Integrating self-organization into control models for wireless sensor networks (WSNs) allows a system to adopt in real-time to maintain the required quality of service in highly dynamic environments. In this paper, the topological structure of a WSN is altered based on time-driven and data-driven events in order to maintain bandwidth, redundancy, and communication speed subject to constraints such as power usage. However, most control models are based on either a time-driven or a data-driven approach which limits the self-organization ability. Unknown data-driven events cause uncertainty in node states leading to variability in outcome. Reducing variability involves enriching the knowledge about...