Reducing Cyber Risks in IoT Device Resource Management: A Probabilistic Banker’s Algorithm Approach

In the digital age, IoT devices have revolutionized connectivity and data exchange by embedding sensors, software, and technology into physical objects. From household appliances to industrial tools, IoT facilitates seamless integration across various domains. However, the rising cost of IoT devices necessitates resource sharing in small-scale environments. While the Banker’s Algorithm efficiently manages resource schedules, its deterministic nature faces challenges in dynamic IoT settings. This paper proposes a probabilistic adaptation rooted in historical foundations to address these challenges. Leveraging technologies like fog computing and RFID tags, along with diverse allocation schemes, the adaptation optimizes resource allocation in IoT environments. Probabilistic models handle uncertainties in resource availability, dynamic demand, and risk management, ensuring resilience to real-time changes. By considering metrics proposed by Setzler & Mountrouidou and assessing security health, the proposed adaptation provides a comprehensive approach to IoT resource scheduling, which helps in managing cyber risks effectively.