Evaluating Performance of In-Situ Distributed Processing on IoT Devices by Developing a Workspace Context Recognition Service

被引:0
|
作者
Talusan, Jose Paolo [1 ]
Tiausas, Francis [1 ]
Stirapongsasuti, Sopicha [1 ]
Nakamura, Yugo [1 ]
Mizumoto, Teruhiro [1 ]
Yasumoto, Keiichi [1 ]
机构
[1] Nara Inst Sci & Technol, Nara, Japan
关键词
Edge Computing; Internet of Things; Middle-ware; Distributed processing; Activity recognition;
D O I
10.1109/percomw.2019.8730693
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the number of IoT devices expected to exceed 50 billion in 2023, edge and fog computing paradigms are beginning to attract attention as a way to process the massive amounts of raw data being generated. However, these paradigms do not consider the processing capabilities of the existing commodity IoT devices in the wild. In order to solve this challenge, we are developing a new middleware platform called IFoT, which processes various sensor data while considering Quality of Service (QoS) by utilizing the computational resources of heterogeneous IoT devices within an area. This allows smart services to be created and processed in parallel by various IoT devices. In this paper, we show the effectiveness of the IFoT based approach of constructing services. We designed and implemented a workspace context recognition service, utilizing environmental sensor data processed in a distributed manner according to the IFoT framework. We evaluate the QoS of IFoT middle-ware and its feasibility when used on commodity devices such as the Raspberry Pi, through the service.
引用
收藏
页码:633 / 638
页数:6
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