{"arxiv":1,"type":"conference","date_updated":"2026-05-05T11:52:57Z","day":"30","date_created":"2026-02-16T15:21:27Z","publication_status":"published","department":[{"_id":"ElKo"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","OA_place":"repository","oa":1,"quality_controlled":"1","external_id":{"arxiv":["2404.04183"]},"publication_identifier":{"eisbn":["9798331555573"]},"month":"07","scopus_import":"1","publication":"2025 IEEE 18th International Conference on Cloud Computing","title":"RACS-SADL: Robust and understandable randomized consensus in the cloud","_id":"21243","language":[{"iso":"eng"}],"status":"public","main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2404.04183"}],"author":[{"first_name":"Pasindu","last_name":"Tennage","full_name":"Tennage, Pasindu"},{"id":"06d0c166-aec1-11ee-a7c0-b96e840a602b","last_name":"Desjardins","full_name":"Desjardins, Antoine","first_name":"Antoine"},{"orcid":"0000-0002-8827-3382","first_name":"Eleftherios","full_name":"Kokoris Kogias, Eleftherios","last_name":"Kokoris Kogias","id":"f5983044-d7ef-11ea-ac6d-fd1430a26d30"}],"citation":{"chicago":"Tennage, Pasindu, Antoine Desjardins, and Eleftherios Kokoris Kogias. “RACS-SADL: Robust and Understandable Randomized Consensus in the Cloud.” In <i>2025 IEEE 18th International Conference on Cloud Computing</i>. IEEE, 2025. <a href=\"https://doi.org/10.1109/cloud67622.2025.00044\">https://doi.org/10.1109/cloud67622.2025.00044</a>.","ista":"Tennage P, Desjardins A, Kokoris Kogias E. 2025. RACS-SADL: Robust and understandable randomized consensus in the cloud. 2025 IEEE 18th International Conference on Cloud Computing. CLOUD: Conference on Cloud Computing.","short":"P. Tennage, A. Desjardins, E. Kokoris Kogias, in:, 2025 IEEE 18th International Conference on Cloud Computing, IEEE, 2025.","apa":"Tennage, P., Desjardins, A., &#38; Kokoris Kogias, E. (2025). RACS-SADL: Robust and understandable randomized consensus in the cloud. In <i>2025 IEEE 18th International Conference on Cloud Computing</i>. Helsinki, Finland: IEEE. <a href=\"https://doi.org/10.1109/cloud67622.2025.00044\">https://doi.org/10.1109/cloud67622.2025.00044</a>","ieee":"P. Tennage, A. Desjardins, and E. Kokoris Kogias, “RACS-SADL: Robust and understandable randomized consensus in the cloud,” in <i>2025 IEEE 18th International Conference on Cloud Computing</i>, Helsinki, Finland, 2025.","mla":"Tennage, Pasindu, et al. “RACS-SADL: Robust and Understandable Randomized Consensus in the Cloud.” <i>2025 IEEE 18th International Conference on Cloud Computing</i>, IEEE, 2025, doi:<a href=\"https://doi.org/10.1109/cloud67622.2025.00044\">10.1109/cloud67622.2025.00044</a>.","ama":"Tennage P, Desjardins A, Kokoris Kogias E. RACS-SADL: Robust and understandable randomized consensus in the cloud. In: <i>2025 IEEE 18th International Conference on Cloud Computing</i>. IEEE; 2025. doi:<a href=\"https://doi.org/10.1109/cloud67622.2025.00044\">10.1109/cloud67622.2025.00044</a>"},"OA_type":"green","year":"2025","date_published":"2025-07-30T00:00:00Z","conference":{"start_date":"2025-07-07","end_date":"2025-07-12","name":"CLOUD: Conference on Cloud Computing","location":"Helsinki, Finland"},"abstract":[{"lang":"eng","text":"Widely deployed consensus protocols in the cloud are often leader-based and optimized for low latency under synchronous network conditions. However, cloud networks can experience disruptions such as network partitions, high-loss links, and configuration errors. These disruptions interfere with the operation of leader-based protocols, as their view change mechanisms interrupt the normal case replication and cause the system to stall. We propose RACS, a novel randomized consensus protocol that ensures robustness against adversarial network conditions. RACS achieves optimal one-round trip latency under synchronous network conditions while remaining resilient to adversarial network conditions. RACS follows a simple design inspired by Raft, the most widely used consensus protocol in the cloud, and therefore enables seamless integration with the existing cloud software stack. Experiments with a prototype running on Amazon EC2 show that RACS achieves 28k cmd/sec throughput, ninefold higher than Raft under adversarial cloud network conditions. Under synchronous network conditions, RACS matches the performance of Multi-Paxos and Raft, achieving a throughput of 200k cmd/sec with a median latency of 300ms, confirming that RACS introduces no unnecessary overhead. Finally, SADL-RACS, a throughput-optimized version of RACS, achieves a throughput of 500k cmd/sec, delivering 150 percent higher throughput than Raft."}],"doi":"10.1109/cloud67622.2025.00044","corr_author":"1","oa_version":"Preprint","article_processing_charge":"No","publisher":"IEEE"}