Bounded-Memory Stream Processing

Özgür Lütfü Özçep

doi:10.1007/978-3-030-00111-7_32

Bounded-Memory Stream Processing

Institut für Informationssysteme

Abstract

Foundational work on stream processing is relevant for different areas of AI and it becomes even more relevant if the work concerns feasible and scalable stream processing. One facet of feasibility is treated under the term bounded memory. In this paper, streams are represented as finite or infinite words and stream processing is modelled with stream functions, i.e., functions mapping one or more input stream to an output stream. Bounded-memory stream functions can process input streams by using constant space only. The main result of this paper is a syntactical characterization of bounded-memory functions by a form of safe recursion.

Originalsprache	Englisch
Titel	KI 2018: Advances in Artificial Intelligence
Redakteure/-innen	Frank Trollmann, Anni-Yasmin Turhan
Seitenumfang	14
Band	11117
Erscheinungsort	Cham
Herausgeber (Verlag)	Springer International Publishing
Erscheinungsdatum	30.08.2018
Seiten	377-390
ISBN (Print)	978-3-030-00110-0
ISBN (elektronisch)	978-3-030-00111-7
DOIs	https://doi.org/10.1007/978-3-030-00111-7_32
Publikationsstatus	Veröffentlicht - 30.08.2018
Veranstaltung	41st German Conference on Artificial Intelligence - Berlin, Deutschland Dauer: 24.09.2018 → 28.09.2018 Konferenznummer: 218679

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Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung

SDG 9 – Industrie, Innovation und Infrastruktur

DFG-Fachsystematik

4.43-01 Theoretische Informatik

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10.1007/978-3-030-00111-7_32

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https://www.scopus.com/pages/publications/85054536335

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title = "Bounded-Memory Stream Processing",

abstract = "Foundational work on stream processing is relevant for different areas of AI and it becomes even more relevant if the work concerns feasible and scalable stream processing. One facet of feasibility is treated under the term bounded memory. In this paper, streams are represented as finite or infinite words and stream processing is modelled with stream functions, i.e., functions mapping one or more input stream to an output stream. Bounded-memory stream functions can process input streams by using constant space only. The main result of this paper is a syntactical characterization of bounded-memory functions by a form of safe recursion.",

author = "{\"O}z{\c c}ep, \{{\"O}zg{\"u}r L{\"u}tf{\"u}\}",

year = "2018",

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series = "Lecture Notes in Computer Science",

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pages = "377--390",

editor = "Frank Trollmann and Anni-Yasmin Turhan",

booktitle = "KI 2018: Advances in Artificial Intelligence",

note = "41st German Conference on Artificial Intelligence<br/>, KI 2018 ; Conference date: 24-09-2018 Through 28-09-2018",

}

Özçep, ÖL 2018, Bounded-Memory Stream Processing. in F Trollmann & A-Y Turhan (Hrsg.), KI 2018: Advances in Artificial Intelligence. Bd. 11117, Lecture Notes in Computer Science, Bd. 11117, Springer International Publishing, Cham, S. 377-390, 41st German Conference on Artificial Intelligence
, Berlin, Berlin, Deutschland, 24.09.18. https://doi.org/10.1007/978-3-030-00111-7_32

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AU - Özçep, Özgür Lütfü

N1 - Conference code: 218679

PY - 2018/8/30

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N2 - Foundational work on stream processing is relevant for different areas of AI and it becomes even more relevant if the work concerns feasible and scalable stream processing. One facet of feasibility is treated under the term bounded memory. In this paper, streams are represented as finite or infinite words and stream processing is modelled with stream functions, i.e., functions mapping one or more input stream to an output stream. Bounded-memory stream functions can process input streams by using constant space only. The main result of this paper is a syntactical characterization of bounded-memory functions by a form of safe recursion.

AB - Foundational work on stream processing is relevant for different areas of AI and it becomes even more relevant if the work concerns feasible and scalable stream processing. One facet of feasibility is treated under the term bounded memory. In this paper, streams are represented as finite or infinite words and stream processing is modelled with stream functions, i.e., functions mapping one or more input stream to an output stream. Bounded-memory stream functions can process input streams by using constant space only. The main result of this paper is a syntactical characterization of bounded-memory functions by a form of safe recursion.

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DO - 10.1007/978-3-030-00111-7_32

M3 - Conference contribution

SN - 978-3-030-00110-0

VL - 11117

T3 - Lecture Notes in Computer Science

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EP - 390

BT - KI 2018: Advances in Artificial Intelligence

A2 - Trollmann, Frank

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Y2 - 24 September 2018 through 28 September 2018

ER -

Bounded-Memory Stream Processing

Abstract

UN SDGs

DFG-Fachsystematik

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