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In order to ensure efficient data transmission from satellites to ground stations (GSs), resource allocation schemes must be designed. In cases where direct data transmission from satellites to GSs is not possible due to a dynamic network topology and limited contact time, efficient relay selection or route selection schemes should be employed. This paper considers a satellite communication network in which a number of source low earth orbit(SLEO) satellites are attempting to transmit their data flows to the designated GSs. To improve the transmission performance of the data flows, one geosynchronous earth orbit (GEO) satellite and a number of relay LEO (RLEO) satellites in the network are used as relays. To maximize energy efficiency, a joint route selection and resource allocation mechanism is proposed. The energy cost of the system, which is the sum of the energy cost of the SLEO satellites and the RLEO satellites, is used to formulate the joint route selection and resource allocation as a system energy cost minimization problem. Since the original optimization problem is NP hard, it is transformed into three subproblems: inter-satellite power allocation, satellite-ground power allocation, and route selection. These subproblems are solved using a greedy algorithm, the Lagrange dual method, and a matching-based heuristic algorithm, respectively. The numerical results demonstrate the effectiveness of the proposed scheme.

With the development of artificial intelligence of things (AIoT), multi-access edge computing (MEC) becomes a key enabler to migrate cloud services to edge clients. In comparison to traditional cloud computing techniques, MEC is characterized with low transmission latency, good flexibility, adaptability and robustness. Nevertheless, traditional resource allocation methods are difficult to meet the requirements of achieving a ubiquitous, pervasive, and intelligent computation offloading strategy in high-dynamic network environments. In this article, we construct an edge intelligence-enabled cloud-edge-client collaborative network structure, and conceive a model-aided multi-agent deep deterministic policy gradient (MA2DDPG) computation offloading framework relying on both centralized training and distributed execution. Simulation results corroborate that our proposed decentralized resource orchestration platform significantly reduces the energy consumption and the transmission latency against state-of-the-art methods. Finally, we highlight open challenges and potential solutions.

Recently, content-centric networking (CCN) has become a hot research topic for the diffusion of contents over the Internet. Most existing works on CCN focus on the improvement of network resource utilization. Consequently, the energy consumption aspect of CCN is largely ignored. In this paper, we propose a distributed energy-efficient in-network caching scheme for CCN, where each content router only needs locally available information to make caching decisions considering both caching energy consumption and transport energy consumption. We formulate the in-network caching problem as a non-cooperative game. Through rigorous mathematical analysis, we prove that pure strategy Nash equilibria exist in the proposed scheme, and it always has a strategy profile that implements the socially optimal configuration, even if the routers are self-interested in nature. Simulation results are presented to show that the distributed solution is competitive to the centralized scheme, and has superior performance compared to other popular caching schemes in CCN. Besides, it exhibits a fast convergence speed when the capacity of content routers varies.

As the front line of defense, user authentication is crucial for integrity and confidentiality. Mobile ad hocnetworks (MANETs) impose a number of non‐trivial challenges to user authentication such as lack of central coordination and limited resources. In high security MANETs, continuous authentication is desirable so that a system can be monitored for the duration of the session to reduce the vulnerability. Biometrics provides some possible solutions to the authentication problem in MANETs, since it has direct connection with user identity. In this paper, we introduce some biometric technologies and their applications in the authentication problem. Multimodal biometrics can be used to exploit the benefits of one biometric while mitigating the inaccuracies of another. We propose an optimal multimodal biometric‐based continuous authentication scheme in MANETs. Some numerical results show the effectiveness of the proposed scheme. Copyright © 2007 John Wiley & Sons, Ltd.

With the tremendous advances in the field of information and communications technology (ICT), and the emergence of new applications, such as 4K/8K, AR/VR, Internet of Things, and Industrial Internet and so on, the traditional Internet has faced severe challenges on scalability, flexibility, controllability, mobility and security and so on. In order to cope with these challenges, numerous promising future Internet architectures and techniques, such as software-defined networking (SDN), information-centric networking (ICN), and network virtualization (NV), have emerged over the last few years and been attracted a lot of attention.