This Thesis addresses the complexity of engineering approaches for fault-tolerant mobile networks. The problem originates from conventional IT systems, where, despite the maturity of software development practices, fault tolerance often does not receive adequate attention. This perspective is extended even further to the field of cooperative mobile network solutions. The primary goal of this research is to advance efficient, fault-tolerant solutions for cooperative mobile networks and provide insights into the efficiency of fault-tolerant consensus, exploring its various forms and practical implementation strategies. The research specifically focuses on measuring the efficiency of eventual and synchronous leader election algorithms in cooperative UAV patrol missions. Insights are provided into the characteristics of the eventual algorithm’s convergence process, the effects of different timeout strategies on mission quality, the dynamic characteristics of cooperative UAV networks, and the impact of AI accuracy and performance on mission outcomes. Additionally, the consensus problem is analyzed in the context of smart vehicle cooperative crash avoidance scenarios, exploring whether the Byzantine error model is necessary in V2V communications. A method for modeling and measuring fail-stop flooding consensus performance in this scenario is developed, and the results are analyzed. To achieve these objectives, a novel, real-time, Docker-based simulation was designed and developed. A queuing network model was created to analyze the dynamic characteristics of the cooperative UAV solution, while a custom NS3 simulation was developed to evaluate consensus in V2V scenarios.