Selective Edge Computing for Mobile Analytics

Selective Edge Computing for Mobile Analytics

Galanopoulos, Apostolos (Trinity College Dublin)
Iosifidis, G. (TU Delft Embedded Systems)
Salonidis, Theodoros (IBM Thomas J. Watson Research Centre)
Leith, Douglas J. (Trinity College Dublin)

2022

An increasing number of mobile applications rely on Machine Learning (ML) routines for analyzing data. Executing such tasks at the user devices saves the energy spent on transmitting and processing large data volumes at distant cloud-deployed servers. However, due to memory and computing limitations, the devices often cannot support the required resource-intensive routines and fail to accurately execute such tasks. In this work, we address the problem of edge-assisted analytics in resourceconstrained systems by proposing and evaluating a rigorous selective offloading framework. The devices execute their tasks locally and outsource them to cloudlet servers only when they predict a significant performance improvement. We consider the practical scenario where the offloading gains and resource costs are time-varying; and propose an online optimization algorithm that maximizes the service performance without requiring to know this information. Our approach relies on an approximate dual subgradient method combined with a primal-averaging scheme, and works under minimal assumptions about the system stochasticity. We fully implement the proposed algorithm in a wireless testbed and evaluate its performance using a state-of-theart image recognition application, finding significant performance gains and cost savings.

Edge Computing
Data Analytics
Network Optimization
Resource Allocation
Subgradient method

http://resolver.tudelft.nl/uuid:c4aa2140-b9f3-474c-bee6-1e0415d9afc2

https://doi.org/10.1109/TNSM.2022.3174776

2023-07-01

1932-4537

IEEE Transactions on Network and Service Management, 19 (3), 3090-3104

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

journal article

© 2022 Apostolos Galanopoulos, G. Iosifidis, Theodoros Salonidis, Douglas J. Leith