183 research outputs found

    Fast network configuration in Software Defined Networking

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    Software Defined Networking (SDN) provides a framework to dynamically adjust and re-program the data plane with the use of flow rules. The realization of highly adaptive SDNs with the ability to respond to changing demands or recover after a network failure in a short period of time, hinges on efficient updates of flow rules. We model the time to deploy a set of flow rules by the update time at the bottleneck switch, and formulate the problem of selecting paths to minimize the deployment time under feasibility constraints as a mixed integer linear program (MILP). To reduce the computation time of determining flow rules, we propose efficient heuristics designed to approximate the minimum-deployment-time solution by relaxing the MILP or selecting the paths sequentially. Through extensive simulations we show that our algorithms outperform current, shortest path based solutions by reducing the total network configuration time up to 55% while having similar packet loss, in the considered scenarios. We also demonstrate that in a networked environment with a certain fraction of failed links, our algorithms are able to reduce the average time to reestablish disrupted flows by 40%

    Loop-Free Route Updates for Software-Defined Networks

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    Softair: Software-defined networking and network function virtualization solutions for 5g cellular systems

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    One of the main building blocks and major challenges for 5G cellular systems is the design of flexible network architectures, which can be realized by the paradigm of software-defined networking (SDN) and network function virtualization (NFV). Existing commercial cellular systems rely on closed and inflexible hardware-based architectures both at the radio frontend and in the core network. These problems significantly delay the adoption and deployment of new standards, impose great challenges in implementing new techniques to maximize the network capacity and coverage, and prevent provisioning of truly-differentiated services for highly variable traffic patterns. The objective of this thesis is to introduce an innovative software-defined architecture for 5G cellular systems, called SoftAir. First, a detailed overview is provided for priori wireless SDN architecture solutions. Second, the SoftAir architecture is introduced with key design elements. Third, four essential management tools for SoftAir are developed. Last, novel software-defined traffic engineering, enabled by SoftAir, are proposed. Through the synergy of SDN and NFV, SoftAir enables the next-generation cellular networks with the needed flexibility for evolving and adapting to the ever-changing network context, and lays out the foundation for 5G wireless software-defined cellular systems.Ph.D.Ph.D

    Coeus: Consistent and Continuous Network Update in Software-Defined Networks:38th IEEE Conference on Computer Communications, INFOCOM 2020

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    Network update enables Software-Defined Networks (SDNs) to optimize the data plane performance via southbound APIs. The single update between the initial and the final network states fail to handle high-frequency changes or the burst event during the update procedure in time, leading to prolonged update time and inefficiency. On the contrary, the continuous update can respond to the network condition changes at all times. However, existing work, especially Update Algebra can only guarantee blackhole- and loop-free. The congestion-free property cannot be respected during the update procedure. In this paper, we propose Coeus, a continuous network update system while maintaining blackhole-, loop- and congestion-free simultaneously. Firstly, we establish an operation-based continuous update model. Based on this model, we dynamically reconstruct an operation dependency graph to capture unexecuted update operations and the link utilization variations. Subsequently, we develop an operation composition algorithm to eliminate redundant update commands and an operation node partition algorithm to speed up the update procedure. We prove that the partition algorithm is optimal and can guarantee the consistency. Finally, extensive evaluations show that Coeus can improve the makespan by at least 179% compared with state-of-the-art approaches when the arrival rate of update events equals to three times per second. © 2020 IEEE

    A Cognitive Routing framework for Self-Organised Knowledge Defined Networks

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    This study investigates the applicability of machine learning methods to the routing protocols for achieving rapid convergence in self-organized knowledge-defined networks. The research explores the constituents of the Self-Organized Networking (SON) paradigm for 5G and beyond, aiming to design a routing protocol that complies with the SON requirements. Further, it also exploits a contemporary discipline called Knowledge-Defined Networking (KDN) to extend the routing capability by calculating the “Most Reliable” path than the shortest one. The research identifies the potential key areas and possible techniques to meet the objectives by surveying the state-of-the-art of the relevant fields, such as QoS aware routing, Hybrid SDN architectures, intelligent routing models, and service migration techniques. The design phase focuses primarily on the mathematical modelling of the routing problem and approaches the solution by optimizing at the structural level. The work contributes Stochastic Temporal Edge Normalization (STEN) technique which fuses link and node utilization for cost calculation; MRoute, a hybrid routing algorithm for SDN that leverages STEN to provide constant-time convergence; Most Reliable Route First (MRRF) that uses a Recurrent Neural Network (RNN) to approximate route-reliability as the metric of MRRF. Additionally, the research outcomes include a cross-platform SDN Integration framework (SDN-SIM) and a secure migration technique for containerized services in a Multi-access Edge Computing environment using Distributed Ledger Technology. The research work now eyes the development of 6G standards and its compliance with Industry-5.0 for enhancing the abilities of the present outcomes in the light of Deep Reinforcement Learning and Quantum Computing

