Adriana Fernández-Fernández

Achieving Energy Efficiency: An Energy-Aware Approach in SDN

Achieving energy efficiency has recently become an essential aim of networking research due to the ever increasing power consumption and CO2 emissions generated by large data networks. 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 addresses the problem of optimizing the power consumption in SDN using an energy-aware traffic engineering approach that minimizes the number of links that can be used to satisfy a given traffic demand. Different from previous works, we focus on optimizing energy consumption in OpenFlow networks with in-band control traffic. Our approach also considers performance constraints that are crucial in the correct operation of SDN, such as bounded delay for the control plane traffic and load balance between controllers. First, we present a complete formulation of the optimization problem involving the routing requirements for control and data plane communications. To reduce the time complexity of our model in large-scale topologies we derive a heuristic algorithm. Significant values of energy saving (up to 60%) are reached in the simulations using real topologies and demands data.

A Multi-Objective Routing Strategy for QoS and Energy Awareness in Software-Defined Networks

Energy consumption is a key concern in the deployment and operation of current data networks, for which software-defined networks (SDNs) 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.

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.

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.

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.

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

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 adta 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.

A Distributed Algorithm for Topology Discovery in Software-Defined Networks

In this paper we address the issue of designing a novel distributed routing algorithm that optimizes the power consumption in large scale software-defined networks (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 traffic demand under performance constraints such as control traffic delay and link utilization.To ensure a proficient topology discovery service in Software-Defined Networks (SDN), we propose a simple agents-based mechanism to improve the efficiency of the topology discovery process. In this work, an algorithm for a novel Topology Discovery Protocol (SD-TDP) is designed. This protocol will be implemented in each switch through an agent. Thus, this approach will provide a distributed solution to solve the problem of network topology discovery in a more simple and efficient way.To ensure a proficient topology discovery service in Software-Defined Networks (SDN), we propose a simple agents-based mechanism to improve the efficiency of the topology discovery process. In this work, an algorithm for a novel Topology Discovery Protocol (SD-TDP) is designed. This protocol will be implemented in each switch through an agent. Thus, this approach will provide a distributed solution to solve the problem of network topology discovery in a more simple and efficient way.

A Distributed Energy-Aware Routing Algorithm in Software-Defined Networks

In this paper we address the issue of designing a novel distributed routing algorithm that optimizes the power consumption in large scale software-defined networks (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 traffic demand under performance constraints such as control traffic delay and link utilization.

Improved Energy-Aware Routing Algorithm in 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, SDN allows a flexible programmability, suitable for the power-consumption optimization problem. In this paper we present an energy-aware routing approach which minimizes the number of links used to satisfy a given traffic demand. Different from previous works, we optimize energy consumption in OpenFlow networks with in-band control traffic. To this end, we start formulating an optimization model that considers routing requirements for control and data plane communications. To reduce the complexity of our model in large-scale topologies, a heuristic algorithm is developed as well. Although it is not widely researched, except for quantitative and heuristic results, we also derive a simple and efficient algorithm for the best controller placement in terms of energy saving. Simulation results confirm that the proposed solution enables the achievement of significant energy savings.