The imminent arrival of the Internet of Things (IoT), which consists of a vast number of devices with heterogeneous characteristics, means that future networks need a new architecture to accommodate the expected increase in data generation. Software defined networking (SDN) and network virtualization (NV) are two technologies that promise to cost-effectively provide the scale and versatility necessary for IoT services. In this paper, we survey the state of the art on the application of SDN and NV to IoT. To the best of our knowledge, we are the first to provide a comprehensive description of every possible IoT implementation aspect for the two technologies. We start by outlining the ways of combining SDN and NV. Subsequently, we present how the two technologies can be used in the mobile and cellular context, with emphasis on forthcoming 5G networks. Afterward, we move to the study of wireless sensor networks, arguably the current foremost example of an IoT network. Finally, we review some general SDN-NV-enabled IoT architectures, along with real-life deployments and use-cases. We conclude by giving directions for future research on this topic.

SDN and Virtualization Solutions for the Internet of Things: A Survey

Vehicular communication networks is a powerful tool that enables numerous vehicular data services and applications. The rapid growth in vehicles has also resulted in the vehicular network becoming heterogeneous, dynamic, and large-scale, making it hard to meet the strict requirements, such as extremely latency, high mobility, top security, and enormous connections of the fifth-generation network. Previous studies have shown that with the increase in the application of Software-Defined Networking (SDN) on Vehicular Ad-hoc Network (VANET) in industries, researchers have exerted considerable efforts to improve vehicular communications. This study presents an exhaustive review of previous works by classifying them based on based on wireless communication, particularly VANET. First, a concise summary of the VANET structure and SDN controller with layers and details of their infrastructure is provided. Second, a description of SDN-VANET applications in different wireless communications, such as the Internet of Things (IoT) and VANET is provided with concentration on the examination and comparison of SDN-VANET works on several parameters. This paper also provides a detailed analysis of the open issues and research directions accomplished while integrating the VANET with SDN. It also highlights the current and emerging technologies with use cases in vehicular networks to address the several challenges in the VANET infrastructure. This survey acts as a catalyst in raising the emergent robustness routing protocol, latency, connectivity and security issues of future SDN-VANET architectures.

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A Comprehensive Survey: Benefits, Services, Recent Works, Challenges, Security, and Use Cases for SDN-VANET

With the recent advances in the telecommunications and auto industries, we have witnessed growing interest in ITS, of which VANETs are an essential component. SDN can bring advantages to ITS through its ability to provide flexibility and programmability to networks through a logically centralized controller entity that has a comprehensive view of the network. However, as the SDN paradigm initially had fixed networks in mind, adapting it to work on VANETs requires some changes to address particular characteristics of this kind of scenario, such as the high mobility of its nodes. There has been initial work on bringing SDN concepts to vehicular networks to expand its abilities to provide applications and services through the increased flexibility, but most of these studies do not directly tackle the issue of loss of connectivity with said controller entity. In this article, we propose a hierarchical SDN-based vehicular architecture that aims to have improved performance in the situation of loss of connection with the central SDN controller. Simulation results show that our proposal outperforms traditional routing protocols in the scenario where there is no coordination from the central SDN controller.

An Architecture for Hierarchical Software-Defined Vehicular Networks

Proposing an optimal routing protocol for internet of vehicles with reduced overhead has endured to be a challenge owing to the incompetence of the current architecture to manage flexibility and scalability. The proposed architecture, therefore, consolidates an evolving network standard named as software defined networking in internet of vehicles. Which enables it to handle highly dynamic networks in an abstract way by dividing the data plane from the control plane. Firstly, road-aware routing strategy is introduced: a performance-enhanced routing protocol designed specifically for infrastructure-assisted vehicular networks. In which roads are divided into road segments, with road side units for multi-hop communication. A unique property of the proposed protocol is that it explores the cellular network to relay control messages to and from the controller with low latency. The concept of edge controller is introduced as an operational backbone of the vehicle grid in internet of vehicles, to have a real-time vehicle topology. Last but not least, a novel mathematical model is estimated which assists primary controller in a way to find not only a shortest but a durable path. The results illustrate the significant performance of the proposed protocol in terms of availability with limited routing overhead. In addition, we also found that edge controller contributes mainly to minimizes the path failure in the network.

