Optimizing the Performance and Secure Distributed Wireless Network in Unreliable D-NCS using CGA?

Distributed network-control-systems (D-NCS) are a network structure and components that are capable of integrating sensors, actuators, communication, and control algorithms to suit real-time applications. Distributed networked control systems (D-NCS) are vulnerable to various network attacks when the network is not secured, thus, D-NCS must be well protected with security mech- anisms (e.g., cryptography), which may adversely affect the dynamic performance of the D-NCS because of limited system resources. This paper is concerned with the problem of designing a secure distributed control methodology that is capable of performing a secure consensus computation in a D-NCS in the presence of misbehaving nodes. It embeds four phases (detection, mitigation, identification, and update) into the distributed control process. We use a wireless network based, robot navigation path tracking system called Intelligent Space (iSpace) as a D-NCS test bed in this paper. Network security algorithms DES and 3DES are integrated with the application to secure the sensitive information flow. Then, the paper proposes a paradigm of the performance-security tradeoff optimization based on the Coevolutionary genetic algorithm (CGA) for D-NCS.