Efficient HIP-based approach to ensure lightweight end-to-end security in the internet of things

2015 ◽  
Vol 91 ◽  
pp. 26-45 ◽  
Author(s):  
Somia Sahraoui ◽  
Azeddine Bilami
Keyword(s):  
Internet Of Things ◽  
The Internet ◽  
End To End ◽  
The Internet Of Things

End-to-end secure group communication for the Internet of Things

2021 ◽  
Vol 58 ◽  
pp. 102772
Author(s):  
André Lizardo ◽  
Raul Barbosa ◽  
Samuel Neves ◽  
Jaime Correia ◽  
Filipe Araujo
Keyword(s):  
Internet Of Things ◽  
Group Communication ◽  
The Internet ◽  
Secure Group Communication ◽  
End To End ◽  
The Internet Of Things

scholarly journals Research on Cooperative Communication Strategy and Intelligent Agent Directional Source Grouping Algorithms for Internet of Things

2019 ◽  
Vol 11 (11) ◽  
pp. 233
Author(s):  
Zou ◽  
Zhang ◽  
Yi
Keyword(s):  
Internet Of Things ◽  
Cooperative Communication ◽  
Intelligent Agent ◽  
The Internet ◽  
End To End Delay ◽  
Multi Agent ◽  
End To End ◽  
Directional Source ◽  
The Internet Of Things ◽  
Cooperative Nodes

In order to improve the network layer of the Internet of things to improve transmission reliability, save time delay and energy consumption, the Internet of things cooperative communication and intelligent agent technology were studied in this paper. In cooperative communication, a new cooperative communication algorithm KCN (k-cooperative node), and a reliability prediction model are proposed. The k value is determined by the end-to-end reliability. After k cooperative nodes are selected, other nodes enter dormancy. In aggregate traffic allocation, game theory is used to model the traffic equilibrium and end-to-end delay optimization scenarios. In practice, the optimal duty cycle can be calculated, which makes some cooperative nodes enter an idle state to save energy. Under the premise of guaranteeing end-to-end delay, it is shown that the reliability of the proposed KCN algorithm is better than that of the other existing routing protocols. In the aspect of intelligent agent, a directional source grouping algorithm D-MIP is proposed. This algorithm studies the routing problem of multi-agent parallel access to multiple source nodes. A directed source packet multi-agent routing planning algorithm is proposed. The iterative algorithm of each source node is limited to a sector, and the optimal intelligent agent route is obtained by selecting an appropriate angle. Compared with other algorithms, it is shown through a lot of simulated results that energy consumption and time delay has been saved by the proposed D-MIP algorithm.

scholarly journals Dynamic Control Architecture Based on Software Defined Networking for the Internet of Things

2021 ◽  
Vol 13 (5) ◽  
pp. 113
Author(s):  
Michele Bonanni ◽  
Francesco Chiti ◽  
Romano Fantacci ◽  
Laura Pierucci
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Real Time ◽  
Controller Design ◽  
Time Estimation ◽  
Software Defined Networking ◽  
Life Time ◽  
The Internet ◽  
End To End ◽  
The Internet Of Things

Software Defined Networking (SDN) provides a new perspective for the Internet of Things (IoT), since, with the separation of the control from the data planes, it is viable to optimise the traditional networks operation management. In particular, the SDN Controller has a global vision of the network of sensors/actuators domain, allowing real-time network nodes and data flows reconfiguration. As a consequence, devices, usually facing limited communications and computing resources, are relieved of the route selection task in a distributed and, thus, suboptimal way. This paper proposes a SDN-IoT architecture, specifically focusing on the Controller design, which dynamically optimises in real time the end-to-end flows delivery. In particular, the dynamic routing policy adaptation is based on the real-time estimation of the network status and it allows jointly minimising the end-to-end latency and energy consumption and, consequently, to improve the network life time. The performance of the proposed approach is analysed in terms of the average latency, energy consumption and overhead, pointing out a better behaviour in comparison with the existing distributed approaches.

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