Multi-valued model checking IoT and intelligent systems with commitment protocols in multi-source data environments

In today's world of connectivity, various domains use different multi-sensor Internet of Things (IoT) and Intelligent Systems (IS) applications. These applications involve extensive interactions between thousands or millions of components in open environments, which challenges verifying their reliability and efficiency. This paper introduces the first investigation in verifying IoT applications and intelligent systems in multi-source data settings with multi-agent commitment protocols in uncertain or inconsistent environments. Specifically, we present original and efficient solutions for modeling and verifying these systems with conditional and unconditional commitment protocols under uncertain or inconsistent settings. We introduce 4v-CTLc and 4v-CTLcc, multi-valued logics of commitment for reasoning about inconsistency over these systems that expand 3v-CTLc and 3v-CTLcc for reasoning about uncertainty. Moreover, we introduce new reduction algorithms for reducing our multi-valued model checking problems to the two-valued ones. To implement these algorithms, we develop two new automatic verification tools. The first tool translates the multi-valued logics to CTL and automatically interacts with the NuSMV model checker. The second tool translates these logics to the two-valued versions, CTLc and CTLcc, and automatically interacts with the MCMAS+ model checker. We apply our verification approaches to a Smart Home, a Smart Hospital and a Smart Mortgage system with multi-source data as case studies using sets of properties, including safety, liveness and reachability. The experimental results obtained by the proposed multi-valued model checking techniques proved these techniques' high efficiency and applicability to modeling and verifying intelligent and autonomous multi-source data systems.