Lazy Replication: Exploiting the Semantics of Distributed Services

Ladin, Rivka; Liskov, Barbara; Shrira, Liuba; Ghemawat, Sanjay

doi:10.21236/ada225584

Cited by 20 publications

(34 citation statements)

References 8 publications

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“…This application-defined explicit causality [5,16,7] is a small subset of traditional potential causality and dramatically reduces the depth and degree of the causality graph, ameliorating scalability concerns. To quantitatively illustrate these effects, we draw on a substantial body of literature studying behavior patterns in modern Internet services ( §4.1).…”

Section: Better Living Through Semantic Contextmentioning

confidence: 99%

“…While prior research briefly considered variants of explicit causality in the form of "state"-and "client"-level dependency tracking [4,5,16], its time has finally come: modern applications like social networking hugely benefit from semantic pruning of causal relationships. To quantitatively study the structure of explicit causality graphs, we surveyed existing literature on user behavior on several modern human-facing Internet services.…”

Section: Explicit Causality In the Wildmentioning

confidence: 99%

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The potential dangers of causal consistency and an explicit solution

Bailis

Fekete

Ghodsi

et al. 2012

Proceedings of the Third ACM Symposium on Cloud Computing

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Causal consistency is the strongest consistency model that is available in the presence of partitions and provides useful semantics for human-facing distributed services. Here, we expose its serious and inherent scalability limitations due to write propagation requirements and traditional dependency tracking mechanisms. As an alternative to classic potential causality, we advocate the use of explicit causality, or applicationdefined happens-before relations. Explicit causality, a subset of potential causality, tracks only relevant dependencies and reduces several of the potential dangers of causal consistency.

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Section: Better Living Through Semantic Contextmentioning

confidence: 99%

Section: Explicit Causality In the Wildmentioning

confidence: 99%

The potential dangers of causal consistency and an explicit solution

Bailis

Fekete

Ghodsi

et al. 2012

Proceedings of the Third ACM Symposium on Cloud Computing

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show abstract

“…Synchronous updating ensures strong consistency among replicas. Asynchronous updating allows one or a portion of replicas is updated first, and others can be updated later [4] . Consistency problems can occur during asynchronous updating since the completion of such updating does not mean that all replicas have been updated.…”

Section: B Replica Update Strategymentioning

confidence: 99%

A Two-Layered Replica Management Method

Yang

Zhou

2011

2011IEEE 10th International Conference on Trust, Security and Privacy in Computing and Communications

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Replica management method has been widely used in distributed file system to improve parallelism and reliability. Traditional replica management method is synchronous replication management (SRM) which updates replicas synchronously. Because of synchronous updating, it is difficult to provide high throughput and low access latency. If the system achieves SRM in the memory hierarchy, it will take a lot of memory space.In order to improve write performance, we design a Two-Layered Replica Management Method (TLRMM) based on memory and disk. It can be used for disk-based or memory-based data storage system. TLRMM maintains 3 replicas for every chunk and store one in memory. Using asynchronous update, it can improve the system's I/O performance significantly. We integrated TLRMM in Carrier which is a distributed file system designed by Tsinghua University, and use version number to ensure replica consistency. Furthermore, in order to ensure the reliability of Carrier, we design a replica recovery strategy to solve the failure of single point. We have implemented and evaluated the integrated prototype system. The experimental results show that TLRMM can deliver high performance on distributed file system. Compared with SRM, write throughput of TLRMM increased by a factor of 1.62 2.05, without read performance degradation.

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“…In fact, it is already contemplated in distributed systems [7], [8], [9], [10], [11], but their approaches aren't suited to the Web architecture.…”

Section: Existing Problemsmentioning

confidence: 99%

Implementing offline work in Web applications for rich domains

Goncalves

Leitão

2009

2009 11th IEEE International Symposium on Web Systems Evolution

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Web applications are the preferred information system platform for many organizations. Some tasks, though, must be done offline, either for connectivity costs and reliability or security constraints. Still, offline work isn't a common feature in Web applications, for it demands a more complex software architecture and a difficult development process. Existing applications are even harder to adapt with offline support, usually implying writing alternate versions of its code.We provide a novel development methodology that speeds up the implementation of offline work in a Web application with a rich domain. It is based on the deployment of the server functionalities on the local machine. Replicating all data to the local server isn't practical for application's with large domain. We overcome this by enhancing the local server with an adaptive prefetcher that, while online, keeps fetching useful data from the remote server. To select the best suggestions, heuristics are applied to profiled data.We discuss the application of this methodology in a Web server prototype. We discuss the choice of heuristics, and enhance the prototype with a statistics collector, to measure their usefulness. We also show how we can identify functional modules and find errors on the application by using the collected information.

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Lazy Replication: Exploiting the Semantics of Distributed Services

Cited by 20 publications

References 8 publications

The potential dangers of causal consistency and an explicit solution

The potential dangers of causal consistency and an explicit solution

A Two-Layered Replica Management Method

Implementing offline work in Web applications for rich domains

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