Controllability of Random Networks

• Activity Number: 136
• Type: Contributed
• Date/Time: Monday, August 4, 2014 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistical Learning and Data Mining
• Author(s): Mohamad Kazem Shirani Faradonbeh*+ and Ambuj Tewari and George Michailidis
• Companies: University of Michigan and University of Michigan and University of Michigan
• Keywords: Structural Controllability ; Random Networks ; Linear Dynamics ; Graph Algorithms

Abstract

We consider a random network whose nodes can be in different states taking values in a real-valued set. Further, the network evolves over time according to linear dynamics. The problem under study is how to steer the network to "desirable" states. This problem captures key features of applications in social network analysis, marketing science, genome networks and wireless communication. To achieve the posited goal, a subset of nodes can act as controllers. We present algorithms on how to select a minimum number of controllers . Further, we establish results on trade-offs between selection efficiency and computational complexity of the algorithms and examine how these issues are effected by the structure of the underlying random network topology.