Employing topology modification strategies in scale-free IoT networks for robustness optimization

被引:2
作者
Khan, Zahoor Ali [1 ]
Awais, Muhammad [2 ]
Alghamdi, Turki Ali [3 ]
Javaid, Nadeem [4 ]
机构
[1] Higher Coll Technol, Comp Informat Sci, Fujairah 4114, U Arab Emirates
[2] COMSATS Univ Islamabad, Dept Elect & Comp Engn, Islamabad 44000, Pakistan
[3] Umm Al Qura Univ, Coll Comp & Informat Syst, Dept Comp Sci, Mecca 21955, Saudi Arabia
[4] COMSATS Univ Islamabad, Dept Comp Sci, Islamabad 44000, Pakistan
关键词
Assortativity; Entropy; Hill climbing algorithm; Random and malicious attacks; Robustness; Simulated annealing algorithm; Scale-free IoT networks; COMPLEX NETWORK; ALGORITHM; INTERNET; SCHEME; MODEL;
D O I
10.1007/s00607-024-01273-2
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Nowadays, the Internet of Things (IoT) networks provide benefits to humans in numerous domains by empowering the projects of smart cities, healthcare, industrial enhancement and so forth. The IoT networks include nodes, which deliver the data to the destination. However, the network nodes' connectivity is affected by the nodes' removal caused due to the malicious attacks. The ideal plan is to construct a topology that maintains nodes' connectivity after the attacks and subsequently increases the network robustness. Therefore, for constructing a robust scale-free network, two different mechanisms are adopted in this paper. First, a Multi-Population Genetic Algorithm (MPGA) is used to deal with premature convergence in GA. Then, an entropy based mechanism is used, which replaces the worst solution of high entropy population with the best solution of low entropy population to improve the network robustness. Second, two types of Edge Swap Mechanisms (ESMs) are proposed. The Efficiency based Edge Swap Mechanism (EESM) selects the pair of edges with high efficiency. While the second ESM named as EESM-Assortativity, transforms the network topology into an onion-like structure to achieve maximum connectivity between similar degree network nodes. Further, Hill Climbing (HC) and Simulated Annealing (SA) methods are used for optimizing the network robustness. The simulation results show that the proposed MPGA Entropy has 9% better network robustness as compared to MPGA. Moreover, both the proposed ESMs effectively increase the network robustness with an average of 15% better robustness as compared to HC and SA. Furthermore, they increase the graph density as well as network's connectivity.
引用
收藏
页码:1845 / 1872
页数:28
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