Symbiotic Sensing for Energy-Intensive Tasks in Large-Scale Mobile Sensing Applications

Energy consumption is a critical performance and user experience metric when developing mobile sensing applications, especially with the significantly growing number of sensing applications in recent years. As proposed a decade ago when mobile applications were still not popular and most mobile oper...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Duc V. Le [verfasserIn] Thuong Nguyen [verfasserIn] Hans Scholten [verfasserIn] Paul J. M. Havinga [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2017

Schlagwörter:	participatory sensing opportunistic sensing success probability energy consumption mobile sensing massive sensing

Übergeordnetes Werk:	In: Sensors - MDPI AG, 2003, 17(2017), 12, p 2763
Übergeordnetes Werk:	volume:17 ; year:2017 ; number:12, p 2763

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/s17122763

Katalog-ID:	DOAJ085509531

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language	English
source	In Sensors 17(2017), 12, p 2763 volume:17 year:2017 number:12, p 2763
sourceStr	In Sensors 17(2017), 12, p 2763 volume:17 year:2017 number:12, p 2763
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topic_facet	participatory sensing opportunistic sensing success probability energy consumption mobile sensing massive sensing Chemical technology
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authorswithroles_txt_mv	Duc V. Le @@aut@@ Thuong Nguyen @@aut@@ Hans Scholten @@aut@@ Paul J. M. Havinga @@aut@@
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callnumber-first	T - Technology
author	Duc V. Le
spellingShingle	Duc V. Le misc TP1-1185 misc participatory sensing misc opportunistic sensing misc success probability misc energy consumption misc mobile sensing misc massive sensing misc Chemical technology Symbiotic Sensing for Energy-Intensive Tasks in Large-Scale Mobile Sensing Applications
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topic	misc TP1-1185 misc participatory sensing misc opportunistic sensing misc success probability misc energy consumption misc mobile sensing misc massive sensing misc Chemical technology
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title_auth	Symbiotic Sensing for Energy-Intensive Tasks in Large-Scale Mobile Sensing Applications
abstract	Energy consumption is a critical performance and user experience metric when developing mobile sensing applications, especially with the significantly growing number of sensing applications in recent years. As proposed a decade ago when mobile applications were still not popular and most mobile operating systems were single-tasking, conventional sensing paradigms such as opportunistic sensing and participatory sensing do not explore the relationship among concurrent applications for energy-intensive tasks. In this paper, inspired by social relationships among living creatures in nature, we propose a symbiotic sensing paradigm that can conserve energy, while maintaining equivalent performance to existing paradigms. The key idea is that sensing applications should cooperatively perform common tasks to avoid acquiring the same resources multiple times. By doing so, this sensing paradigm executes sensing tasks with very little extra resource consumption and, consequently, extends battery life. To evaluate and compare the symbiotic sensing paradigm with the existing ones, we develop mathematical models in terms of the completion probability and estimated energy consumption. The quantitative evaluation results using various parameters obtained from real datasets indicate that symbiotic sensing performs better than opportunistic sensing and participatory sensing in large-scale sensing applications, such as road condition monitoring, air pollution monitoring, and city noise monitoring.
abstractGer	Energy consumption is a critical performance and user experience metric when developing mobile sensing applications, especially with the significantly growing number of sensing applications in recent years. As proposed a decade ago when mobile applications were still not popular and most mobile operating systems were single-tasking, conventional sensing paradigms such as opportunistic sensing and participatory sensing do not explore the relationship among concurrent applications for energy-intensive tasks. In this paper, inspired by social relationships among living creatures in nature, we propose a symbiotic sensing paradigm that can conserve energy, while maintaining equivalent performance to existing paradigms. The key idea is that sensing applications should cooperatively perform common tasks to avoid acquiring the same resources multiple times. By doing so, this sensing paradigm executes sensing tasks with very little extra resource consumption and, consequently, extends battery life. To evaluate and compare the symbiotic sensing paradigm with the existing ones, we develop mathematical models in terms of the completion probability and estimated energy consumption. The quantitative evaluation results using various parameters obtained from real datasets indicate that symbiotic sensing performs better than opportunistic sensing and participatory sensing in large-scale sensing applications, such as road condition monitoring, air pollution monitoring, and city noise monitoring.
abstract_unstemmed	Energy consumption is a critical performance and user experience metric when developing mobile sensing applications, especially with the significantly growing number of sensing applications in recent years. As proposed a decade ago when mobile applications were still not popular and most mobile operating systems were single-tasking, conventional sensing paradigms such as opportunistic sensing and participatory sensing do not explore the relationship among concurrent applications for energy-intensive tasks. In this paper, inspired by social relationships among living creatures in nature, we propose a symbiotic sensing paradigm that can conserve energy, while maintaining equivalent performance to existing paradigms. The key idea is that sensing applications should cooperatively perform common tasks to avoid acquiring the same resources multiple times. By doing so, this sensing paradigm executes sensing tasks with very little extra resource consumption and, consequently, extends battery life. To evaluate and compare the symbiotic sensing paradigm with the existing ones, we develop mathematical models in terms of the completion probability and estimated energy consumption. The quantitative evaluation results using various parameters obtained from real datasets indicate that symbiotic sensing performs better than opportunistic sensing and participatory sensing in large-scale sensing applications, such as road condition monitoring, air pollution monitoring, and city noise monitoring.
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title_short	Symbiotic Sensing for Energy-Intensive Tasks in Large-Scale Mobile Sensing Applications
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