Journal article
Evidence-Aware Mobile Computational Offloading
H Flores, P Hui, P Nurmi, E Lagerspetz, S Tarkoma, J Manner, V Kostakos, Y Li, X Su
IEEE Transactions on Mobile Computing | IEEE COMPUTER SOC | Published : 2018
Abstract
Computational offloading can improve user experience of mobile apps through improved responsiveness and reduced energy footprint. A fundamental challenge in offloading is to distinguish situations where offloading is beneficial from those where it is counterproductive. Currently, offloading decisions are predominantly based on profiling performed on individual devices. While significant gains have been shown in benchmarks, these gains rarely translate to real-world use due to the complexity of contexts and parameters that affect offloading. We contribute by proposing crowdsensed evidence traces as a novel mechanism for improving the performance of offloading systems. Instead of limiting to p..
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Funding Acknowledgements
The authors thank the anonymous reviewers for their insightful comments. This research has been supported, in part, by projects 26211515 and 16214817 from the Research Grants Council of Hong Kong. This work also was supported by the Jorma Ollila Grant 201620040.