Filtering and scalability in the ECO distributed event model

Haahr,; Meier,; Nixon, Lyndon; Cahill,; Jul,

doi:10.1109/pdse.2000.847853

Cited by 20 publications

(22 citation statements)

References 5 publications

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“…Examples include ECO [21], JavaPS [13], EventJava [14], Ptolemy [38], and EScala [19]. None of these provide any other features than propagation of implicit invocations; focusing on centralized deployments, Ptolemy or EScala could easily provide information on the number of publishers per subscriber or vice-versa.…”

Section: Implicit Invocationsmentioning

confidence: 99%

Aggregation for implicit invocations

Frischbier

Margara²,

Freudenreich

et al. 2013

Proceedings of the 12th Annual International Conference on Aspect-Oriented Software Development

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Implicit invocations are a popular mechanism for exchanging information between software components without binding these strongly. This decoupling is particularly important in distributed systems when interacting components are not known until runtime. In most realistic distributed systems though, components require some information about each other, be it only about their presence or their number. Runtime systems for implicit invocations-so-called publish/subscribe systems-are thus often combined with other systems providing such information.Given the variety of requirements for information about interacting components across applications, this paper proposes a generic augmentation of implicit invocations: rather than extending a given publish/subscribe API and system in order to convey a particular type of information across interacting components, we describe domain-specific joinpoints that can be used to advise application-level invocation routers-so-called brokers-used by publish/subscribe systems. This enables aggregation of application-specific information to and from components in a scalable manner.After presenting our domain-specific joinpoint model, we describe its implementation inside the REDS publish/subscribe middleware. The empirical evaluation of our approach shows that: (a) it outperforms external aggregation systems, by collecting and distributing information with a limited overhead; (b) the deployment of new functionalities has virtually no overhead, even if it occurs while the publish/subscribe system is running.

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Section: Implicit Invocationsmentioning

confidence: 99%

Aggregation for implicit invocations

Frischbier

Margara²,

Freudenreich

et al. 2013

Proceedings of the 12th Annual International Conference on Aspect-Oriented Software Development

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“…Simple predicated event handlers 1, 1, 1 . This includes content-based publish/subscribe multicast systems such as Siena [9] or languages inspired by the model (e.g., ECO [10], Java P S [11]), as well as Actor-based languages or Actor libraries supporting predicates on individual messages (e.g., Erlang 2 , Scala Actors [4], AmbientTalk [12]). Join languages 1, #, 0 .…”

Section: State Of the Art Of Cedmentioning

confidence: 99%

Scalable Efficient Composite Event Detection

Jayaram

Eugster

2010

Lecture Notes in Computer Science

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Abstract. Composite event detection (CED) is the task of identifying combinations of events which are meaningful with respect to programdefined patterns. Recent research in event-based programming has focused on language design (in different paradigms), leading to a wealth of prototype programming models and languages. However, implementing CED in an efficient and scalable manner remains an under-addressed problem. In fact, the lack of scalable algorithms is the main roadblock to incorporating support for more expressive event patterns into prominent event-based programming languages. This lack of scalable algorithms is a particularly acute problem in event stream processing, where event patterns can additionally be specified over time windows. In this paper we describe GenTrie, a deterministic trie-based algorithm for CED. We describe how complex event patterns are split, how each sub-pattern maps to a node in the trie, and demonstrate through empirical evaluation that GenTrie has higher throughput than current implementations of related languages.

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“…There are three main types of distribute event-based systems [15]: co-located middleware -the event service is in the same address space as the clients (e.g., mSECO [11]); single separated middleware -the event service is located on a single machine while the clients are distributed on other machines (e.g., CORBA); multiple separated middleware -clients and event service are distributed and execute on different machines or address spaces (e.g., SIENA). While our approach could be applied to all three types of system, we chose SIENA because both the clients and middleware are distributed making it a challenging architecture in which to discover mismatch.…”

Section: Distributed Event-based Systemsmentioning

confidence: 99%

Verifying Distributed, Event-Based Middleware Applications Using Domain-Specific Software Model Checking

Cai

Bradbury

Dingel

2007

Lecture Notes in Computer Science

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Abstract. The success of distributed event-based infrastructures such as SIENA and Elvin is partially due to their ease of use. Even novice users of these infrastructures not versed in distributed programming can quickly comprehend the small and intuitive interfaces that these systems typically feature. However, if these users make incorrect assumptions about how the infrastructure services work, a mismatch between the infrastructure and its client applications occurs, which may manifest itself in erroneous client behaviour. We propose a framework for automatically model checking distributed event-based systems in order to discover mismatch between the infrastructure and its clients. Using the SIENA event service as an example, we implemented and evaluated our framework by customizing the Bandera/Bogor tool pipeline. Two realistic Java applications are implemented to test and evaluate the framework.

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Filtering and scalability in the ECO distributed event model

Abstract: Abstract

Cited by 20 publications

References 5 publications

Aggregation for implicit invocations

Aggregation for implicit invocations

Scalable Efficient Composite Event Detection

Verifying Distributed, Event-Based Middleware Applications Using Domain-Specific Software Model Checking

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