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

Abstract

The Mobile Edge Computing (MEC) vision leverages the availability of powerful and low-cost middle boxes, statically deployed at suitable edges of the network and acting as local proxies for the centralized cloud backbone; this potentially enables, among the others, better scalability and better reactivity in the 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 scenarios, but mutual benefits due to the integration of MEC and Mobile CrowdSensing (MCS). The paper originally proposes Human-driven Edge Computing (HEC) as a new model to ease the provisioning and to extend the coverage of traditional 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 (M 2 EC) 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 living lab, an ongoing MCS real-world experiment that involved about 170 students of the University of Bologna for more than two years. Reported experimental results quantitatively show the effectiveness of the proposed techniques in elastically scaling the load at edge nodes according to runtime provisioning needs.

All one needs to know about fog computing and related edge computing paradigms: A complete survey

“…With the described FoT paradigm, the authors further propose a platform for the actual implementation of the FoT paradigm. The authors in [185] propose human-driven edge computing (HEC) as a new model to ease the provisioning and to extend the coverage of traditional fixed MEC solutions by utilizing devices that humans carry.…”

Resource Management in Fog/Edge Computing

“…Human-driven edge computing (HEC) [145] points out that mobile edge computing has limitations because the number of edges is not sufficient, and some highly populated areas may result in congestion on edges. To address these limitations, HEC combines mobile edge computing with mobile crowdsensing [146], where smartphones or tablet computers become edge nodes, share sensor data, and analyze the data for common interest.…”

Process Migration-Based Computational Offloading Framework for IoT-Supported Mobile Edge/Cloud Computing

“…Bellavista et al [17] proposed human-driven edge computing to ease the provisioning and extend the coverage of traditional MEC solutions for IoT and cyberphysical systems application scenarios. Similarly, a general framework for IoT fog-cloud applications, along with a delay-minimizing collaboration and offloading policy for fog-capable devices, was proposed in [18].…”