Abstract
Analysis of Internet of Things (IoT) sensor data is a key for achieving city smartness. In this paper a multitier fog computing model with large-scale data analytics service is proposed for smart cities applications. The multitier fog is consisted of ad-hoc fogs and dedicated fogs with opportunistic and dedicated computing resources, respectively. The proposed new fog computing model with clear functional modules is able to mitigate the potential problems of dedicated computing infrastructure and slow response in cloud computing. We run analytics benchmark experiments over fogs formed by Rapsberry Pi computers with a distributed computing engine to measure computing performance of various analytics tasks, and create easy-to-use workload models. Quality of services (QoS) aware admission control, offloading, and resource allocation schemes are designed to support data analytics services, and maximize analytics service utilities. Availability and cost models of networking and computing resources are taken into account in QoS scheme design. A scalable system level simulator is developed to evaluate the fog-based analytics service and the QoS management schemes. Experiment results demonstrate the efficiency of analytics services over multitier fogs and the effectiveness of the proposed QoS schemes. Fogs can largely improve the performance of smart city analytics services than cloud only model in terms of job blocking probability and service utility.
| Original language | English |
|---|---|
| Pages (from-to) | 677-686 |
| Number of pages | 10 |
| Journal | IEEE Internet of Things Journal |
| Volume | 5 |
| Issue number | 2 |
| Early online date | 11 Jul 2017 |
| DOIs | |
| Publication status | Published - 1 Apr 2018 |
Keywords
- Data analytics
- fog computing
- Internet of Things (IoT)
- quality of services (QoS)
- Raspberry Pi
- smart cities
- Spark
ASJC Scopus subject areas
- Signal Processing
- Information Systems
- Hardware and Architecture
- Computer Science Applications
- Computer Networks and Communications
Access to Document
- Author Accepted Manuscript
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