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SD-IoV: SDN enabled routing for internet of vehicles in road-aware approach

5G-enabled Hierarchical architecture for software-defined intelligent transportation system

Vehicular Ad hoc Network (VANET) is an intermittently connected mobile network in which message propagation is quite challenging. Conventional routing protocols proposed for VANET are usually in greedy or optimum fashion. Geographical forwarding only uses local information to make the routing decision which may lead to long packet delay, while link-based forwarding has better performance but requires much more overheads. To disseminate message efficiently in VANET, a routing protocol which has both short delivery delay time and low routing overhead is required. In this paper, we proposed a SDN-based routing framework for efficiently message propagation in VANET. Software-Defined Networking (SDN) is an emerging technology that decouples the control plane from the data forwarding plane in switches and collects all the control planes into a central controller. In SDN-based routing framework, the central controller gathers network information from switches and computes optimal routing paths for switches based on the global network information. Since switches don’t need to exchange routing information with each other, the routing overhead is much lower. This paper is the first to propose a SDN-based routing framework for efficiently message propagation in VANET. A new algorithm is developed to find the global optimal route from the source to the destination in VANET with dynamic network density. We demonstrate, through the simulation results, that our proposed framework significantly outperforms the related protocols in terms of both delivery delay time and routing overhead.

SDN-Based Routing for Efficient Message Propagation in VANET

Spectrum auction is an important approach of spectrum distribution in cognitive radio networks. However, a single secondary user (SU) probably can't afford the price of spectrum. Multiple SUs grouping together to participate in the auction as a whole is helpful to increase purchasing power. However, SUs could suffer from a new group cheating problem, i.e., parts of users conspire to manipulate the auction by submitting untruthful bids. Existing auction mechanisms were mainly designed to be strategy-proof only for individual user and can't deal with group cheating. In this paper, a novel spectrum auction mechanism called COSTAG (COst Sharing based Truthful Auction with Group-buying) is proposed to address the group cheating problem. COSTAG consists of a grouping rule to perform grouping and a payment rule to determine the market-clearing price in the spectrum auction. Different from single-echelon pricing approach employed in existing works, a multi-echelon pricing strategy is designed to increase the transaction rate and optimize social profit for the auction. Comprehensive theoretical analysis shows that COSTAG can satisfy the crucial economic robustness properties, both individual and group truthfulness. Simulations demonstrate that comparing with existing works, COSTAG can improve the system performance significantly.

Cost sharing based truthful spectrum auction with collusion-proof

Dynamic spectrum sharing can improve the efficiency of spectrum utilization. Spectrum trading between primary users (PUs) and secondary users (SUs) is a popular and efficient way to fulfill this kind of spectrum sharing. In this paper we present a novel spectrum trading mechanism which operate among secondary users. More specifically, some secondary users which has leased spectrum from PUs can sublet it to other SUs to reduce their own leasing cost. Then all of the SUs can share these spectrum bands to conduct data transmission respectively. This leads to a new multi-leader multi-follower (MLMF) game which is different from existing works. The existence of Nash equilibrium of this formulated game is proven by redefining it as a shared MLMF constraint game. A decentralized algorithm is then proposed to find Nash equilibrium of this two tiers game with only local information. Simulations are provided to illustrate the convergence and effectiveness of the proposed algorithm.

Spectrum Sublet Game Among Secondary Users in Cognitive Radio Networks

AbstractIn this paper, we investigate device-free fall detection based on wireless channel state information (CSI). Here, we mainly propose a method that uses continuous wavelet transform (CWT) to generate images and then uses transform learning of convolutional networks for classification. In addition, we add a wavelet scattering network to automatically extract features and classify them using a long and short-term memory network (LSTM), which can increase the interpretability and reduce the computational complexity of the system. After applying these methods to wireless sensing technology, both methods have a higher accuracy rate. The first method can cope with the problem of degraded sensing performance when the environment is not exactly the same, and the second method has more stable sensing performance.KeywordsIntelligent wireless sensingFall detectionContinuous wavelet transformDeep learning 

A Deep Learning Approach Based on Continuous Wavelet Transform Towards Fall Detection

The spatial and temporal variations of licensed spectrum bands introduce new problems to cognitive wireless LANs. We propose a novel client-centric heterogeneous spectrum access mechanism to deal with these new challenges. All clients in a cell would not have to use the same channel to communicate with access point when there is no common available channel among these clients. In order to achieve channel agreement among nodes on different channels, a new MAC protocol is proposed with no need of common control channel. Considering that AP can only work on one channel at a time, we use a novel technique, subcarrier coding, to enable it to monitor multiple spectrum bands simultaneously. Each client can select its best channel based on local environment and requirement independently. Promising simulation results show that this new access mechanism not only resolve the problem of lacking common data channel in single cell, but also minimizes conflict significantly even in the case of a large number of clients.

Deming Pang

Papers

SDN-Based Routing for Efficient Message Propagation in VANET

Cost sharing based truthful spectrum auction with collusion-proof

Spectrum Sublet Game Among Secondary Users in Cognitive Radio Networks

A Deep Learning Approach Based on Continuous Wavelet Transform Towards Fall Detection

Client-centric heterogeneous access in cognitive WLANs