Titlebook: Robustness Optimization for IoT Topology; Tie Qiu,Ning Chen,Songwei Zhang Book 2022 The Editor(s) (if applicable) and The Author(s), under

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濃縮

Endometrium

Future Research Directions,t can be processed. Furthermore, in industrial applications, we mainly focus on Industrial Internet of Things (IIoT), smart city, and Underwater Internet of Things (UIoT), which play vital roles in supporting communication services based on robust network topology.

行為

Introduction,he breakthrough in topology optimization through analyzing the characteristics of the IoT topology. In addition, this chapter also compares different attack strategies for network topology, which provides a targeted optimization direction for topology robustness.

完成才會征服

Preliminaries of Robustness Optimization,thms based on small world and scale-free network models. Before optimizing network topology, we should know the definition of robustness and what is important for network topology. Nevertheless, robustness optimization algorithms are essential for IoT applications to provide robust communication sup

主講人

暗語

certain

Robustness Optimization Based on Swarm Intelligence,ms are easy to fall into the local optimum and cannot obtain the global optimum. The heuristic algorithm based on swarm intelligence can find an approximate optimal solution in polynomial time, which can meet the requirements of constructing a robust topology. In the swarm intelligence algorithm, an

aggrieve

Robustness Optimization Based on Multi-Objective Cooperation,rifies that the multi-sink network has better performance and can avoid the energy holes. However, in the 5. scenario, large-scale IoT devices are deployed densely to increase the peak value of traffic. This poses a greater challenge to the optimization of the IoT topology. The improvement of a sing

Gourmet

Robustness Optimization Based on Self-Learning,enetic evolution or swarm intelligence have a long running time when the large-scale nodes are deployed in a scenario. In order to further reduce the time for topology construction, this chapter studies the application of artificial intelligence in topology to obtain a robust topology deployment mod