It is the overriding trend of the present-day world that traditional systems and mobile devices are currently transforming into intelligent systems and smart devices. Against this backdrop, cyber-physical systems (CPSs) and Internet-of-Things (IoT) emerge as the times require. To achieve the parallel interactions between the human world and the computer network, IoT along with wireless mobile communication and computing open up some future opportunities as well as challenges for constructing a novel cyber-physical-social system (CPSS) that takes human factors into account during the system operation and management. In this article, a brief comprehensive survey is provided on some of the current research work that contributes to enabling CPSSs. Some crucial aspects of CPSSs are identified, including: the development from CPSs to CPSSs, architecture design, applications, standards, real-world case studies, enabling techniques and networks for CPSSs. To lay a foundation for the development of the upcoming smart world, we further propose a virtualization architecture and an integrated framework of caching, computing and networking for CPSSs. Simulations verify the performance improvement of the proposals. At last, some research issues with challenges and possible solutions are unearthed for researchers in the related research areas.

In this letter, we develop a novel layered physical layer security model to secure multiple messages simultaneously. It maintains a hierarchical security structure, in which each message transmitted from the base station has a security level, and each user in the network has a security clearance correspondingly. Focusing on the basic two-layer unicast system, we propose an artificial-noise-aided optimal beamforming scheme to maximize the higher level information security performance while adhering to the low-level information secrecy rate constraint. Due to the nonconvexity of the problem formulated, a successive convex approximation-based algorithm is proposed to earn a safe convex approximation of the original. Afterward, a low-complexity zero-forcing beamforming scheme is proposed to achieve high efficiency by reducing the computational complexity. Simulation results validate the superiority of our schemes on the promotion of the overall secrecy performance.

In this paper, we propose a novel layered physical layer security model, which is the extension of the traditional physical layer security to the domain of multiple-layer information security. It has a hierarchical information security structure that every transmitted message has a security level, while every user has a security clearance. Users can only decode the messages with security levels lower than or equal to their clearance, otherwise they will be deemed as eavesdroppers. Based on the framework of the layered information security and assuming perfect channel state information of all users, an artificial-noise-aided optimal beamforming scheme is proposed to minimize the total transmit power at the base station, while satisfying the minimum secrecy rate requirements of all secret messages. Due to the intrinsical complexity of the formulated nonconvex problem, a safe and convex reformulation based on the first-order Taylor series expansion method is proposed to generate a tractable approximation. A successive convex approximation-based algorithm is then proposed, which solves a series of second-order cone problems with convergence to the stationary point of the original problem. We also consider the imperfect channel state information case, and then propose a worst-case robust design to overcome the influence of channel uncertainties. Semi-definite relaxation method and S-procedure are utilized to get a computationally efficient lower bound of the intractable power minimization problem. Moreover, we investigate the application of the suboptimal zero-forcing-based beamforming scheme in the system to tradeoff the achievable performance and the computational complexity. Simulation results are provided to demonstrate the effectiveness of our proposed schemes.

This paper investigates a joint resource allocation for ultra-reliable and low-latency radio access networks (URLLRANs) with edge computing. Compared with conventional networks, URLLRANs have more restrictive latency and reliability requirements, and always feature short packet communications. It is a challenging work to provide edge computing services in URLLRANs, since the processing and transmission delay as well as packet loss during computation and communications should all be taken into considerations. Along these lines, to specify the trade-off between latency and reliability, this paper defines computation rates and transmission rates for short packets. Different from the existing work, the proposal takes effective information as well as energy consumption as performance metrics based on the definition. The packet request rates, computation latency, service rates, communication power, blocklength, and transmission information amounts are jointly optimized to reduce energy consumption and meanwhile generate more effective information for both the computation system and the communication system. To solve the NP-hard problem, the locally optimal solution and global optimal solution are both derived. Simulation results validate the performance advantage of the proposal and also indicate that the locally optimal solution can greatly reduce the computation complexity with only a small performance loss when compared with the global optimal solution.

To promote future intelligent systems, a novel cyber-physical-social smart system powered by the Internet of Things is presented in this paper, where wireless network virtualization is adopted to enhance the diversity and the flexibility of the service operation and the system management. Based on the presented system, a robust energy-efficient resource allocation scheme is proposed to guarantee the outage probability requirements of controllers and actuators while realizing the maximization of the system energy efficiency. Different from the existing works, imperfect channel state information is studied for energy-efficient resource allocation in cyber-physical-social smart systems. To effectively handle the formulated optimization problem, the concept of virtual devices is introduced to equivalently reformulate the original problem. Afterwards, the probabilistic mixed problem is approximately transformed into a non-probabilistic problem though outage probability analyses. After the transformation, the optimization problem can be decomposed into power allocation and channel allocation, where an iterative algorithm for power allocation is adopted to maximize the system energy, and a heuristic greedy algorithm is presented to schedule sensors and actuators on different sub-channels based on the obtained power allocation results. Simulation results demonstrate the convergency of the proposed algorithm and the advantages of the proposed scheme.

To support the massive content delivery, a novel virtualized heterogeneous networks framework is proposed to enable content transcoding, caching and multicast. In addition, a virtual multi-resources allocation problem is formulated to jointly optimize the utilities of computing, caching, and communication for the proposed framework. Simulations are conducted to show the effectiveness of the proposed scheme.