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Article

A Task Execution Scheme for Dew Computing with State-of-the-Art Smartphones †

1
ISISTAN–UNCPBA–CONICET, Tandil, 7000 Buenos Aires, Argentina
2
Department of Information Systems, University of Agder, 4630 Kristiansand, Norway
3
Mobile Technology Lab, Department of Technology, Kristiania University College, 0176 Oslo, Norway
4
Institute of Computer Technology, TU Wien, 1040 Vienna, Austria
*
Author to whom correspondence should be addressed.
This paper is an extended version of our paper published in HICSS-54.
Academic Editors: Ka Lok Man and Kevin Lee
Electronics 2021, 10(16), 2006; https://doi.org/10.3390/electronics10162006
Received: 29 June 2021 / Revised: 12 August 2021 / Accepted: 16 August 2021 / Published: 19 August 2021
(This article belongs to the Special Issue Edge Computing for Internet of Things)
The computing resources of today’s smartphones are underutilized most of the time. Using these resources could be highly beneficial in edge computing and fog computing contexts, for example, to support urban services for citizens. However, new challenges, especially regarding job scheduling, arise. Smartphones may form ad hoc networks, but individual devices highly differ in computational capabilities and (tolerable) energy usage. We take into account these particularities to validate a task execution scheme that relies on the computing power that clusters of mobile devices could provide. In this paper, we expand the study of several practical heuristics for job scheduling including execution scenarios with state-of-the-art smartphones. With the results of new simulated scenarios, we confirm previous findings and better comprehend the baseline approaches already proposed for the problem. This study also sheds some light on the capabilities of small-sized clusters comprising mid-range and low-end smartphones when the objective is to achieve real-time stream processing using Tensorflow object recognition models as edge jobs. Ultimately, we strive for industry applications to improve task scheduling for dew computing contexts. Heuristics such as ours plus supporting dew middleware could improve citizen participation by allowing a much wider use of dew computing resources, especially in urban contexts in order to help build smart cities. View Full-Text
Keywords: dew computing; edge computing; smartphone; job scheduling; scheduling heuristics dew computing; edge computing; smartphone; job scheduling; scheduling heuristics
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MDPI and ACS Style

Hirsch, M.; Mateos, C.; Zunino, A.; Majchrzak, T.A.; Grønli, T.-M.; Kaindl, H. A Task Execution Scheme for Dew Computing with State-of-the-Art Smartphones. Electronics 2021, 10, 2006. https://doi.org/10.3390/electronics10162006

AMA Style

Hirsch M, Mateos C, Zunino A, Majchrzak TA, Grønli T-M, Kaindl H. A Task Execution Scheme for Dew Computing with State-of-the-Art Smartphones. Electronics. 2021; 10(16):2006. https://doi.org/10.3390/electronics10162006

Chicago/Turabian Style

Hirsch, Matías, Cristian Mateos, Alejandro Zunino, Tim A. Majchrzak, Tor-Morten Grønli, and Hermann Kaindl. 2021. "A Task Execution Scheme for Dew Computing with State-of-the-Art Smartphones" Electronics 10, no. 16: 2006. https://doi.org/10.3390/electronics10162006

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