In the 6G network era, energy-efficient computing means higher resource utilization and lower energy consumption. The traditional computing model regards the network as a transmission pipeline and has not fully explored the potential of network devices. In-network computing is a new type of computing model that delegates application-layer processing functions to the network data plane. The traffic can be processed during transmission, and the amount of traffic is reduced. As a result, the computing pressure and energy consumption of the cloud-side system is reduced. Most of the existing in-network computing models are based on programable network devices. Due to the limitations of the TCP/IP protocol, these methods can only handle application messages at the packet level. We propose an energy-efficient in-network computing paradigm for 6G that integrates network functions into a general computing platform instead of delegating computing tasks to network devices. The computing platform that integrates network functions replaces traditional network devices and acts as a network node. Unlike traditional network devices, the network node provides a unified operating environment for application tasks through hypervisors and containers. Therefore, data processing tasks can be deployed on cloud servers or on network nodes. The network controller schedules the processing tasks to execute on the network node passing the application traffic. The experimental results show that our paradigm can make full use of the computing resources of network nodes and significantly reduce the computing pressure, network transmission overhead and energy consumption of the data center.

The incredible development of Internet of things technology promotes the integration of application systems, which enable people to enjoy the convenience of multiple application services through a single intelligent device or terminal. In order to implement value exchange and information sharing between different applications, cross-domain access is inevitable. In order to prevent illegal access, identity authentication is necessary before the terminal accesses the service. Because of the need to introduce a trusted third party, the traditional centralized authentication model not only destroys the autonomy and flexibility of the application system, but also causes issues such as single point of failure and hidden dangers of unilateral control. This paper proposes an identity-based cross-domain authentication scheme for the Internet of Things. This scheme uses the Blockchain as a decentralized trust anchor instead of the traditional certificate of authority, and uses the identity-based self-authentication algorithm to replace the traditional PKI authentication algorithm. The scheme proposed in this paper implements a decentralized authentication model, which can guarantee the autonomy and initiative of the security domain.

The rapid development of the Industrial Internet of Things (IIoT) has led to the explosive growth of industrial control data. Cloud computing-based industrial control models cause vast energy consumption. Most existing solutions try to reduce the overall energy consumption by optimizing task scheduling and disregard how to reduce the load of computing and data transmission. On the other hand, due to the rigid architecture and limited capability of the edge computing platform, solutions based on edge computing urgently need to be deeply optimized in terms of data processing and energy efficiency. This paper proposes Deep-Green, which is a dispersed energy-efficient computing paradigm for the Industrial Internet of Things. The core idea of Deep-Green is to realize the joint optimization of computing and network resources by merging data transmission and data processing. Deep-Green provides a novel method of constructing an IIoT edge layer based on a dispersed computing platform. By using an energy-efficiency task scheduling algorithm, container service technology, and programmable protocol stack, the data processing service is dispatched from the cloud side to the on-site controller. Therefore, the data from manufacturing equipment can be processed while they are forwarded by the on-site industrial controller. The results of experiments show that Deep-Green can not only effectively reduce the computing load and communication overhead of the cloud-side server, but also simplify the network topology and the number of devices at the edge layer of the IIoT.

With the rapid development of mobile and wireless technologies, the industrial manufacturing sector has entered the era of automation. The proliferation of mobile devices, sensor networks, and remote monitoring systems enables factory equipment to be more flexibly connected and controlled. However, the trend towards industrial networks also brings new challenges. Industrial control systems (ICSs) and programmable logic controllers (PLCs) are more susceptible to hacker attacks and interference. Honeypoints have been developed to protect ICSs from addressing these threats, including potential internal attacks. Honeypoints are active deception systems that mitigate the limitations of conventional defense mechanisms, which successfully entice and neutralize internal enemies. This paper presents the PLC Honeypoint Communication Generator (PHCG), enhancing honeypoint protective capabilities in industrial IoT systems. Using an automated construction process, PHCG provides a convenient and efficient deployment method, ensuring quick and effective functioning. The functionality of a PLC relies on a data generation model trained on PLC response data. This model allows PHCG to imitate genuine PLC responses accurately when given authorized commands. The experimental results illustrate the adaptability of information produced by PHCG in different communication processes, with satisfactory timescales for both model training and data generation.

The fifth-generation mobile communication technology (5G) provides high-bandwidth and low-latency data channels for massive IoT terminals to access the core business network. At the same time, it also brings higher security threats and challenges. Terminal identity authentication is an important security mechanism to ensure the core business network; however, most of the existing solutions adopt a centralized authentication model. Once the number of authentication requests exceeds the processing capacity of the authentication center service, it will cause authentication request congestion or deadlock. The decentralized authentication model can effectively solve the above problems. This article proposes a decentralized IoT authentication scheme called A² Chain. First, A² Chain uses edge computing to decentralize the processing of authentication requests and eliminate the burden on authentication services and the network. Second, to implement cross-domain identity verification of IoT devices, A² Chain uses blockchain, and sidechain technologies are used to securely share the identity verification information of IoT devices. Additionally, A² Chain replaces public key infrastructure (PKI) algorithm with identity-based cryptography (IBC) algorithm to eliminate the management overhead caused by centralized authentication model.