Green Resilience of Cyber-Physical Systems
This addresses the need for green and resilient recovery techniques in CPS, but it is an early proposal with incremental aspects.
The paper tackles the problem of maintaining reliability in Cyber-Physical Systems (CPS) under uncertainties by proposing a game theory solution to achieve resilience with minimized CO2 footprint, showing expected results for a collaborative AI system involving robots and humans.
Cyber-Physical System (CPS) represents systems that join both hardware and software components to perform real-time services. Maintaining the system's reliability is critical to the continuous delivery of these services. However, the CPS running environment is full of uncertainties and can easily lead to performance degradation. As a result, the need for a recovery technique is highly needed to achieve resilience in the system, with keeping in mind that this technique should be as green as possible. This early doctorate proposal, suggests a game theory solution to achieve resilience and green in CPS. Game theory has been known for its fast performance in decision-making, helping the system to choose what maximizes its payoffs. The proposed game model is described over a real-life collaborative artificial intelligence system (CAIS), that involves robots with humans to achieve a common goal. It shows how the expected results of the system will achieve the resilience of CAIS with minimized CO2 footprint.