Due to the development of the Internet and the smart end systems such as smartphones, portable laptop, and other smart mobile devices, as well as the emergence of concepts such as cloud computing, social networks, and Internet of Things, 4G and 5G have changed network requirements. A software-defined network (SDN) is a new architecture to support new network requirements. This architecture is composed of three layers, data, control, and application plane. A lot of papers have been published in well-known journals to improve network performance, so we classify the solutions for performance improvement based on three SDN layers and three SDN-based spheres which are (a) SDN-data center, (b) wireless networks, and (c) software-defined wide area network. This paper surveys the articles which have been published by Springer, IEEE, Elsevier, and ACM. We extract the performance improvement solutions and resources which are required for performance control and the metrics to evaluate the network performance. This article can help network enthusiasts to better understand, investigate, and improve the performance of SDN-based networks.

Performance issues and solutions in SDN-based data center: a survey

Software Defined Networking (SDN) is a new technology that makes computer networks farther programmable. SDN is currently attracting significant consideration from both academia and industry. SDN is simplifying organisations to implement applications and assist flexible delivery, offering the capability of scaling network resources in lockstep with application and data. This technology allows the user to manage the network easily by permitting the user to control the applications and operating system. SDN not only introduces new ways of interaction within network devices, but it also gives more flexibility for the existing and future networking designs and operations. SDN is an innovative approach to design, implement, and manage networks that separate the network control (control plane) and the forwarding process (data plane) for a better user experience. The main differentiation between SDN and Traditional Networking is that SDN removes the decision-making part from the routers and it provides, logically, a centralised Control-Plane that creates a network view for the control and management applications. Through the establishment of SDN, many new network capabilities and services have been enabled, such as Software Engineering, Traffic Engineering, Network Virtualisation and Automation, and Orchestration for Cloud Applications. This paper surveys the state-of-the-art contribution such as a comparison between SDN and traditional networking. Also, comparison with other survey works on SDN, new information about controller, details about OpenFlow architecture, configuration, comprehensive contribution about SDN security threat and countermeasures, SDN applications, benefit of SDN, and Emulation & Tested for SDN. In addition, some existing and representative SDN tools from both industry and academia are explained. Moreover, future direction of SDN security solutions is discussed in detail.

A survey on the architecture, application, and security of software defined networking: challenges and open issues

Virtual reality (VR) content, including 360° panoramic video, provides users with an immersive multimedia experience and therefore attracts increasing research and development attention. However, the requirement of high bandwidth and low latency of virtual reality service demand puts forward greater challenges to the current infrastructure, especially mobile networks. Inspired by the sharable nature of virtual reality content tiles, we further considered the potential opportunities for computing, caching, and multicast to address the challenges of transmission of panoramic content. This paper proposes a novel transcoding-enabled VR video caching and delivery framework for edge-enhanced next-generation wireless networks. Firstly, an edge cooperative caching scheme based on multi-agent reinforcement learning is introduced to improve the utilization efficiency of computing and storage resources, and then reduce service delay. Second, a two-tier NOMA-based base station-multicast group matching mechanism is designed to solve the collaboration challenge during the edge delivery process. A series of experiments have demonstrated the advantages of the proposed scheme in terms of cache hit rate, latency and other aspects in comparison with alternative approaches.

A Transcoding-Enabled 360° VR Video Caching and Delivery Framework for Edge-Enhanced Next-Generation Wireless Networks

This paper considers a cross-layer optimization framework for video streaming in multinode wireless networks with a time-varying interference environment. We develop a distributed joint power control and rate adaptation framework that exploits the time diversity of the wireless channels, satisfies the hard delay constraints associated with video applications, and respects a certain fairness criterion among the nodes. The proposed framework performs power allocation at the physical/media access control layers to achieve a certain target signal-to-interference-plus-noise ratio, such that the difference between the arrival and the departure rates at the queues is very small, and performs video rate adaptation at the video coding layer (upper layer) according to the nodes' demanded video quality, their channel conditions, and a given fairness criterion. A main challenge here is that the adaptation of the video rate and the power control is not performed at the same time scale. We deal with this issue and model the power and rate variations of the nodes as linear stochastic dynamic equations and formulate a risk-sensitive control problem that captures the hard delay constraints of the video services and the fairness criterion for resource utilization. We provide an optimal solution for this control problem and illustrate the performance of our framework through simulations.

Joint Power Control and Rate Adaptation for Video Streaming in Wireless Networks With Time-Varying Interference

Since Internet of Things (IoT) communications can enjoy many advantages brought by content-centric networking (CCN) in nature, there is an increasing interest on their integration for better information retrieval and distribution. Nevertheless, different from the conventional multimedia traffic of which contents are hardly changed, IoT data are always transient and updated by their producers according to the actual situation. As a result, if without any effective countermeasures, outdated copies are inevitably stored by CCN routers and then distributed to the associated consumers, degrading both caching efficiency and user experience. In fact, most of related policies take little account of information freshness for cached contents, and how to tackle transient IoT data in CCN is still an ignored but crucial issue required for further explorations. Therefore, in this article, we propose an efficient popularity-based cache consistency management scheme, which aims to guarantee freshness of IoT data returned by on-path routers and avoid heavy signalling costs introduced at the same time. Extensive simulations were performed under both real-world scare-free and binary-tree topologies, and corresponding results have proved the efficiency of the proposed scheme in timely evictions of outdated IoT data stored by CCN in-network caching.

