Context-Aware Social Task Resolution Using Feedback Control in Cyber Physical Systems
M. Bala Krishna · 2018
Social computing and crowdsourcing models incorporate the node social behavior, group behavior and inter-relations between the social groups to enhance the user services and connectivity in the network. Context-aware social computing and crowdsourcing models improve the performance of cyber physical systems (CPS). Auctioning and incentive models in social computing techniques evaluate the node behavior, reputations and enhance the user participation in CPS. In this regard, this article proposes a novel Context-Aware Social Task REsolution using Feedback control (CASTREF) in Cyber Physical Systems. The proposed CASTREF model comprises of Sensing and Sending Module (SSM), Context-aware Servicing Module (CSM) and Computational Intelligence Module (CIM). These modules perform the data collection and task resolution services, and evaluate the feedback constraints and context competency levels. The proposed model classifies the service lists as per user contexts and computes the feedback labels, context competency and context rationality in the system. CASTREF model applies the set cover and minimum exposure theorems to establish the optimal node connectivity and maximize the task revenues of participant nodes in the system. Simulation results indicate that the task mapped services and incentive costs of the proposed model increase the context competency levels in cyber physical system.