Machine Learning-Driven Trust Prediction for MEC-Based IoT Services
| Title | Machine Learning-Driven Trust Prediction for MEC-Based IoT Services |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Abeysekara, P., Dong, H., Qin, A. K. |
| Conference Name | 2019 IEEE International Conference on Web Services (ICWS) |
| Date Published | July 2019 |
| Publisher | IEEE |
| ISBN Number | 978-1-7281-2717-0 |
| Keywords | alternate direction method of multipliers, Computing Theory, distributed machine-learning architecture, distributed trust prediction model, graph theory, Human Behavior, human factors, Internet of Things, Internet of Things services, IoT systems, large-scale networked-graphs, learning (artificial intelligence), machine learning, machine learning-driven trust prediction, machine-learning architecture models, Mathematical model, MEC-based IoT services, MEC-based IoT systems, MEC-environments, mobile computing, Mobile Edge Computing, network Lasso problem, Network topology, optimisation, Optimization, pattern clustering, Predictive models, pubcrawl, sensor services, simultaneous clustering, Topology, Trust, Trusted Computing, trustworthiness |
| Abstract | We propose a distributed machine-learning architecture to predict trustworthiness of sensor services in Mobile Edge Computing (MEC) based Internet of Things (IoT) services, which aligns well with the goals of MEC and requirements of modern IoT systems. The proposed machine-learning architecture models training a distributed trust prediction model over a topology of MEC-environments as a Network Lasso problem, which allows simultaneous clustering and optimization on large-scale networked-graphs. We then attempt to solve it using Alternate Direction Method of Multipliers (ADMM) in a way that makes it suitable for MEC-based IoT systems. We present analytical and simulation results to show the validity and efficiency of the proposed solution. |
| URL | https://ieeexplore.ieee.org/document/8818406 |
| DOI | 10.1109/ICWS.2019.00040 |
| Citation Key | abeysekara_machine_2019 |
- Predictive models
- MEC-environments
- mobile computing
- Mobile Edge Computing
- network Lasso problem
- network topology
- optimisation
- optimization
- pattern clustering
- MEC-based IoT systems
- pubcrawl
- sensor services
- simultaneous clustering
- Topology
- trust
- Trusted Computing
- trustworthiness
- IoT systems
- Computing Theory
- distributed machine-learning architecture
- distributed trust prediction model
- graph theory
- Human behavior
- Human Factors
- Internet of Things
- Internet of Things services
- alternate direction method of multipliers
- large-scale networked-graphs
- learning (artificial intelligence)
- machine learning
- machine learning-driven trust prediction
- machine-learning architecture models
- Mathematical model
- MEC-based IoT services