e interaction with mobile nodes via local control decisions and actuation. MEC has already been proposed as an enabler for several Internet of Things and cyber-physical systems application sce- narios, and also mutual benefits due to the inte- gration of MEC and mobile crowdsensing (MCS). The article originally proposes human-driven edge computing (HEC) as a new model to ease the provisioning and to extend the coverage of tra- ditional MEC solutions. From a methodological perspective, we show how it is possible to exploit MCS i) to support the effective deployment of fixed MEC (FMEC) proxies and ii) to further extend their coverage through the introduction of impromptu and human-enabled mobile MEC (M2EC) proxies. In addition, we describe how we have implemented these novel concepts in the MCS ParticipAct platform through the integration of the MEC Elijah platform in the ParticipAct liv- ing lab, an ongoing MCS real-world experiment that involved about 170 students at the University of Bologna for more than two years. Reported experimental results quantitatively show the effec- tiveness of the proposed techniques in elastically scaling the load at edge nodes according to run- time provisioning needs.

Human-Enabled Edge Computing: Exploiting the Crowd as a Dynamic Extension of Mobile Edge Computing

Girolami M
2018

Abstract

e interaction with mobile nodes via local control decisions and actuation. MEC has already been proposed as an enabler for several Internet of Things and cyber-physical systems application sce- narios, and also mutual benefits due to the inte- gration of MEC and mobile crowdsensing (MCS). The article originally proposes human-driven edge computing (HEC) as a new model to ease the provisioning and to extend the coverage of tra- ditional MEC solutions. From a methodological perspective, we show how it is possible to exploit MCS i) to support the effective deployment of fixed MEC (FMEC) proxies and ii) to further extend their coverage through the introduction of impromptu and human-enabled mobile MEC (M2EC) proxies. In addition, we describe how we have implemented these novel concepts in the MCS ParticipAct platform through the integration of the MEC Elijah platform in the ParticipAct liv- ing lab, an ongoing MCS real-world experiment that involved about 170 students at the University of Bologna for more than two years. Reported experimental results quantitatively show the effec- tiveness of the proposed techniques in elastically scaling the load at edge nodes according to run- time provisioning needs.
2018
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
cloud computing
cyber-physical systems
Internet of Things
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Descrizione: Human-Enabled Edge Computing: Exploiting the Crowd as a Dynamic Extension of Mobile Edge Computing
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/367418
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