Efficient Cache Consistency Management for Transient IoT Data in Content-Centric Networking

A receiver-driven adaptive layer switching algorithm is proposed for adapting the video bitrate to match the achievable network throughput. It relies on a QoS-constrained equivalent bandwidth estimator employed at the receiver, which is used for triggering the adjustment of video layers at the video source. Simulations are conducted to illustrate its efficiency by showing that it is capable of accommodating different channel qualities without their prior knowledge.

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Receiver-Driven Adaptive Enhancement Layer Switching Algorithm for Scalable Video Transmission Over Link-adaptive Networks

Explosive growth in video traffic volumes incurs a high percentage of redundancy in today's Internet, following the 80–20 rule. Fortunately, the advanced in-network cache is considered as an effective scheme for eliminating the repetitive traffic by caching the popular content in network nodes. Besides, the emerging software-defined networking (SDN) enables centralized control and management, as well as the collaboration between network devices and upper applications. Moreover, the Network Functions Virtualization is also developed to support for customized network functions, including caching and streaming. This inspires us to design an SDN-assisted multimedia streaming Video-on-Demand system, integrating in-network cache, to improve the quality of service. The designed architecture is capable of reducing the redundant traffic via the reusable duplications. In particular, it can achieve greater performance gains by deploying specific scheduling policy. We further propose a variable-length interval cache strategy for RTP streaming, which can realize the self-adaptive adjustment of the size of cached video segments based on their access patterns. Our goal is to efficiently utilize the limited storage resources and increase the cache hit ratio. We present the theoretical analysis to demonstrate the attainable performance of the proposed algorithm; furthermore, the integrated system design is implemented as a prototype to show its feasibility and applicability. Ultimately, emulation experiments are conducted to evaluate the achievable performance improvement more comprehensively.

Software-Defined Multimedia Streaming System Aided By Variable-Length Interval In-Network Caching

Caching contents close to end-users can improve the network performance, while causing the problem of guaranteeing consistency. Specifically, solutions are classified into validation and invalidation, the latter of which can provide strong cache consistency strictly required in some scenarios. To date, little work on the analysis of cache invalidation has been covered. In this work, by using conditional probability to characterize the interactive relationship between existence and validity, we develop an analytical model that evaluates the performance (hit probability and server load) of four different invalidation schemes with LRU replacement under arbitrary invalidation frequency distribution. The model allows us to theoretically identify some key parameters that affect our metrics of interest and gain some common insights on parameter settings to balance the performance of cache invalidation. Compared with other cache invalidation models, our model can achieve higher accuracy in predicting the cache hit probability. We also conduct extensive simulations that demonstrate the achievable performance of our model.

On the Analysis of Cache Invalidation With LRU Replacement

Named Data Networking (NDN) aims to improve the efficiency of data delivery for the Internet. One of the typical characteristics of NDN is ubiquitous caching, that is to say, each network participant in NDN is capable of caching contents. This caching feature is beneficial for enhancing the data availability but also raises a problem of cache consistency. In this paper, we propose a novel strategy of cache invalidation, called PIOR (Proactive Invalidation with Optional Renewing), to provide strong consistency for NDN. PIOR is based on a lightweight publish/subscribe model, actively publishing the updated contents to the router nodes to guarantee the copy validity. We also conceive customized publish/subscribe rules to relieve the unbearable burden on the server imposed by the excessive publishing traffic. The advantage of PIOR lies in simple deployment and compatibility, since the invalidation process of PIOR is independent of the inherent process of NDN. We conduct extensive simulations over a real topology to evaluate the achievable performance of PIOR. The simulation results show that PIOR is able to achieve a high hit ratio and low server load at the low cost of network management.

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A Cache Invalidation Strategy Based on Publish/Subscribe for Named Data Networking

With the rapid development of network technology and encryption technology, network security issues have received more and more attention, and network encryption traffic is increasing, which results in a huge challenge for network traffic classification. Combining machine learning algorithms with manual design has become a mainstream approach to solve this problem, However, it requires a large amount of human effort to extract and process features, which depend on professional experience heavily. In this paper, We discuss the essential reason why convolutional neural network(CNN) can deal with the problem of encrypted traffic classification and propose a novel classification framework the Bidirectional Flow Sequence Network(BFSN) based on long short-term memory (LSTM). Compared with the traditional traffic classification scheme, the BFSN is an end-to-end classification model that learns representative features from the raw traffic and classifies them. Moreover, We apply the length and direction information of the encrypted traffic to construct the bidirectional traffic sequence and then process it based on LSTM. Our Experiments gains the excellent accuracy about 91% based the ISCX VPN-NonVPN dataset.

Quan Zheng

Papers

Receiver-Driven Adaptive Enhancement Layer Switching Algorithm for Scalable Video Transmission Over Link-adaptive Networks

Software-Defined Multimedia Streaming System Aided By Variable-Length Interval In-Network Caching

On the Analysis of Cache Invalidation With LRU Replacement

A Cache Invalidation Strategy Based on Publish/Subscribe for Named Data Networking

BFSN: A Novel Method of Encrypted Traffic Classification Based on Bidirectional Flow Sequence Network