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Rising demand for the integration of IoT services in cloud computing has brought cloud-native principles (e.g., system automation, loosely coupled services, etc.) to the edge of the network. A fundamental element of the cloud-native approach is a microservice &#x2014; an instance, which is usually virtualised, serving for only a defined purpose. Virtualised microservices are mostly used in cloud-based IoT systems, which can be covered with multi-agent system (MAS) paradigm. The maintenance of a MAS requires a constant monitoring to track the system state and to satisfy the service level agreement (SLA) (or any other) requirements. This paper presents a resource efficient reliability model for MAS IoT systems for monitoring purposes. First, we provide a thorough mathematical analysis to describe the generic system model and its elements. This model takes into account SLA requirements and it is characterised with linear time complexity, simplicity of computations and input metrics (e.g., combination of SLA for CPU and its workload), where all of the input data are aligned to the same range. Then, we evaluate time complexity and provide a measurement to demonstrate the reliability of the model application. The results show that the proposed model is efficient for large number of the IoT agents. It is approximately 98 times faster in computation with 1,000 systems when compared with [D. Ursino, <italic>et al.</italic>, 2020] and 51 times faster in computations with 1,000 systems when compared with [J. Yao, <italic>et al.</italic>, 2019].

Resource Efficient Real-Time Reliability Model for Multi-Agent IoT Systems