Nowadays, network traffic classification plays an important role in many fields including network management, intrusion detection system, malware detection system, etc. Most of the previous research works concentrate on features extracted in the non-encrypted network traffic. However, these features are not compatible with all kind of traffic characterization. Google's QUIC protocol (Quick UDP Internet Connection protocol) is implemented in many services of Google. Nevertheless, the emergence of this protocol imposes many obstacles for traffic classification due to the reduction of visibility for operators into network traffic, so the port and payload- based traditional methods cannot be applied to identify the QUIC- based services. To address this issue, we proposed a novel technique for traffic classification based on the convolutional neural network which combines the feature extraction and classification phase into one system. The proposed method uses the flow and packet-based features to improve the performance. In comparison with current methods, the proposed method can detect some kind of QUIC-based services such as Google Hangout Chat, Google Hangout Voice Call, YouTube, File transfer and Google play music. Besides, the proposed method can achieve the microaveraging F1-score of 99.24 percent.

As current server capacity and network bandwidth become increasingly overloaded by the rapid growth of high quality emerging multimedia services such as mobile online gaming, social networking or IPTV, a critical factor of success of these multimedia services becomes the end-user perception of quality while them using the service. As a result, user-centered approaches that consider quality of experience (QoE) constitute the current design trend for network systems of content providers and network operators. A content distribution network (CDN) that replicates the content from original servers to the replicated servers close to end users is actually an effective solution to improve network quality. We propose a QoE-based server selection algorithm in the context of a CDN architecture. Using realistic characteristics of the server selection process, we formalize our selection model as a sequential decision problem solved by the multi-armed bandit (MAB) paradigm. By using realistic experiments, we demonstrate that our approach yields significant improvements in term of user perception compared to traditional methods (such as Fastest, Closest and Round Robin).

Software‐Defined Networking (SDN) brought a groundbreaking idea to facilitate network system management by decoupling and abstracting the Control plane and Data plane of traditional networks. The centralised control offers network administrators many benefits such as a global view of the network, programmability, dynamic updating of forwarding rules, and software‐based traffic analysis. The SDN architecture has been applied a lot in practice, and especially in Internet of Things (IoT) platforms. With the superiority of SDN, IoT devices can be managed and configured much more easily when combined. However, SDN also raises many challenges in terms of scalability, reliability, and security. Blockchain is another promising solution for secure information storage and transmission technology that operates without a centralised authority. Applying Blockchain technology into SDN can address some of the current issues of SDN by providing decentralised methods to authenticate exchanged network information. This study provides a comprehensive survey on Blockchain technologies applied to SDN in both security and non‐security fields. First, related studies and an overview of SDN and the background of Blockchain technology are presented. Then, the authors review how Blockchain technologies are applied in SDN from two perspectives: non‐security and security‐aware approaches. Finally, challenges and broader perspectives are discussed.

A content delivery network (CDN) is able to handle high traffic and offer reliable services by geographically bringing the content data to the edge network, where replica servers are installed closer to the end users. The traditional CDN architecture lacks a global view of the whole network and, thus, cannot dynamically and optimally perform the server selection task. In this letter, we propose to integrate a software-defined network (SDN) into the CDN architecture. Our intuitive motivation is to decouple the control plane from the forwarding plane in order to offer flexibility and programmability by using the centralized controller. This letter also develops a novel server selection algorithm that is based on the so-called multi-armed bandit problem. Such an algorithm is proved to optimize the server selection function and provide a good experimental result in terms of both average response time and reward score.

In the years since its initiation, the software-defined network paradigm has evolved into a distinguished networking technology by causing a revolution in separating the control logic from physical devices and centralizing software-based controllers. Despite its indisputable benefits compared with the traditional network, the SDN raises the challenge of scalability with its physically centralized control. The only potential solution is to transform it into physically distributed SDN control. However, this solution requires the interoperability between SDN controllers, and the consistency of network state being distributed across these controllers. Although some east–west interfaces that help SDN controllers exchange network information have been released, they reveal several drawbacks. First, they cannot support a heterogeneous SDN system where SDN controllers are developed by different providers. Secondly, their consistency solution is simple in disregarding the tradeoff between the consistency level and the performance of SDN networks. This paper proposes an east–west interface, called SINA, to provide the interoperability of a heterogeneous and distributed SDN network. In addition, a novel reinforcement-learning-based consistency algorithm is introduced for an adaptive, quorum-based replication mechanism. The experimental results showed that SINA successfully connects heterogeneous and distributed SDN domains and balances the consistency and network performance.