Title
Single-Board-Computer Clusters for Cloudlet Computing in Internet of Things.
Abstract
The number of connected sensors and devices is expected to increase to billions in the near future. However, centralised cloud-computing data centres present various challenges to meet the requirements inherent to Internet of Things (IoT) workloads, such as low latency, high throughput and bandwidth constraints. Edge computing is becoming the standard computing paradigm for latency-sensitive real-time IoT workloads, since it addresses the aforementioned limitations related to centralised cloud-computing models. Such a paradigm relies on bringing computation close to the source of data, which presents serious operational challenges for large-scale cloud-computing providers. In this work, we present an architecture composed of low-cost Single-Board-Computer clusters near to data sources, and centralised cloud-computing data centres. The proposed cost-efficient model may be employed as an alternative to fog computing to meet real-time IoT workload requirements while keeping scalability. We include an extensive empirical analysis to assess the suitability of single-board-computer clusters as cost-effective edge-computing micro data centres. Additionally, we compare the proposed architecture with traditional cloudlet and cloud architectures, and evaluate them through extensive simulation. We finally show that acquisition costs can be drastically reduced while keeping performance levels in data-intensive IoT use cases.
Year
DOI
Venue
2019
10.3390/s19133026
SENSORS
Keywords
Field
DocType
Internet of Things,resource efficiency,cloudlet computing,edge computing,distributed systems
Edge computing,Use case,Cloudlet,Electronic engineering,Single-board computer,Engineering,Throughput,Latency (engineering),Scalability,Cloud computing,Distributed computing
Journal
Volume
Issue
Citations 
19
13
1
PageRank 
References 
Authors
0.36
0
5