Event processing under uncertainty

Artikis, Alexander; Etzion, Opher; Feldman, Zohar; Fournier, Fabiana

doi:10.1145/2335484.2335488

Cited by 42 publications

(36 citation statements)

References 38 publications

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“…At the application level, discussions of asynchrony are limited to event processing architectures [9]. There is little discussion, however, of protocol enactments where the end points are maximally decoupled from each other.…”

Section: B Asynchrony and Decoupled Enactmentmentioning

confidence: 99%

The Internet of Things and Multiagent Systems: Decentralized Intelligence in Distributed Computing

Singh

Chopra

2017

2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)

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Abstract-Traditionally, distributed computing concentrates on computation understood at the level of information exchange and sets aside human and organizational concerns as largely to be handled in an ad hoc manner. Increasingly, however, distributed applications involve multiple loci of autonomy. Research in multiagent systems (MAS) addresses autonomy by drawing on concepts and techniques from artificial intelligence. However, MAS research generally lacks an adequate understanding of modern distributed computing.In this Blue Sky paper, we envision decentralized multiagent systems as a way to place decentralized intelligence in distributed computing, specifically, by supporting computation at the level of social meanings. We motivate our proposals for research in the context of the Internet of Things (IoT), which has become a major thrust in distributed computing. From the IoT's representative applications, we abstract out the major challenges of relevance to decentralized intelligence. These include the heterogeneity of IoT components; asynchronous and delay-tolerant communication and decoupled enactment; and multiple stakeholders with subtle requirements for governance, incorporating resource usage, cooperation, and privacy. The IoT yields high-impact problems that require solutions that go beyond traditional ways of thinking.We conclude with highlights of some possible research directions in decentralized MAS, including programming models; interaction-oriented software engineering; and what we term enlightened governance.

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Section: B Asynchrony and Decoupled Enactmentmentioning

confidence: 99%

The Internet of Things and Multiagent Systems: Decentralized Intelligence in Distributed Computing

Singh

Chopra

2017

2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)

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“…Many of the key challenges faced for implementing real-time processing for Web Observatories is also situated in a wider community of research of involved in real-time stream processing [18,2]. As Heinze et al [10] describe, there are several important aspects of (real-time) stream processing including designing scalable solutions which are able to both partition and query data efficiently, and systems which have an amount of fault tolerance, being able to actively respond to changes in stream conditions.…”

Section: Real-time Processingmentioning

confidence: 99%

A Streaming Real-Time Web Observatory Architecture for Monitoring the Health of Social Machines

Tinati

Wang

Brown

et al. 2015

Proceedings of the 24th International Conference on World Wide Web

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Over the past years, streaming Web services have become popular, with many of the top Web platforms now offering near real-time streams of user and machine activity. In light of this, Web Observatories now are faced with the challenge of being able to process and republish real-time, big data, Web streams, whilst maintaining access control and data consistency. In this paper we describe the architecture used in the Southampton Web Observatory to harvest, process, and serve real-time Web streams.

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“…Other approaches involving probabilistic event processing (for timing, computation and communication errors) have been developed, e.g., [27]. Our approach is targeted towards distributed real-time applications applied onto lightweight nodes, hence computational and memory efficiency of the CEP implementation is a prime requirement, not feasible using AI approaches like [27].…”

Section: Related Workmentioning

confidence: 99%

“…Our approach is targeted towards distributed real-time applications applied onto lightweight nodes, hence computational and memory efficiency of the CEP implementation is a prime requirement, not feasible using AI approaches like [27]. Our approach also stands out by proposing the use of a stanards based SOA middleware, in contrast to proprietary middleware for the transportation and communication of (complex) events.…”

Section: Related Workmentioning

confidence: 99%

A SOA approach to delay and jitter tolerant distributed real-time Complex Event Processing

Lindgren

Kyusakov

Eliasson

et al. 2013

2013 IEEE International Symposium on Industrial Electronics

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Abstract-The combination of Service Oriented Architectures (SOAs) and Complex Event Processing (CEP) is gaining momentum for event centric management and processing of information in complex distributed systems (e.g., business automation). Whereas systems for factory automation have traditionally been deployed using dedicated buses and proprietary (often scan based) protocols, a recent trend in process automation is towards adopting open internet based technologies and event based communication. This trend is driven by the increasing number and capabilities of devices used for monitoring and control, and the increased flexibility, maintainability and price/performance gains expected from IP (potentially SOA/CEP) enabled systems.In this paper we discuss the challenges involved to apply SOA and CEP to the field of factory automation. In particular, realtime aspects are highlighted, both w.r.t. to accurate time-stamping of physical events in a distributed system, as well as end-to-end timing including communication and CEP processing.We approach the challenges by an architecture combining state-of-the-art synchronisation mechanisms for wired and wireless networks together with real-time communication and distributed query processing based on the notion of time constrained reactions. We discuss the impact of synchronisation inaccuracies and delays introduced by processing and communication, and present a method for implementation of safe potential-and certain matches.

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Event processing under uncertainty

Cited by 42 publications

References 38 publications

The Internet of Things and Multiagent Systems: Decentralized Intelligence in Distributed Computing

The Internet of Things and Multiagent Systems: Decentralized Intelligence in Distributed Computing

A Streaming Real-Time Web Observatory Architecture for Monitoring the Health of Social Machines

A SOA approach to delay and jitter tolerant distributed real-time Complex Event Processing

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