Blockchain and AI Empowered Trust-Information-Centric Network for Beyond 5G

Yan

IEEE Commun. Surv. Tutorials

et al. 2022

Heterogeneous networks (HetNets) merge different types of networks into an integrated network system, which has become a hot research area in recent years towards nextgeneration communication networks. HetNets aim to effectively exploit network resources and provide seamless connectivity for heterogeneous objects. Unlike other networks, HetNets hold such characteristics as heterogeneity, openness, distribution, multidomain involvement, thus are susceptible to various security threats and attacks. Traditional security approaches are not sufficiently effective in defending against them. With extensive study and practice, researchers found that trust models offer effective measures to enhance the security and reliability of a network system. However, there still lacks a comprehensive survey on the recent advances of trust models in HetNets. In this paper, we fill this gap. We first retrospect the history of HetNets research and introduce important concepts related to trust. Then, we propose a set of criteria that a sound trust model should satisfy, which can also serve as a measure to evaluate the quality of a trust model, i.e., Quality of Trust (QoT). We provide taxonomies of trust models and their applications, and continue with a thorough review on trust models in HetNets. Based on the review, a list of open issues is highlighted, and corresponding future research directions are suggested to advance the research on trustworthy HetNets.

Section: A Decision Models In Hetnetsmentioning

confidence: 99%

“…Nevertheless, it is difficult to update them frequently in the face of new and diverse contexts. RL becomes promising as it can make optimal decisions (e.g., selecting a routing path [120]) intelligently due to its strong learning ability [166]…”

Section: A Decision Models In Hetnetsmentioning

confidence: 99%

A Survey on Trust Models in Heterogeneous Networks

Yan

IEEE Commun. Surv. Tutorials

et al. 2022

“…It is characterized by name-based data retrieval and in-network data caching, allowing users to retrieve data from nearby copyholders. ICN separates the content from the location and provides services such as storage and multi-party communication through the publish/subscribe paradigm, so that people's attention has shifted to the rapid acquisition of information regardless of the location of information storage [48]- [50]. By converting raw data into useful information, this layer introduces self-awareness to the physical components of the Internet of intelligence systems.…”

Section: B Architecture Of Internet Of Intelligencementioning

confidence: 99%

Internet of Intelligence: A Survey on the Enabling Technologies, Applications, and Challenges

Tang,

Yu,

Xie

et al. 2022

Preprint

The Internet of intelligence is conceived as an emerging networking paradigm, which will make intelligence as easy to obtain as information. This paper provides an overview of the Internet of intelligence, focusing on motivations, architecture, enabling technologies, applications, and existing challenges. This can provide a good foundation for those who are interested to gain insights into the concept of the Internet of intelligence and the key enablers of this emerging networking paradigm. Specifically, this paper starts by investigating the evolution of networking paradigms and artificial intelligence (AI), based on which we present the motivations of the Internet of intelligence by demonstrating that networking needs intelligence and intelligence needs networking. We then present the layered architecture to characterize the Internet of intelligence systems and discuss the enabling technologies of each layer. Moreover, we discuss the critical applications and their integration with the Internet of intelligence paradigm. Finally, some technical challenges and open issues are summarized to fully exploit the benefits of the Internet of intelligence.

“…Letaief et al investigate the AI-empowered 6G wireless communication, where AI-enabled technologies, methodologies, and key trends for 6G design and optimization are discussed [28]. The work in [29] proposes an AI and blockchain empowered trust-information centric network architecture for B5G, where deep reinforcement learning (DRL) is utilized to calculate the content credibility. The authors of [30] propose a joint power transfer and AI design for IoT to realize blockchain-based energy-knowledge trading.…”

Section: Artificial Intelligence For 6gmentioning

confidence: 99%

Leveraging AI and Intelligent Reflecting Surface for Energy-Efficient Communication in 6G IoT

Pan¹,

Wu²,

Zheng³

et al. 2020

Preprint

Self Cite

The ever-increasing data traffic, various delay-sensitive services, and the massive deployment of energy-limited Internet of Things (IoT) devices have brought huge challenges to the current communication networks, motivating academia and industry to move to the sixth-generation (6G) network. With the powerful capability of data transmission and processing, 6G is considered as an enabler for IoT communication with low latency and energy cost. In this paper, we propose an artificial intelligence (AI) and intelligent reflecting surface (IRS) empowered energy-efficiency communication system for 6G IoT. First, we design a smart and efficient communication architecture including the IRS-aided data transmission and the AI-driven network resource management mechanisms. Second, an energy efficiency-maximizing model under given transmission latency for 6G IoT system is formulated, which jointly optimizes the settings of all communication participants, i.e. IoT transmission power, IRS-reflection phase shift, and BS detection matrix. Third, a deep reinforcement learning (DRL) empowered network resource control and allocation scheme is proposed to solve the formulated optimization model. Based on the network and channel status, the DRL-enabled scheme facilities the energy-efficiency and low-latency communication. Finally, experimental results verified the effectiveness of our proposed communication system for 6G IoT.