-aware Software-Defined Networks written by Alba Xifra Porxas and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: [ANGLÈS] Software-Defined Networking (SDN) has been recognized as the next-generation networking paradigm. It is a fast-evolving technology that decouples the network data plane, which are the network devices that forward traffic, from the network control plane, which is the software logic that controls ultimately how traffic is forwarded through the network. A logically centralized controller is responsible for all the control decisions and communication among the forwarding elements. It allows to control the network behavior from a single high level control program. However, Software-Defined Networks use many of its network resources inefficiently, which leads to over-loading network links, congestion in the queues and end-to-end packet delays. Consequently, it becomes clear that routing decisions affect the overall performance of a communication's network. Performance is determined in terms of Quality of Service guarantees, i.e. throughput, average packet delay, jitter and losses. Thus, a QoS-aware routing algorithm is required. Current traffic engineering techniques and state-of-the-art routing algorithms do not effectively use the merits of SDNs, such as global centralized visibility, real-time fast decisions, control and data plane decoupling, network management simplification and portability. In this thesis, we developed two new QoS-aware routing algorithms that exploit the advantages that SDN brings to improve the network performance. Two different scenarios have been studied: a centralized and a distributed models. The centralized scenario simplifies the management of complex flows and the customization, but scalability issues arise. In contrast, the distributed scenario is more scalable, but there may be state inconsistency and increase of shared information. In general, a centralized approach is better for data centers or home networks, whereas a distributed approach is better for large scale networks, e.g. cloud environments. First, the centralized SDN controller model is discussed, for which a multi-tenancy management framework is proposed to fulfill the quality-of-services (QoSs) requirements through tenant isolation, prioritization and flow allocation. A network virtualization algorithm is provided to isolate and prioritize tenants from different clients. Furthermore, a novel routing scheme, called QoS-aware Virtualization-enabled Routing (QVR), is presented. It combines the proposed virtualization technique and a QoS-aware framework to enable flow allocation with respect to different tenant applications. Simulation results confirm that the proposed QVR algorithm surpasses the conventional algorithms with less traffic congestion and packet delay. This facilitates reliable and efficient data transportation in generalized SDNs. Therefore, it yields to service performance improvement for numerous applications and enhancement of client isolation. Second, a distributed SDN controller model is analyzed. The network is divided into different clusters, and hierarchically split in two levels. This architecture leads to smaller sizes of routing tables in the switches, and substantially lesser calculations and updates of routing tables from the controller. Moreover, a new algorithm is developed, called QoS-aware Reinforcement Learning Routing (QRLR), where reinforcement learning is applied to the routing problem. The modeling of the reward function calculation solution allows the customization of the different requirements for each type of traffic, thus providing flexibility and adaptability to different flows and its requirements.


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