Contributions to topology discovery, self-healing and VNF placement in software-defined and virtualized networks

The evolution of information and communication technologies (e.g. cloud computing, the Internet of Things (IoT) and 5G, among others) has enabled a large market of applications and network services for a massive number of users connected to the Internet. Achieving high programmability while decreasing complexity and costs has become an essential aim of networking research due to the ever-increasing pressure generated by these applications and services. However, meeting these goals is an almost impossible task using traditional IP networks. Software-Defined Networking (SDN) is an emerging network architecture that could address the needs of service providers and network operators. This new technology consists in decoupling the control plane from the data plane, enabling the centralization of control functions on a concentrated or distributed platform. It also creates an abstraction between the network infrastructure and network applications, which allows for designing more flexible and programmable networks. Recent trends of increased user demands, the explosion of Internet traffic and diverse service requirements have further driven the interest in the potential capabilities of SDN to enable the introduction of new protocols and traffic management models. This doctoral research is focused on improving high-level policies and control strategies, which are becoming increasingly important given the limitations of current solutions for large-scale SDN environments. Specifically, the three largest challenges addressed in the development of this thesis are related to the processes of topology discovery, fault recovery and Virtual Network Function (VNF) placement in software-defined and virtualized networks. These challenges led to the design of a set of effective techniques, ranging from network protocols to optimal and heuristic algorithms, intended to solve existing problems and contribute to the deployment and adoption of such programmable networks.For the first challenge, this work presents a novel protocol that, unlike existing approaches, enables a distributed layer 2 discovery without the need for previous IP configurations or controller knowledge of the network. By using this mechanism, the SDN controller can discover the network view without incurring scalability issues, while taking advantage of the shortest control paths toward each switch. Moreover, this novel approach achieves noticeable improvement with respect to state-of-the-art techniques. To address the resilience concern of SDN, we propose a self-healing mechanism that recovers the control plane connectivity in SDN-managed environments without overburdening the controller performance. The main idea underlying this proposal is to enable real-time recovery of control paths in the face of failures without the intervention of a controller. Obtained results show that the proposed approach recovers the control topology efficiently in terms of time and message load over a wide range of generated networks. The third contribution made in this thesis combines topology knowledge with bin packing techniques in order to efficiently place the required VNF. An online heuristic algorithm with low-complexity was developed as a suitable solution for dynamic infrastructures. Extensive simulations, using network topologies representative of different scales, validate the good performance of the proposed approaches regarding the number of required instances and the delay among deployed functions. Additionally, the proposed heuristic algorithm improves the execution times by a fifth order of magnitude compared to the optimal formulation of this problem.Postprint (published version

Energy-aware routing in multiple domains software defined networks

The growing energy consumption of communication networks has attracted the attention of the networking researchers in the last decade. In this context, the new architecture of Software-Defined Networks (SDN) allows a flexible programmability, suitable for the power-consumption optimization problem. In this paper we address the issue of designing a novel distributed routing algorithm that optimizes the power consumption in large scale SDN with multiple domains. The solution proposed, called DEAR (Distributed Energy- Aware Routing), tackles the problem of minimizing the number of links that can be used to satisfy a given data traffic demand under performance constraints such as control traffic delay and link utilization. To this end, we present a complete formulation of the optimization problem that considers routing requirements for control and data plane communications. Simulation results confirm that the proposed solution enables the achievement of significant energy savings.Peer ReviewedPostprint (published version

Discovering the network topology: an efficient approach for SDN

Network topology is a physical description of the overall resources in the network. Collecting this information using efficient mechanisms becomes a critical task for important network functions such as routing, network management, quality of service (QoS), among many others. Recent technologies like Software-Defined Networks (SDN) have emerged as promising approaches for managing the next generation networks. In order to ensure a proficient topology discovery service in SDN, we propose a simple agents-based mechanism. This mechanism improves the overall efficiency of the topology discovery process. In this paper, an algorithm for a novel Topology Discovery Protocol (SD-TDP) is described. This protocol will be implemented in each switch through a software agent. Thus, this approach will provide a distributed solution to solve the problem of network topology discovery in a more simple and efficient way.Peer ReviewedPostprint (published version

Self-healing topology discovery protocol for software defined networks

“© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. http://ieeexplore.ieee.org/document/8319433/”This letter presents the design of a self-healing protocol for automatic discovery and maintenance of the network topology in Software Defined Networks (SDN). The proposed protocol integrates two enhanced features (i.e. layer 2 topology discovery and autonomic fault recovery) in a unified mechanism. This novel approach is validated through simulation experiments using OMNET++. Obtained results show that our protocol discovers and recovers the control topology efficiently in terms of time and message load over a wide range of generated networks.Peer ReviewedPostprint (author's final draft

A multi-objective routing strategy for QoS and energy awareness in software-defined networks

“© © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. http://ieeexplore.ieee.org/document/8013750/”Energy consumption is a key concern in the deployment and operation of current data networks, for which Software-Defined Networks (SDN) have become a promising alternative. Although several works have been proposed to improve the energy efficiency, these techniques may lead to performance degradations when QoS requirements are neglected. Inspired by this problem, this letter introduces a new routing strategy, jointly considering QoS requirements and energy awareness in SDN with in-band control traffic. To that end, we present a complete formulation of the optimization problem and implement a Multi- Objective Evolutionary Algorithm. Simulation results validate the performance improvement on critical network parameters.Peer ReviewedPostprint (published version

