EdgeCons: Achieving Efficient Consensus in Edge Computing Networks


Zijiang Hao, Shanhe Yi, and Qun Li, College of William and Mary


Fast event ordering is critical for delay-sensitive edge computing applications that serve massive geographically distributed clients. Using a centralized cloud to determine the event order suffers from unsatisfactory latency. Naive edge-centric solutions, which designate one edge node to order all the events, have scalability and single point of failure issues. To address these problems, we propose EdgeCons, a novel consensus algorithm optimized for edge computing networks. EdgeCons achieves fast consensus by running a sequence of Paxos instances among the edge nodes and dynamically distributing their leadership based on the recent running history. It also guarantees progressiveness by incorporating a reliable, backend cloud. A preliminary evaluation shows that EdgeCons works more efficiently than the state-of-the-art consensus algorithms, in the context of achieving fast event ordering in edge computing networks.

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@inproceedings {216795,
author = {Zijiang Hao and Shanhe Yi and Qun Li},
title = {EdgeCons: Achieving Efficient Consensus in Edge Computing Networks},
booktitle = {{USENIX} Workshop on Hot Topics in Edge Computing (HotEdge 18)},
year = {2018},
address = {Boston, MA},
url = {https://www.usenix.org/conference/hotedge18/presentation/hao},
publisher = {{USENIX} Association},
month = jul,