From 4d216f833833697919a0bc16f1391aaa83c179bc Mon Sep 17 00:00:00 2001 From: Amaury Date: Wed, 12 Jul 2023 14:24:04 +0200 Subject: [PATCH] update biblio --- docs/bibliographie/My Library.bib | 30 ++++++++++++++++++++++++++++ docs/bibliographie/liste_detaille.md | 4 ++++ 2 files changed, 34 insertions(+) diff --git a/docs/bibliographie/My Library.bib b/docs/bibliographie/My Library.bib index 5ced189..db1c852 100644 --- a/docs/bibliographie/My Library.bib +++ b/docs/bibliographie/My Library.bib @@ -241,3 +241,33 @@ langid = {english}, file = {DeCandia et al. - Dynamo Amazon’s Highly Available Key-value Store.pdf:/home/amaury/Zotero/storage/KDHRPBGR/DeCandia et al. - Dynamo Amazon’s Highly Available Key-value Store.pdf:application/pdf}, } + +@misc{misra_byzantine_2021, + title = {Byzantine Fault Tolerant Causal Ordering}, + url = {http://arxiv.org/abs/2112.11337}, + abstract = {Causal ordering in an asynchronous system has many applications in distributed computing, including in replicated databases and real-time collaborative software. Previous work in the area focused on ordering point-to-point messages in a fault-free setting, and on ordering broadcasts under various fault models. To the best of our knowledge, Byzantine faulttolerant causal ordering has not been attempted for point-topoint communication in an asynchronous setting. In this paper, we first show that existing algorithms for causal ordering of point-to-point communication fail under Byzantine faults. We then prove that it is impossible to causally order messages under point-to-point communication in an asynchronous system with one or more Byzantine failures. We then present two algorithms that can causally order messages under Byzantine failures, where the network provides an upper bound on the message transmission time. The proofs of correctness for these algorithms show that it is possible to achieve causal ordering for point-to-point communication under a stronger asynchrony model where the network provides an upper bound on message transmission time. We also give extensions of our two algorithms for Byzantine fault-tolerant causal ordering of multicasts.}, + number = {{arXiv}:2112.11337}, + publisher = {{arXiv}}, + author = {Misra, Anshuman and Kshemkalyani, Ajay}, + urldate = {2023-07-12}, + date = {2021-12-21}, + langid = {english}, + eprinttype = {arxiv}, + eprint = {2112.11337 [cs]}, + keywords = {Computer Science - Distributed, Parallel, and Cluster Computing}, + file = {Misra and Kshemkalyani - 2021 - Byzantine Fault Tolerant Causal Ordering.pdf:/home/amaury/Zotero/storage/P2R366US/Misra and Kshemkalyani - 2021 - Byzantine Fault Tolerant Causal Ordering.pdf:application/pdf}, +} + +@inproceedings{tseng_distributed_2019, + title = {Distributed Causal Memory in the Presence of Byzantine Servers}, + doi = {10.1109/NCA.2019.8935059}, + abstract = {We study distributed causal shared memory (or distributed read/write objects) in the client-server model over asynchronous message-passing networks in which some servers may suffer Byzantine failures. Since Ahamad et al. proposed causal memory in 1994, there have been abundant research on causal storage. Lately, there is a renewed interest in enforcing causal consistency in large-scale distributed storage systems (e.g., {COPS}, Eiger, Bolt-on). However, to the best of our knowledge, the fault-tolerance aspect of causal memory is not well studied, especially on the tight resilience bound. In our prior work, we showed that 2 f+1 servers is the tight bound to emulate crash-tolerant causal shared memory when up to f servers may crash. In this paper, we adopt a typical model considered in many prior works on Byzantine-tolerant storage algorithms and quorum systems. In the system, up to f servers may suffer Byzantine failures and any number of clients may crash. We constructively present an emulation algorithm for Byzantine causal memory using 3 f+1 servers. We also prove that 3 f+1 is necessary for tolerating up to f Byzantine servers. In other words, we show that 3 f+1 is a tight bound. For evaluation, we implement our algorithm in Golang and compare their performance with two state-of-the-art fault-tolerant algorithms that ensure atomicity in the Google Cloud Platform.}, + eventtitle = {2019 {IEEE} 18th International Symposium on Network Computing and Applications ({NCA})}, + pages = {1--8}, + booktitle = {2019 {IEEE} 18th International Symposium on Network Computing and Applications ({NCA})}, + author = {Tseng, Lewis and Wang, Zezhi and Zhao, Yajie and Pan, Haochen}, + date = {2019-09}, + note = {{ISSN}: 2643-7929}, + keywords = {asynchrony, Byzantine faults, causal memory, Computer crashes, Consensus protocol, distributed storage system, Emulation, evaluation, Fault tolerance, Fault tolerant systems, History, Servers, tight condition}, + file = {IEEE Xplore Abstract Record:/home/amaury/Zotero/storage/DDV34ULW/8935059.html:text/html}, +} diff --git a/docs/bibliographie/liste_detaille.md b/docs/bibliographie/liste_detaille.md index e37e963..701d6bc 100644 --- a/docs/bibliographie/liste_detaille.md +++ b/docs/bibliographie/liste_detaille.md @@ -26,3 +26,7 @@ Pas spécifiquement à propos des fautes byzantines dans la cohérence faible ma __singh_zeno_2009__, "Zeno: Eventually Consistent Byzantine-Fault Tolerance": Algorithme pour de la convergence BFT. (Reflexions sur des erreurs byzanties possible + algo et implé) + +__tseng_distributed_2019__, "Algo BFT pour cohérence causale (preuve + experiences)" + +__misra_byzantine_2021__, "Preuve d'impossibilité de BFT dans un certain contexte pour de la cohérence causale + 2 algo pour de la cohérence causale BFT" \ No newline at end of file