TY - GEN
T1 - Running Consistent Applications Closer to Users with Radical for Lower Latency
AU - Kaashoek, Nicolaas
AU - Golev, Oleg A.
AU - Li, Austin T.
AU - Levy, Amit Aryeh
AU - Lloyd, Wyatt
N1 - Publisher Copyright:
© 2025 Copyright held by the owner/author(s).
PY - 2025/10/12
Y1 - 2025/10/12
N2 - Running applications close to users - in nearby datacenters, at edge points of presence, or in on-premises clusters - is attractive, as it reduces end-to-end latency. Moving strong consistent applications closer to users is difficult, as they incur high latencies either when accessing, or coordinating, their storage system. This restricts such applications to running co-located with their data, in a datacenter. Radical allows these applications to leverage the latency benefits that come from running near users. Radical uses its new LVI protocol to perform all necessary coordination in a single request. This request guarantees linearizability with a combination of locks, a validation step, and write intents. Radical hides the latency of the LVI request by overlapping it with speculative execution of the application. Our evaluation shows that Radical achieves 84-89% of the latency improvement obtainable by moving out of the datacenter, while providing Linearizability.
AB - Running applications close to users - in nearby datacenters, at edge points of presence, or in on-premises clusters - is attractive, as it reduces end-to-end latency. Moving strong consistent applications closer to users is difficult, as they incur high latencies either when accessing, or coordinating, their storage system. This restricts such applications to running co-located with their data, in a datacenter. Radical allows these applications to leverage the latency benefits that come from running near users. Radical uses its new LVI protocol to perform all necessary coordination in a single request. This request guarantees linearizability with a combination of locks, a validation step, and write intents. Radical hides the latency of the LVI request by overlapping it with speculative execution of the application. Our evaluation shows that Radical achieves 84-89% of the latency improvement obtainable by moving out of the datacenter, while providing Linearizability.
UR - https://www.scopus.com/pages/publications/105020852638
UR - https://www.scopus.com/pages/publications/105020852638#tab=citedBy
U2 - 10.1145/3731569.3764831
DO - 10.1145/3731569.3764831
M3 - Conference contribution
AN - SCOPUS:105020852638
T3 - SOSP 2025 - Proceedings of the 2025 ACM SIGOPS 31st Symposium on Operating Systems Principles
SP - 962
EP - 978
BT - SOSP 2025 - Proceedings of the 2025 ACM SIGOPS 31st Symposium on Operating Systems Principles
PB - Association for Computing Machinery, Inc
T2 - 31st ACM Symposium on Operating Systems Principles, SOSP 2025
Y2 - 13 October 2025 through 16 October 2025
ER -