EdgeCons: Achieving Efficient Consensus in Edge Computing Networks

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-theart consensus algorithms, in the context of achieving fast event ordering in edge computing networks.