Work

Enabling Energy-Efficient Data Communication with Participatory Sensing and Mobile Cloud : Cloud-assisted crowd-sourced data-driven optimization

Year: 2016
Type: dissertation
Abstract: This thesis proposes a novel power management solution for the resource-constrained devices in the context of Internet of Things (IoT). We focus on smartphones in the IoT, as they are getting increasingly popular and equipped with strong sensing capabilities. Smartphones have complex and chaotic asynchronous power consumption incurred by heterogeneous components including their onboard sensors. Their interaction with the cloud can support computation offloading and remote data access via the network. In this work, we aim at monitoring the power consumption behaviours of smartphones and profiling individual applications and platform to make better decisions in power management. A solution is to design architecture of cloud orchestration as an epic predictor of the behaviours of smart devices with respect to time, location, and context. We design and implement this architecture to provide an integrated cloud-based energy monitoring service. This service enables the monitoring of power consumption on smartphones and support data analysis on massive data logs collected by a large number of users.
Language: English
Open Access status: green
OpenAlex ID: W2536810476
Cites: 12
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Related to: 10