Abstract-The Internet has led to the creation of a digital society, where (almost) everything is connected and is accessible from anywhere. However, despite their widespread adoption, traditional IP networks are complex and very hard to manage. It is both difficult to configure the network according to predefined policies, and to reconfigure it to respond to faults, load and changes. To make matters even more difficult, current networks are also vertically integrated: the control and data planes are bundled together. Software-Defined Networking (SDN) is an emerging paradigm that promises to change this state of affairs, by breaking vertical integration, separating the network's control logic from the underlying routers and switches, promoting (logical) centralization of network control, and introducing the ability to program the network. The separation of concerns introduced between the definition of network policies, their implementation in switching hardware, and the forwarding of traffic, is key to the desired flexibility: by breaking the network control problem into tractable pieces, SDN makes it easier to create and introduce new abstractions in networking, simplifying network management and facilitating network evolution.In this paper we present a comprehensive survey on SDN. We start by introducing the motivation for SDN, explain its main concepts and how it differs from traditional networking, its roots, and the standardization activities regarding this novel paradigm. Next, we present the key building blocks of an SDN infrastructure using a bottom-up, layered approach. We provide an in-depth analysis of the hardware infrastructure, southbound and northbound APIs, network virtualization layers, network operating systems (SDN controllers), network programming languages, and network applications. We also look at cross-layer problems such as debugging and troubleshooting. In an effort to anticipate the future evolution of this new paradigm, we discuss the main ongoing research efforts and challenges of SDN. In particular, we address the design of switches and control platforms -with a focus on aspects such as resiliency, scalability, performance, security and dependability -as well as new opportunities for carrier transport networks and cloud providers. Last but not least, we analyze the position of SDN as a key enabler of a software-defined environment.

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The increase in the number of SDN-based deployments in production networks is triggering the need to consider fault-tolerant designs of controller architectures. Commercial SDN controller solutions incorporate fault tolerance, but there has been little discussion in the SDN community on the design of such systems and the tradeoffs involved. To fill this gap, we present a by-construction design of a fault-tolerant controller, and materialize it by proposing and formalizing a practical architecture for small to medium-sized networks. A central component of our design is a replicated shared database that stores all network state. Contrary to the more common primarybackup approaches, the proposed design guarantees a smooth transition in case of failures and avoids the need of an additional coordination service. Our preliminary results show that the performance of our solution fulfills the demands of the target networks. We hope this work to be a first step in what we consider a necessary discussion on how to build robust SDNs.

Maintaining a strongly consistent network view in a Software Defined Network has been usually proclaimed as a synonym of low performance. We disagree. To support our view, in this paper we argue that with the use of modern distributed systems techniques it is possible to build a strongly consistent, fault-tolerant SDN control framework that achieves acceptable performance.The central element of our architecture is a highly-available, strongly consistent data store. We describe a prototype implementation of a distributed controller architecture integrating the Floodlight controller with a data store implemented using a stateof-the-art replication algorithm. We evaluate the feasibility of the proposed design by analyzing the workloads of real SDN applications (a learning switch, a load balancer and a device manager) and showing that the data store is capable of handling them with adequate performance.

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