Discovering the Network Topology: An Efficient Approach for SDN

Network topology is a physical description of the overall resources in the network. Collecting this information using efficient mechanisms becomes a critical task for important network functions such as routing, network management, quality of service (QoS), among many others. Recent technologies like Software-Defined Networks (SDN) have emerged as promising approaches for managing the next generation networks. In order to ensure a proficient topology discovery service in SDN, we propose a simple agents-based mechanism. This mechanism improves the overall efficiency of the topology discovery process. In this paper, an algorithm for a novel Topology Discovery Protocol (SD-TDP) is described. This protocol will be implemented in each switch through a software agent. Thus, this approach will provide a distributed solution to solve the problem of network topology discovery in a more simple and efficient way

Self-healing and SDN: bridging the gap

Achieving high programmability has become an essential aim of network research due to the ever-increasing internet traffic. Software-Defined Network (SDN) is an emerging architecture aimed to address this need. However, maintaining accurate knowledge of the network after a failure is one of the largest challenges in the SDN. Motivated by this reality, this paper focuses on the use of self-healing properties to boost the SDN robustness. This approach, unlike traditional schemes, is not based on proactively configuring multiple (and memory-intensive) backup paths in each switch or performing a reactive and time-consuming routing computation at the controller level. Instead, the control paths are quickly recovered by local switch actions and subsequently optimized by global controller knowledge. Obtained results show that the proposed approach recovers the control topology effectively in terms of time and message load over a wide range of generated networks. Consequently, scalability issues of traditional fault recovery strategies are avoided.Postprint (published version

Evaluating the Impact of Energy-Aware Routing on Software-Defined Networking Performance

[EN] Increasing power consumption and CO2 emissions generated by large data networks have become a major concern over the last decade. For this problem, the emerging paradigm of Software-Defined Networks (SDN) can be seen as an attractive solution. In these networks an energy-aware routing model could be easily implemented leveraging the control and data plane separation. This paper investigates the impact of energy-aware routing on SDN performance. To that end, we propose a novel energy- aware mechanism that reduces the number of active links in SDN with multiple controllers, considering in-band control traffic, i.e. links are shared between data and control plane traffic. The proposed strategy exploits knowledge of the network topology combined with traffic engineering techniques to reduce the overall power consumption. Therefore, two heuristic algorithms are designed: a static network configuration and a dynamic energy-aware routing. Significant values of switched-off links are reached in the simulations using real topologies and demands data. Moreover, obtained results confirm that crucial network parameters such as control traffic delay, data path latency, link utilization and TCAM occupation are affected by the performance-agnostic energy-aware model.This work has been supported by the Ministerio de Econom´ıa y Competitividad of the Spanish Government under project TEC2016-76795-C6-1-R and AEI/FEDER, UE and through a predoctoral FPI scholarship.Fernández-Fernández, A.; Cervelló-Pastor, C.; Ochoa-Aday, L. (2018). Evaluating the Impact of Energy-Aware Routing on Software-Defined Networking Performance. En XIII Jornadas de Ingeniería telemática (JITEL 2017). Libro de actas. Editorial Universitat Politècnica de València. 241-248. https://doi.org/10.4995/JITEL2017.2017.6489OCS24124

ETDP: enhanced topology discovery protocol for software-defined networks

Discovering network elements in a dynamic and optimized manner and being able to contend with ever-growing traffic is a key requirement for current networking environments. In software-defined networks (SDNs), the controller collects the topology information from the data plane and maintains an abstract view of the entire network, which is crucial for the proper functioning of applications and network services. However, there is still the need for an enhanced protocol for automatic discovery and mechanisms of autoconfiguration of network elements according to new policies and business requirements. To overcome this challenge, this paper presents a novel protocol that, unlike existing approaches, enables a distributed layer-2 discovery without the need for previous network configurations or controller knowledge of the network. By using this mechanism, the SDN controller can discover the network view without incurring scalability issues, while taking advantage of the shortest control paths toward each switch. The obtained results show that our enhanced protocol is efficient in terms of time and message load over a wide range of generated networks and outperforms the state-of-the-art techniques.Peer ReviewedPostprint (published version

An online algorithm for dynamic NFV placement in cloud-based autonomous response networks

Autonomous response networks are becoming a reality thanks to recent advances in cloud computing, Network Function Virtualization (NFV) and Software-Defined Networking (SDN) technologies. These enhanced networks fully enable autonomous real-time management of virtualized infrastructures. In this context, one of the major challenges is how virtualized network resources can be effectively placed. Although this issue has been addressed before in cloud-based environments, it is not yet completely resolved for the online placement of virtual machines. For such a purpose, this paper proposes an online heuristic algorithm called Topology-Aware Placement of Virtual Network Functions (TAP-VNF) as a low-complexity solution for such dynamic infrastructures. As a complement, we provide a general formulation of the network function placement using the service function chaining concept. Furthermore, two metrics called consolidation and aggregation validate the efficiency of the proposal in the experimental simulations. We have compared our approach with optimal solutions, in terms of consolidation and aggregation ratios, showing a more suitable performance for dynamic cloud-based environments. The obtained results show that TAP-VNF also outperforms existing approaches based on traditional bin packing schemes.Postprint (published version