Open AccessInteroperability Improvement in Internet of Things Using Fog Assisted Semantic Frame Work
Author(s) -
Joy Iong Zong Chen,
S. Smys
Publication year - 2020
Publication title -
journal of trends in computer science and smart technology
Language(s) - English
Resource type - Journals
ISSN - 2582-4104
DOI - 10.36548/jtcsst.2020.1.006
Subject(s) - cloud computing , computer science , interoperability , bottleneck , semantic interoperability , ontology , frame (networking) , semantics (computer science) , the internet , rdf , efficient energy use , distributed computing , database , semantic web , world wide web , embedded system , computer network , operating system , engineering , philosophy , epistemology , programming language , electrical engineering
Cloud computing is equipped with the numerous of advantageous features to support software and utilities on the Internet of Things (IoT). Cloud-based technology is widely used when offering support for heterogeneous applications integrating specific IoT that follows various semantics. Attaching additional information to raw data sensed with the help of ontology is accomplished in semantic model. The longer distance between the cloud and IoT applications, however, is a bottleneck for vital IoT software. So the paper puts forth a semantic frame work assisted by the fog to enhance the interoperability in the internet of things. The structure put forth moves some of the cloud's commonly used semantic resources sensor networks edge and also offers an effective off-loading technique between fog – fog and fog – cloud devices to diminish total computation time of the task and the energy consumed by the nodes in the fog. The proposed method further follows an efficient mapping technique to transform the data’s sensed into a RDF-format such that it is compatible for processing. The proposed model is evaluated on the basis of delay in the service provision, the energy consumed , and the total cost of the system and further the results obtained are compared with the relevant cloud based computing models , to reveal the proficiency of the proposed.