A Robust Networking Model With Quantum Evolution for Internet of Things

被引:1
|
作者
Zhang, Songwei [1 ]
Qiu, Tie [1 ]
Chen, Ning [1 ]
Ning, Huansheng [2 ]
Han, Min [3 ]
Liu, Xingcheng [4 ]
机构
[1] Tianjin Univ, Coll Intelligence & Comp, Sch Comp Sci & Technol, Tianjin 300350, Peoples R China
[2] Univ Sci & Technol Beijing, Sch Comp & Commun Engn, Beijing 100083, Peoples R China
[3] Dalian Univ Technol, Key Lab Intelligent Control & Optimizat Ind Equipm, Minist Educ, Dalian 116024, Peoples R China
[4] Sun Yat Sen Univ, Sch Elect & Informat Technol, Guangzhou 510006, Peoples R China
来源
IEEE NETWORK | 2024年 / 38卷 / 02期
基金
中国国家自然科学基金;
关键词
Network topology; Qubit; Logic gates; Biological cells; Robustness; Encoding; Internet of Things; Sensors; Quantum computing; Statistics; SCALE-FREE NETWORKS;
D O I
10.1109/MNET.135.2200597
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The Internet of Things (IoT), which includes massive energy-limited sensor nodes, has become the foundation of smart city. Improving the ability of network topology to resist node cascading failures, namely robustness, is the key for IoT to provide stable data-aware services for upper-layer applications. However, the robustness optimization problem of complex topology is an NP-hard problem and cannot be optimally solved in polynomial time. The existing researches try to find the approximate solution by heuristic algorithms, but there are problems of slow convergence and easy to fall into local optimum. Quantum computing has more diverse search spaces due to the existence of quantum superposition states, which can jump out of the local optimum. Therefore, this paper firstly combines quantum computing with topology robustness evolution, and proposes a robust networking model based on quantum evolution. By using the quantum encoding, we design a novel quantum measurement method to collapse quantum states towards a more robust network topology. The experimental results show that our model can jump out of the local optimum with fewer population individuals and achieve higher robustness.
引用
收藏
页码:218 / 224
页数:7
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