    Load Balancing Mechanisms in the Software Defined Networks: A Systematic and Comprehensive Review of the Literature

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    With the expansion of the network and increasing their users, as well as emerging new technologies, such as cloud computing and big data, managing traditional networks is difficult. Therefore, it is necessary to change the traditional network architecture. Lately, to address this issue, a notion named software-defined network (SDN) has been proposed, which makes network management more conformable. Due to limited network resources and to meet the requirements of quality of service, one of the points that must be considered is load balancing issue that serves to distribute data traffic among multiple resources in order to maximize the efficiency and reliability of network resources. Load balancing is established based on the local information of the network in the conventional network. Hence, it is not very precise. However, SDN controllers have a global view of the network and can produce more optimized load balances. Although load balancing mechanisms are important in the SDN, to the best of our knowledge, there exists no precise and systematic review or survey on investigating these issues. Hence, this paper reviews the load balancing mechanisms which have been used in the SDN systematically based on two categories, deterministic and non-deterministic. Also, this paper represents benefits and some weakness regarded of the selected load balancing algorithms and investigates the metrics of their algorithms. In addition, the important challenges of these algorithms have been reviewed, so better load balancing techniques can be applied by the researchers in the future. © 2018 IEEE

    Enhancing SDN WISE with Slicing Over TSCH

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    [EN] IWSNs (Industrial Wireless Sensor Networks) have become the next step in the evolution of WSN (Wireless Sensor Networks) due to the nature and demands of modern industry. With this type of network, flexible and scalable architectures can be created that simultaneously support traffic sources with different characteristics. Due to the great diversity of application scenarios, there is a need to implement additional capabilities that can guarantee an adequate level of reliability and that can adapt to the dynamic behavior of the applications in use. The use of SDNs (Software Defined Networks) extends the possibilities of control over the network and enables its deployment at an industrial level. The signaling traffic exchanged between nodes and controller is heavy and must occupy the same channel as the data traffic. This difficulty can be overcome with the segmentation of the traffic into flows, and correct scheduling at the MAC (Medium Access Control) level, known as slices. This article proposes the integration in the SDN controller of a traffic manager, a routing process in charge of assigning different routes according to the different flows, as well as the introduction of the Time Slotted Channel Hopping (TSCH) Scheduler. In addition, the TSCH (Time Slotted Channel Hopping) is incorporated in the SDN-WISE framework (Software Defined Networking solution for Wireless Sensor Networks), and this protocol has been modified to send the TSCH schedule. These elements are jointly responsible for scheduling and segmenting the traffic that will be sent to the nodes through a single packet from the controller and its performance has been evaluated through simulation and a testbed. The results obtained show how flexibility, adaptability, and determinism increase thanks to the joint use of the routing process and the TSCH Scheduler, which makes it possible to create a slicing by flows, which have different quality of service requirements. This in turn helps guarantee their QoS characteristics, increase the PDR (Packet Delivery Ratio) for the flow with the highest priority, maintain the DMR (Deadline Miss Ratio), and increase the network lifetime.This work has been supported by the MCyU (Spanish Ministry of Science and Universities) under the project ATLAS (PGC2018-094151-B-I00), which is partially funded by AEI, FEDER and EU and has been possible thanks to the collaboration of the Instituto Tecnologico de Informatica (ITI) of Valencia.Orozco-Santos, F.; Sempere Paya, VM.; Albero Albero, T.; Silvestre-Blanes, J. (2021). Enhancing SDN WISE with Slicing Over TSCH. Sensors. 21(4):1-29. https://doi.org/10.3390/s21041075S12921
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