A Quantum-Annealing-Based Approach to Optimize the Deployment Cost of a Multi-Sink Multi-Controller WSN

Abstract

Software Defined Networking (SDN) provides network significant reconfiguration capability to Wireless Sensor Networks (WSNs). SDN is a promising technique for WSNs with high scalability and high reliability requirements. In SDN, a set of controller nodes are integrated into the network to advertise routing rules dynamically based on network and link changes. Determining the number and location of both sinks (are in charge of collecting the sensors data) and controller nodes in a WSN subject to both reliability and performance constraints is an important research challenge. In this paper, to address this research challenge, we propose a Quantum Annealing approach that improves the deployment cost of the system by minimizing the number of required sinks and SDN controller nodes. The experiments show that our approach improves the deployment cost of the network against the state-of-the-art by 10.7% on average.