Publications

Adaptive Database Synchronization for an Online Analytical Cloud-to-Edge Continuum

SAC: Symposium on Applied Computing, 2022

Authors

Digital Object Identifier

10.1145/3477314.3507212

Abstract

Wide availability of edge computing platforms, as expected in emerging 5G networks, enables a computing continuum between centralized cloud services and the edge of the network, close to end-user devices. This is particularly appealing for online analytics as data collected by devices is made available for decision-making. However, cloud-based parallel-distributed data processing platforms are not able to directly access data on the edge. This can be circumvented, at the expense of freshness, with data synchronization that periodically uploads data to the cloud for processing. In this work, we propose an adaptive database synchronization system that makes distributed data in edge nodes available dynamically to the cloud by balancing between reducing the amount of data that needs to be transmitted and the computational effort needed to do so at the edge. This adapts to the availability of CPU and network resources as well as to the application workload.

BibTeX

@inproceedings{10.1145/3477314.3507212,
	author = {Costa, Daniel and Pereira, Jos\'{e} and Vila\c{c}a, Ricardo and Faria, Nuno},
	title = {Adaptive Database Synchronization for an Online Analytical Cioud-to-Edge Continuum},
	year = {2022},
	isbn = {9781450387132},
	publisher = {Association for Computing Machinery},
	address = {New York, NY, USA},
	url = {https://doi.org/10.1145/3477314.3507212},
	doi = {10.1145/3477314.3507212},
	booktitle = {Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing},
	pages = {264–266},
	numpages = {3},
	keywords = {replication, analytical, data federation, synchronization, cloud-edge environment},
	location = {Virtual Event},
	series = {SAC '22}
}

Resources