Abstract
Given the recent proliferation in the number of smart devices connected to the Internet, the era of Internet of Things (IoT) is challenged with massive amounts of data generation. Fog Computing is gaining popularity and is being increasingly deployed in various latency-sensitive application domains including industrial IoT. However, efficient discovery of services is one of the prevailing issues in the fog nodes of industrial IoT, which restrain their efficiencies in availing appropriate services to the clients. To address this issue, this paper proposes a novel efficient multilevel index model based on equivalence relation, named the distributed multilevel (DM)-index model, for service maintenance and retrieval in the fog layer of industrial IoT to eliminate redundancy, narrow the search space, reduce both the number of traversed services and retrieval time, ultimately to improve the service discovery efficiency. The efficiency of the proposed index model has been verified theoretically and evaluated experimentally, which demonstrates that the proposed model is effective in achieving much better service discovery and retrieval performance than the sequential and inverted index models.
Highlights
Fog computing, as an extension of cloud computing, is one of the emerging technologies of distributed computing which incorporates a fog layer between the datacentre and the end devices to provide supplements for Internet-based smart devices, transforming such resource-constrained devices into more powerful computing utilities
A multi-scale distributed service paradigm comprises massive number of data/services generated by heterogeneous smart devices, achieving effective service discovery is even complicated in such environments
This paper proposes an efficient multilevel indexing model for fog nodes of industrial Internet of Things (IoT) in order to enhance the time management during the service discovery and retrieval process
Summary
As an extension of cloud computing, is one of the emerging technologies of distributed computing which incorporates a fog layer between the datacentre and the end devices to provide supplements for Internet-based smart devices, transforming such resource-constrained devices into more powerful computing utilities. Enhancing the resource discovery efficiency within the industrial IoT has been studied in many recent research works [6,7,8,9,10,11,12] Most of these existing methodologies [6,7,8][10][12] mainly focus on efficient routing methods without considering efficient ser-. With this in mind, this paper proposes an efficient multilevel indexing model for fog nodes of industrial IoTs in order to enhance the time management during the service discovery and retrieval process.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
