Analysis of the cascading failure for scale-free networks based on a multi-strategy evolutionary game. (July 2020)

• Record Type: Journal Article
• Authors: Dui, Hongyan; Meng, Xueyu; Xiao, Hui; Guo, Jianjun
• Is Part Of: Reliability engineering & system safety. Volume 199(2020)
• Publication Date: 2020-07
• Subjects: Cascading failure -- Reliability -- Multi-state systems -- Scale-free networks -- Evolutionary games; Reliability (Engineering) -- Periodicals; System safety -- Periodicals; Industrial safety -- Periodicals; Fiabilité -- Périodiques; Sécurité des systèmes -- Périodiques; Sécurité du travail -- Périodiques; 620.00452
• DOI: 10.1016/j.ress.2020.106919
• Languages: English
• ISSNs: 0951-8320

Abstract

Highlights: The cascading failure in a scale-free network is analyzed. The multi-strategy evolutionary game is used in failure analysis. The game analysis considers incentive and punishment mechanism. Useful insights are gained from the analysis of a scale-free network. Abstract: This research studies the cascading failure in a scale-free network from the perspective of the payoffs of nodes in a multi-strategy evolutionary game. Different from the traditional methods that eliminate nodes randomly or deliberately, this method starts from the payoff of the more general evolutionary game phenomena in reality, and eliminates the nodes with negative payoff and the edges connected with the failed nodes. By eliminating the failure nodes in the scale-free network, we can analyze the influence of the cascade failure on the topological structure of complex networks and discuss the evolutionary direction of the game. Furthermore, the evolutionary game of a ternary strategy considering incentive and punishment mechanism is analyzed, and the influence of the number of law enforcers on the evolutionary game is discussed. We demonstrate the proposed method by conducting a simulation study on a scale-free network. The results show that the aggregation and invulnerability coefficients of the scale-free network are on the rise. Thus, we can conclude that the small group of the network has a positive resistance to the external environment.