The distant data centre-centric Internet of Things (IoT) systems face the latency issue especially in the real-time-based applications, such as augmented reality, traffic analytics and ambient assisted living. Recently, Fog computing models have been introduced to overcome the latency issue by using the proximity-based computational resources, such as the computers co-located with the cellular base station, grid router devices or computers in local business. However, the increasing users of Fog computing servers cause bottleneck issues and consequently the latency issue arises again. This paper aims to introduce the utilisation of Mist computing (Mist) model, which exploits the computational and networking resources from the devices at the very edge of the IoT networks.
This paper proposes a service-oriented mobile-embedded Platform as a Service (mePaaS) framework that allows the mobile device to provide a flexible platform for proximal users to offload their computational or networking program to mePaaS-based Mist computing node.
The prototype has been tested and performance has been evaluated on the real-world devices. The evaluation results have shown the promising nature of mePaaS.
The proposed framework supports resource-aware autonomous service configuration that can manage the availability of the functions provided by the Mist node based on the dynamically changing hardware resource availability. In addition, the framework also supports task distribution among a group of Mist nodes.
This research was supported by Estonian Research Council grant IUT20-55.
Liyanage, M., Chang, C. and Srirama, S. (2018), "Adaptive mobile Web server framework for Mist computing in the Internet of Things", International Journal of Pervasive Computing and Communications, Vol. 14 No. 3/4, pp. 247-267. https://doi.org/10.1108/IJPCC-D-18-00023Download as .RIS
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