IoT Information Service Composition Driven by User Requirement

Several kinds of sensors would be widely deployed with the development of the Internet of things (IoT). Each IoT information service provides individual sensory data. When a complex service request is submitted, composing multiple information services to satisfy customer´s comprehensive demands efficiently becomes an important research issue. To address the issue of IoT information service composition, we propose an efficient strategy from the perspective of sensory data selection and aggregation. Selection of elite candidate services is discussed by the modelization and evaluation of IoT quality of service (QoS). Improved binary coded genetic algorithm (GA) is used as global optimization method. The optimal solution is defined as the service composition scheme with the maximum overall function value. The experimental results verify the effectiveness of the proposed method in IoT.