• Corpus ID: 201637373

Review of the D 2 D Trusted Cooperative Mechanism in Mobile Edge Computing

@inproceedings{Yuan2019ReviewOT,
  title={Review of the D 2 D Trusted Cooperative Mechanism in Mobile Edge Computing},
  author={Jie Yuan and Erxia Li and Chaoqun Kang and Fangyuan Chang and Xiaoyong Li},
  year={2019}
}
Mobile edge computing (MEC) effectively integrates wireless network and Internet technologies and adds computing, storage, and processing functions to the edge of cellular networks. This new network architecture model can deliver services directly from the cloud to the very edge of the network while providing the best efficiency in mobile networks. However, due to the dynamic, open, and collaborative nature of MEC network environments, network security issues have become increasingly complex… 

Figures and Tables from this paper

References

SHOWING 1-10 OF 55 REFERENCES
A Survey on Mobile Edge Networks: Convergence of Computing, Caching and Communications
TLDR
This survey makes an exhaustive review on the state-of-the-art research efforts on mobile edge networks, including definition, architecture, and advantages, and presents a comprehensive survey of issues on computing, caching, and communication techniques at the network edge.
An Efficient Message-Authentication Scheme Based on Edge Computing for Vehicular Ad Hoc Networks
TLDR
A novel edge-computing concept is introduced into the message-authentication process of VANETs that can efficiently authenticate messages from nearby vehicles and broadcast the authentication results to the vehicles within its communication range, thereby reducing redundant authentication and enhancing the efficiency of the entire system.
Dynamic Trustworthiness Overlapping Community Discovery in Mobile Internet of Things
TLDR
This paper proposes a detection scheme for dynamic trustworthiness overlapping community, called D2-TOC, which employs evidence-based data between node pairs to construct the trustworthiness relationships between devices and the network model of mobile IoT, which can provide the security guarantee for data interaction from the start.
Research on Dynamic Trust Model for Large Scale Distributed Environment
TLDR
The research work indicates that the dynamic nature of trust creates the biggest challenge in measuring trust and predicting trustworthiness, so the future work will focus on the theoretical research of dynamic trust relationships to present a solid theoretical foundation for the practical applications.
Mobile Edge Computing: A Survey
TLDR
The definition of MEC, its advantages, architectures, and application areas are provided; where the security and privacy issues and related existing solutions are also discussed.
A multi-source feedback based trust calculation mechanism for edge computing
  • Jie Yuan, Xiaoyong Li
  • Computer Science
    IEEE INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)
  • 2018
TLDR
This work adopts lightweight trust evaluating mechanism for cooperations of network devices in edge computing, which is suitable for large-scale edge computing because it facilitates low-overhead trust computing algorithms.
A Reliable and Lightweight Trust Computing Mechanism for IoT Edge Devices Based on Multi-Source Feedback Information Fusion
TLDR
A reliable and lightweight trust mechanism is originally proposed for IoT edge devices based on multi-source feedback information fusion based on objective information entropy theory, which can overcome the limitations of traditional trust schemes.
Distributed Reputation Management for Secure and Efficient Vehicular Edge Computing and Networks
TLDR
A distributed reputation management system (DREAMS) is proposed, wherein VEC servers are adopted to execute local reputation management tasks for vehicles, and the effectiveness of the reputation-based resource allocation algorithm is demonstrated.
Secure Social Networks in 5G Systems with Mobile Edge Computing, Caching, and Device-to-Device Communications
TLDR
This article presents a social trust scheme that enhances the security of MSNs with MEC, caching, and D2D and applies a novel deep reinforcement learning approach to automatically make a decision for optimally allocating the network resources.
...
...