Market Driven Multi-domain Network Service Orchestration in 5G Networks

The advent of a new breed of enhanced multimedia services has put network operators into a position where they must support innovative services while ensuring both end-to-end Quality of Service requirements and profitability. Recently, Network Function Virtualization (NFV) has been touted as a cost-effective underlying technology in 5G networks to efficiently provision novel services. These NFV-based services have been increasingly associated with multi-domain networks. However, several orchestration issues, linked to cross-domain interactions and emphasized by the heterogeneity of underlying technologies and administrative authorities, present an important challenge. In this paper, we tackle the cross-domain interaction issue by proposing an intelligent and profitable auction-based approach to allow inter-domains resource allocation

In Broker We Trust: A Double-auction Approach for Resource Allocation in NFV Markets

Network function virtualization (NFV) is an emerging scheme to provide virtualized network function services for next-generation networks. However, finding an efficient way to distribute different resources to customers is difficult. In this paper, we develop a new double-auction approach named DARA that is used for both service function chain routing and NFV price adjustment to maximize the profits of all participants. To the best of our knowledge, this is the first work to adopt a double-auction strategy in this area. The objective of the proposed approach is to maximize the profits of three types of participants: 1) NFV broker; 2) customers; and 3) service providers. Moreover, we prove that the approach is a weakly dominant strategy in a given NFV market by finding the Bayesian Nash equilibrium in the double-auction game. Finally, according to the results of the performance evaluation, our approach outperforms the single-auction mechanism with higher profits for the three types of participants in the given NFV market

A Hybrid SDN-based Architecture for Wireless Networks

With new possibilities brought by the Internet of Things (IoT) and edge computing, the traffic demand of wireless networks increases dramatically. A more sophisticated network management framework is required to handle the flow routing and resource allocation for different users and services. By separating the network control and data planes, Software-defined Networking (SDN) brings flexible and programmable network control, which is considered as an appropriate solution in this scenario.Although SDN has been applied in traditional networks such as data centers with great successes, several unique challenges exist in the wireless environment. Compared with wired networks, wireless links have limited capacity. The high mobility of IoT and edge devices also leads to network topology changes and unstable link qualities. Such factors restrain the scalability and robustness of an SDN control plane. In addition, the coexistence of heterogeneous wireless and IoT protocols with distinct representations of network resources making it difficult to process traffic with state-of-the-art SDN standards such as OpenFlow. In this dissertation, we design a novel architecture for the wireless network management. We propose multiple techniques to better adopt SDN to relevant scenarios. First, while maintaining the centralized control plane logically, we deploy multiple SDN controller instances to ensure their scalability and robustness. We propose algorithms to determine the controllers\u27 locations and synchronization rates that minimize the communication costs. Then, we consider handling heterogeneous protocols in Radio Access Networks (RANs). We design a network slicing orchestrator enabling allocating resources across different RANs controlled by SDN, including LTE and Wi-Fi. Finally, we combine the centralized controller with local intelligence, including deploying another SDN control plane in edge devices locally, and offloading network functions to a programmable data plane. In all these approaches, we evaluate our solutions with both large-scale emulations and prototypes implemented in real devices, demonstrating the improvements in multiple performance metrics compared with state-of-the-art methods

Vehicle as a Service (VaaS): Leverage Vehicles to Build Service Networks and Capabilities for Smart Cities

Smart cities demand resources for rich immersive sensing, ubiquitous communications, powerful computing, large storage, and high intelligence (SCCSI) to support various kinds of applications, such as public safety, connected and autonomous driving, smart and connected health, and smart living. At the same time, it is widely recognized that vehicles such as autonomous cars, equipped with significantly powerful SCCSI capabilities, will become ubiquitous in future smart cities. By observing the convergence of these two trends, this article advocates the use of vehicles to build a cost-effective service network, called the Vehicle as a Service (VaaS) paradigm, where vehicles empowered with SCCSI capability form a web of mobile servers and communicators to provide SCCSI services in smart cities. Towards this direction, we first examine the potential use cases in smart cities and possible upgrades required for the transition from traditional vehicular ad hoc networks (VANETs) to VaaS. Then, we will introduce the system architecture of the VaaS paradigm and discuss how it can provide SCCSI services in future smart cities, respectively. At last, we identify the open problems of this paradigm and future research directions, including architectural design, service provisioning, incentive design, and security & privacy. We expect that this paper paves the way towards developing a cost-effective and sustainable approach for building smart cities.Comment: 32 pages, 11 figure

Game-theoretic Scalable Offloading for Video Streaming Services over LTE and WiFi Networks

This paper presents a game-theoretic scalable offloading system that provides seamless video streaming services by effectively offloading parts of video traffic in all video streaming services to a WiFi network to alleviate cellular network congestion. The system also consolidates multiple physical paths in a cost-effective manner. In the proposed system, the fountain encoding symbols of compressed video data are transmitted through long term evolution (LTE) and WiFi networks concurrently to flexibly control the amount of video traffic through the WiFi network as well as mitigate video quality degradation caused by wireless channel errors. Furthermore, the progressive second price auction mechanism is employed to allocate the limited LTE resources to multiple user equipment in order to maximize social welfare while converging to the epsilon-Nash equilibrium. Specifically, we design an application-centric resource valuation that explicitly considers both the realistic wireless network conditions and characteristics of video streaming services. In addition, the scalability and convergence properties of the proposed system are verified both theoretically and experimentally. The proposed system is implemented using network simulator 3. Simulation results are provided to demonstrate the performance improvement of the proposed system.111Nsciescopu

Convergence of Blockchain and Edge Computing for Secure and Scalable IIoT Critical Infrastructures in Industry 4.0

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this recordCritical infrastructure systems are vital to underpin the functioning of a society and economy. Due to ever-increasing number of Internet-connected Internet-of-Things (IoTs) / Industrial IoT (IIoT), and high volume of data generated and collected, security and scalability are becoming burning concerns for critical infrastructures in industry 4.0. The blockchain technology is essentially a distributed and secure ledger that records all the transactions into a hierarchically expanding chain of blocks. Edge computing brings the cloud capabilities closer to the computation tasks. The convergence of blockchain and edge computing paradigms can overcome the existing security and scalability issues. In this paper, we first introduce the IoT/IIoT critical infrastructure in industry 4.0, and then we briefly present the blockchain and edge computing paradigms. After that, we show how the convergence of these two paradigms can enable secure and scalable critical infrastructures. Then, we provide a survey on state-of-the-art for security and privacy, and scalability of IoT/IIoT critical infrastructures. A list of potential research challenges and open issues in this area is also provided, which can be used as useful resources to guide future research.Engineering and Physical Sciences Research Council (EPSRC

Integration of Blockchain and Auction Models: A Survey, Some Applications, and Challenges

In recent years, blockchain has gained widespread attention as an emerging technology for decentralization, transparency, and immutability in advancing online activities over public networks. As an essential market process, auctions have been well studied and applied in many business fields due to their efficiency and contributions to fair trade. Complementary features between blockchain and auction models trigger a great potential for research and innovation. On the one hand, the decentralized nature of blockchain can provide a trustworthy, secure, and cost-effective mechanism to manage the auction process; on the other hand, auction models can be utilized to design incentive and consensus protocols in blockchain architectures. These opportunities have attracted enormous research and innovation activities in both academia and industry; however, there is a lack of an in-depth review of existing solutions and achievements. In this paper, we conduct a comprehensive state-of-the-art survey of these two research topics. We review the existing solutions for integrating blockchain and auction models, with some application-oriented taxonomies generated. Additionally, we highlight some open research challenges and future directions towards integrated blockchain-auction models