{"title":"Byzantine-tolerant detection of causality: There is no holy grail","authors":"Anshuman Misra , Ajay D. Kshemkalyani","doi":"10.1016/j.parco.2025.103136","DOIUrl":null,"url":null,"abstract":"<div><div>Detecting causality or the “happened before” relation between events in an asynchronous distributed system is a widely used building block in distributed applications. To the best of our knowledge, this problem has not been examined in a system with Byzantine processes. We prove the following results for an asynchronous system with Byzantine processes. (1) We prove that it is impossible to determine causality between events in the presence of even a single Byzantine process when processes communicate by unicasting. (2) We also prove a similar impossibility result when processes communicate by broadcasting. (3) We also prove a similar impossibility result when processes communicate by multicasting. (4–5) In an execution where there exists a causal path between two events passing through only correct processes, we prove that it is possible to detect causality between such a pair of events when processes communicate by unicasting or broadcasting. (6) However, when processes communicate by multicasting and there exists a causal path between two events passing through only correct processes, we prove that it is impossible to detect causality between such a pair of events. (7–9) Even with the use of cryptography, we prove that the impossibility results of (1–3) for unicasts, broadcasts, and multicasts, respectively, hold. (10–12) With the use of cryptography, when there exists a causal path between two events passing through only correct processes, we prove it is possible to detect causality between such a pair of events, irrespective of whether the communication is by unicasts, broadcasts, or multicasts. Our results are significant because Byzantine systems mirror the real world.</div></div>","PeriodicalId":54642,"journal":{"name":"Parallel Computing","volume":"124 ","pages":"Article 103136"},"PeriodicalIF":2.0000,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Parallel Computing","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167819125000122","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Detecting causality or the “happened before” relation between events in an asynchronous distributed system is a widely used building block in distributed applications. To the best of our knowledge, this problem has not been examined in a system with Byzantine processes. We prove the following results for an asynchronous system with Byzantine processes. (1) We prove that it is impossible to determine causality between events in the presence of even a single Byzantine process when processes communicate by unicasting. (2) We also prove a similar impossibility result when processes communicate by broadcasting. (3) We also prove a similar impossibility result when processes communicate by multicasting. (4–5) In an execution where there exists a causal path between two events passing through only correct processes, we prove that it is possible to detect causality between such a pair of events when processes communicate by unicasting or broadcasting. (6) However, when processes communicate by multicasting and there exists a causal path between two events passing through only correct processes, we prove that it is impossible to detect causality between such a pair of events. (7–9) Even with the use of cryptography, we prove that the impossibility results of (1–3) for unicasts, broadcasts, and multicasts, respectively, hold. (10–12) With the use of cryptography, when there exists a causal path between two events passing through only correct processes, we prove it is possible to detect causality between such a pair of events, irrespective of whether the communication is by unicasts, broadcasts, or multicasts. Our results are significant because Byzantine systems mirror the real world.
期刊介绍:
Parallel Computing is an international journal presenting the practical use of parallel computer systems, including high performance architecture, system software, programming systems and tools, and applications. Within this context the journal covers all aspects of high-end parallel computing from single homogeneous or heterogenous computing nodes to large-scale multi-node systems.
Parallel Computing features original research work and review articles as well as novel or illustrative accounts of application experience with (and techniques for) the use of parallel computers. We also welcome studies reproducing prior publications that either confirm or disprove prior published results.
Particular technical areas of interest include, but are not limited to:
-System software for parallel computer systems including programming languages (new languages as well as compilation techniques), operating systems (including middleware), and resource management (scheduling and load-balancing).
-Enabling software including debuggers, performance tools, and system and numeric libraries.
-General hardware (architecture) concepts, new technologies enabling the realization of such new concepts, and details of commercially available systems
-Software engineering and productivity as it relates to parallel computing
-Applications (including scientific computing, deep learning, machine learning) or tool case studies demonstrating novel ways to achieve parallelism
-Performance measurement results on state-of-the-art systems
-Approaches to effectively utilize large-scale parallel computing including new algorithms or algorithm analysis with demonstrated relevance to real applications using existing or next generation parallel computer architectures.
-Parallel I/O systems both hardware and software
-Networking technology for support of high-speed computing demonstrating the impact of high-speed computation on parallel applications