Markov chain-based analytical model supporting service provisioning and network design in the Social Internet of Everything

The Internet of Everything has emerged as a prominent paradigm, enabling the development of advanced services by integrating smart objects, individuals, processes, and data. In the context of social networking within this framework, addressing the inherent uncertainty of the environment and developing secure service provisioning mechanisms is crucial. At present, there has been limited exploration into the stochastic behavior of the service fulfillment process, especially when considering the trustworthiness and resource availability of service providers. Additionally, existing approaches supporting service provisioning often require continuous and computationally prohibitive efforts. To overcome these challenges, this paper introduces a Markov chain-based stochastic model that effectively predicts the steady-state behavior of service providers within an IoE network. The proposed model integrates both the trust levels and resource capabilities of providers to ensure successful service delivery, while simultaneously identifying and excluding malicious entities without imposing significant computational overhead. The validity of the model is demonstrated by comparing various performance metrics against results obtained from extensive simulations, highlighting its effectiveness and practical applicability. Ultimately, the model serves as a valuable tool for fostering trusted service provisioning, optimizing the design of service communities within social networks, preventing data traffic loss, and enhancing the overall reliability and responsiveness of the system