CoAP Composition for Automation Planning Using Genetic Algorithms
Krisada Sangsanit, Suronapee Phoomvuthisarn · 2018
We are entering an era when everything can be accessed through the Internet, a device or a machine can exchange data, collaborate with a neighboring machine, and command others from every part of the world. As a consequence, such a smart device can be used to operate more complicated tasks such as coordination operations in order to reduce the cost of manufacturing new devices and device overlapping. In this regard, a service composition formation is necessary to fulfil user requests. However, by a human judgement to composing a large amount of data involving complicated devices such as the provision of services might lead to the failure of the execution of the whole operation. This research presents the Constrained Application Protocol (CoAP) composition for automation planning using genetic algorithms to reduce the complication of such operations and the coincidence of composition formation. By creating different composition goals, different resource accessibilities, as well as different values and outcomes to ensure validity, our results demonstrate that forming the CoAP composition can achieve a high degree of accuracy with affordable performance.