The paper by Réka Albert, Hawoong Jeong, and Albert-László Barabási explores the error and attack tolerance of complex networks, focusing on scale-free networks. These networks, which include systems like the World Wide Web, Internet, and social networks, exhibit a high degree of robustness against random failures but are highly vulnerable to targeted attacks. The authors compare two types of network models: exponential networks, characterized by a Poisson distribution of node degrees, and scale-free networks, characterized by a power-law distribution. They find that while exponential networks show a monotonically increasing diameter with node removal, scale-free networks maintain their diameter even under significant node removal. However, scale-free networks are highly susceptible to attacks, where the removal of highly connected nodes can rapidly increase the diameter and fragment the network. The study also examines the fragmentation of networks under random failures and attacks, noting that exponential networks exhibit a threshold-like behavior, while scale-free networks remain largely intact under random failures but break apart under targeted attacks. The findings highlight the trade-off between error tolerance and attack survivability in complex networks, with implications for the design and security of communication systems.The paper by Réka Albert, Hawoong Jeong, and Albert-László Barabási explores the error and attack tolerance of complex networks, focusing on scale-free networks. These networks, which include systems like the World Wide Web, Internet, and social networks, exhibit a high degree of robustness against random failures but are highly vulnerable to targeted attacks. The authors compare two types of network models: exponential networks, characterized by a Poisson distribution of node degrees, and scale-free networks, characterized by a power-law distribution. They find that while exponential networks show a monotonically increasing diameter with node removal, scale-free networks maintain their diameter even under significant node removal. However, scale-free networks are highly susceptible to attacks, where the removal of highly connected nodes can rapidly increase the diameter and fragment the network. The study also examines the fragmentation of networks under random failures and attacks, noting that exponential networks exhibit a threshold-like behavior, while scale-free networks remain largely intact under random failures but break apart under targeted attacks. The findings highlight the trade-off between error tolerance and attack survivability in complex networks, with implications for the design and security of communication systems.