Paper Info
Title
Mobi-IoST: Mobility-Aware Cloud-Fog-Edge-IoT Collaborative Framework for Time-Critical Applications
Abstract
The design of mobility-aware framework for edge/fog computing for IoT systems with back-end cloud is gaining research interest. In this paper, a mobility-driven cloud-fog-edge collaborative real-time framework, Mobi-IoST, has been proposed, which has IoT, Edge, Fog and Cloud layers and exploits the mobility dynamics of the moving agent. The IoT and edge devices are considered to be the moving agents in a 2-D space, typically over the road-network. The framework analyses the spatio-temporal mobility data (GPS logs) along with the other contextual information and employs machine learning algorithm to predict the location of the moving agents (IoT and Edge devices) in real-time. The accumulated spatio-temporal traces from the moving agents are modelled using probabilistic graphical model. The major features of the proposed framework are: (i) hierarchical processing of the information using IoT-Edge-Fog-Cloud architecture to provide better QoS in real-time applications, (ii) uses mobility information for predicting next location of the agents to deliver processed information, and (iii) efficiently handles delay and power consumption. The performance evaluations yield that the proposed Mobi-IoST framework has approximately 93% accuracy and reduced the delay and power by approximately 23-26% and 37-41% respectively than the existing mobility-aware task delegation system.
Year
DOI
Venue
2020
10.1109/TNSE.2019.2941754
IEEE Transactions on Network Science and Engineering
Keywords
DocType
Volume
Cloud computing,Edge computing,Fog computing,Internet of Things (IoT),Mobility analytics,Spatio-temporal data.
Journal
7
Issue
ISSN
Citations 
4
2327-4697
5
PageRank 
References 
Authors
0.40
0
4
Name
Order
Citations
PageRank
Shreya Ghosh1679.04
Anwesha Mukherjee2848.80
Soumya Kanti Ghosh334539.91
R. Buyya452234.33