TOT: Trust aware opportunistic transmission in cognitive radio Social Internet of Things

Wang, Xinghan; Zhong, Xiaofeng; Li, Li; Zhang, Sheng; Lu, Renhao; Yang, Tingting

doi:10.1016/j.comcom.2020.08.007

Cited by 14 publications

(7 citation statements)

References 37 publications

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“…Ref. [28] proposes an energy-and trust-aware opportunistic routing approach for the cognitive radio Social Internet of Things (CR-SIoT), leveraging network coding and game-theoretic allocation of trusted channels to enhance the network performance, as validated by extensive simulation results. To improve the social edge service (SES) in the Social Internet of Things (SIoT), Ref.…”

Section: Related Studiesmentioning

confidence: 99%

Reconfigurable-Intelligent-Surface-Enhanced Dynamic Resource Allocation for the Social Internet of Electric Vehicle Charging Networks with Causal-Structure-Based Reinforcement Learning

Zhang,

2024

Future Internet

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Charging stations and electric vehicle (EV) charging networks signify a significant advancement in technology as a frontier application of the Social Internet of Things (SIoT), presenting both challenges and opportunities for current 6G wireless networks. One primary challenge in this integration is limited wireless network resources, particularly when serving a large number of users within distributed EV charging networks in the SIoT. Factors such as congestion during EV travel, varying EV user preferences, and uncertainties in decision-making regarding charging station resources significantly impact system operation and network resource allocation. To address these challenges, this paper develops a novel framework harnessing the potential of emerging technologies, specifically reconfigurable intelligent surfaces (RISs) and causal-structure-enhanced asynchronous advantage actor–critic (A3C) reinforcement learning techniques. This framework aims to optimize resource allocation, thereby enhancing communication support within EV charging networks. Through the integration of RIS technology, which enables control over electromagnetic waves, and the application of causal reinforcement learning algorithms, the framework dynamically adjusts resource allocation strategies to accommodate evolving conditions in EV charging networks. An essential aspect of this framework is its ability to simultaneously meet real-world social requirements, such as ensuring efficient utilization of network resources. Numerical simulation results validate the effectiveness and adaptability of this approach in improving wireless network efficiency and enhancing user experience within the SIoT context. Through these simulations, it becomes evident that the developed framework offers promising solutions to the challenges posed by integrating the SIoT with EV charging networks.

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Section: Related Studiesmentioning

confidence: 99%

Reconfigurable-Intelligent-Surface-Enhanced Dynamic Resource Allocation for the Social Internet of Electric Vehicle Charging Networks with Causal-Structure-Based Reinforcement Learning

Zhang,

2024

Future Internet

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“…CR controllers control the power of CR clients. The intra-based approach involves NSs placed in or above the body which interconnect with a cognitive radio controller within a range of two meters [7,8]. The CRN can be merged with IoT as CRIoT to solve the scarcity problem in IoT.…”

Section: Literature Reviewmentioning

confidence: 99%

Smart Wireless Sensor Technology for Healthcare Monitoring System Using Cognitive Radio Networks

Jabeen

Ashraf

et al. 2023

Sensors

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Programmable Object Interfaces are increasingly intriguing researchers because of their broader applications, especially in the medical field. In a Wireless Body Area Network (WBAN), for example, patients’ health can be monitored using clinical nano sensors. Exchanging such sensitive data requires a high level of security and protection against attacks. To that end, the literature is rich with security schemes that include the advanced encryption standard, secure hashing algorithm, and digital signatures that aim to secure the data exchange. However, such schemes elevate the time complexity, rendering the data transmission slower. Cognitive radio technology with a medical body area network system involves communication links between WBAN gateways, server and nano sensors, which renders the entire system vulnerable to security attacks. In this paper, a novel DNA-based encryption technique is proposed to secure medical data sharing between sensing devices and central repositories. It has less computational time throughout authentication, encryption, and decryption. Our analysis of experimental attack scenarios shows that our technique is better than its counterparts.

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“…TOT, an energy and trust-aware opportunistic transmission strategy for CR-S-IoT, is suggested in (Wang et al, 2020b). Wang et al (2020b), the author developed many forms of flow-oriented forwarding candidate selection algorithms based on optimum stopping theory. In addition, a new trustworthy channel assignment technique based on predicted network gain is created.…”

Section: Trust Management In S-iotmentioning

confidence: 99%

A Comprehensive Survey on Security, Trust Management and Privacy Preservation for Social-Internet-of-Things (S-IoT)

Rahul¹,

Venkatesh²,

Venugopal³

2023

Journal of Computer Science

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The Social Internet of Things (S-IoT) is a new paradigm that evolved with a convergence of social networking concepts and internet of things concepts. This paradigm helps develop intelligent devices and services with higher utility. The new paradigm enriches the social interaction between human's objects, heterogenous social objects interaction, the discovery of service and scalability. In recent years, S-IoT has been researching a hot topic and has drawn the attention of researchers, resulting in research on trust management, privacy preservation, service provisioning and security mechanisms. However, S-IoT faces new research challenges like interoperability, trustworthiness, security threats, scalability, navigability, service discovery and composition. In line with the research trend, this article provides a systematic survey of fundamental concepts of S-IoT and IoT, distinguishable characteristics of S-IoT and IoT and research challenges in S-IoT. This survey thoroughly reviews secure communication mechanisms, privacy-preservation techniques and the trust-evaluation model in S-IoT. Furthermore, we accentuate the privacy-preservation mechanism proposed in the literature for seven years and explored research areas. The holistic survey gives an overview of trust-evaluation models with respect to the service provider's perspective. This article overviews secure communication protocols and architecture in the S-IoT context. Finally, various research gaps, applications of S-IoT and research directions help a researcher to carry out research work in S-IoT.

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TOT: Trust aware opportunistic transmission in cognitive radio Social Internet of Things

Cited by 14 publications

References 37 publications

Reconfigurable-Intelligent-Surface-Enhanced Dynamic Resource Allocation for the Social Internet of Electric Vehicle Charging Networks with Causal-Structure-Based Reinforcement Learning

Reconfigurable-Intelligent-Surface-Enhanced Dynamic Resource Allocation for the Social Internet of Electric Vehicle Charging Networks with Causal-Structure-Based Reinforcement Learning

Smart Wireless Sensor Technology for Healthcare Monitoring System Using Cognitive Radio Networks

A Comprehensive Survey on Security, Trust Management and Privacy Preservation for Social-Internet-of-Things (S-IoT)

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