Grapevine

Birrell, Andrew; Levin, Roy; Schroeder, Michael; Needham, Roger M.

doi:10.1145/358468.358487

Cited by 341 publications

(118 citation statements)

References 6 publications

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“…[40,39,19,53] Such lessons were not lost on the system designers of the early 1980s. Production systems such as Locus [77] and Grapevine [16] wrestled with the fundamental tension between consistency, availability, and performance in distributed systems.…”

Section: Introductionmentioning

confidence: 99%

Distributed computing in practice: the Condor experience

Thain

Tannenbaum

Livny

2005

Concurrency and Computation

1,481

831

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SUMMARYSince 1984, the Condor project has enabled ordinary users to do extraordinary computing. Today, the project continues to explore the social and technical problems of cooperative computing on scales ranging from the desktop to the world-wide computational grid. In this chapter, we provide the history and philosophy of the Condor project and describe how it has interacted with other projects and evolved along with the field of distributed computing. We outline the core components of the Condor system and describe how the technology of computing must correspond to social structures. Throughout, we reflect on the lessons of experience and chart the course traveled by research ideas as they grow into production systems.

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Section: Introductionmentioning

confidence: 99%

Distributed computing in practice: the Condor experience

Thain

Tannenbaum

Livny

2005

Concurrency and Computation

1,481

831

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“…Although the only operations that adhere to these constraints may be the operations of logical conjunction and disjunction or comparable operations over alternate domains, merge operations that do not adhere to these principles may be modified into operations that do. Standard distributed database implementations account for the transitivity and implicit monotonicity of network communications when performing non-transitive and non-monotonic deletions [6]. Similar adaptations of other merge operations may be possible.…”

Section: Propagators In a Distributed Systemmentioning

confidence: 99%

Data Provenance in Distributed Propagator Networks

Jacobi

2010

Lecture Notes in Computer Science

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Abstract. The heterogeneous and unreliable nature of distributed systems has created a distinct need for the inclusion of provenance within their design to allow for error correction and redundancy. Many traditional distributed systems have limited provenance tracing abilities, usually included in generic workflow generation or in an application-specific way. The novel programming paradigm of distributed propagator networks allows for the inclusion of provenance from the ground up. In this paper, I present the concept of propagator networks and demonstrate how provenance may be easily integrated into programs built using them. I also demonstrate the possibility of converting non-provenanceaware applications built using propagator networks into provenanceaware applications by simply performing a transformation of the existing program structure.

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“…Inaccurate information is not a problem in some cases. For example, in a mail system (e.g., [7]), a request to read mail need not produce all messages that have been sent; a promise of timely delivery is sufficient. Other applications require accurate information.…”

Section: The Highly-available Servicementioning

confidence: 99%

Highly-Available Distributed Services and Fault-Tolerant Distributed Garbage Collection

Liskov¹,

Ladin²

1986

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This paper describes two techniques that are only loosely related. The first is a method for constructing a highly available service for use in a distributed system. The service presents its clients with a consistent view of its state, but the view may contain old information. Clients can indicate how recent the information must be. The method can be used in any application in which the property of interest is stable: once the property becomes true, it remains true forever.The paper also describes a fault-tolerant garbage collection method for a distributed heap. The method is practical and efficient. Each computer that contains part of the heap does local garbage collection independently, using whatever algorithm it chooses, and without needing to communicate with the other computers that contain parts of the heap. The highly available central service is used to store information about inter.computer references.

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Grapevine

Cited by 341 publications

References 6 publications

Distributed computing in practice: the Condor experience

Distributed computing in practice: the Condor experience

Data Provenance in Distributed Propagator Networks

Highly-Available Distributed Services and Fault-Tolerant Distributed Garbage Collection

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