WO2017165712A1 - Composition of pattern-driven reactions in real-time dataflow programming - Google Patents

Composition of pattern-driven reactions in real-time dataflow programming Download PDF

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Publication number
WO2017165712A1
WO2017165712A1 PCT/US2017/023911 US2017023911W WO2017165712A1 WO 2017165712 A1 WO2017165712 A1 WO 2017165712A1 US 2017023911 W US2017023911 W US 2017023911W WO 2017165712 A1 WO2017165712 A1 WO 2017165712A1
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WO
WIPO (PCT)
Prior art keywords
input
data
state
pattern
matched
Prior art date
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Ceased
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PCT/US2017/023911
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English (en)
French (fr)
Inventor
Jason Lucas
Abhishek Sharma
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Foghorn Systems Inc
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Foghorn Systems Inc
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Publication date
Application filed by Foghorn Systems Inc filed Critical Foghorn Systems Inc
Priority to EP17771200.7A priority Critical patent/EP3433769B1/en
Priority to CN202210437492.5A priority patent/CN115373977A/zh
Priority to KR1020187030472A priority patent/KR102092721B1/ko
Priority to JP2018549799A priority patent/JP6896759B2/ja
Priority to CN201780019786.3A priority patent/CN108885580B/zh
Priority to AU2017238637A priority patent/AU2017238637B2/en
Publication of WO2017165712A1 publication Critical patent/WO2017165712A1/en
Priority to SA518400084A priority patent/SA518400084B1/ar
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/44—Arrangements for executing specific programs
    • G06F9/448—Execution paradigms, e.g. implementations of programming paradigms
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F8/00—Arrangements for software engineering
    • G06F8/30—Creation or generation of source code
    • G06F8/35—Creation or generation of source code model driven
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/36—Prevention of errors by analysis, debugging or testing of software
    • G06F11/3668—Testing of software
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/36—Prevention of errors by analysis, debugging or testing of software
    • G06F11/3698—Environments for analysis, debugging or testing of software
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F8/00—Arrangements for software engineering
    • G06F8/30—Creation or generation of source code
    • G06F8/31—Programming languages or programming paradigms
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F8/00—Arrangements for software engineering
    • G06F8/30—Creation or generation of source code
    • G06F8/34—Graphical or visual programming
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F8/00—Arrangements for software engineering
    • G06F8/40—Transformation of program code
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/44—Arrangements for executing specific programs
    • G06F9/448—Execution paradigms, e.g. implementations of programming paradigms
    • G06F9/4498—Finite state machines
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/48—Program initiating; Program switching, e.g. by interrupt
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9535—Search customisation based on user profiles and personalisation

Definitions

  • Figure 16 shows a hierarchy of kinds of nodes.
  • Nonvolatile media includes, for example, flash memory, or optical or magnetic disks.
  • FogHorn edge services operate at the edge of the network where the IIoT devices reside.
  • the edge software stack is responsible for ingesting the data from sensors and industrial devices onto a high speed data bus and then executing user-defined analytics expressions on the streaming data to gain insights and optimize the devices.
  • These analytical expressions are executed by FogHorn's highly scalable and small footprint complex event processing (CEP) engine.
  • CEP complex event processing
  • Function translation consists of accepting a source text, breaking the text into tokens, and then, guided by a grammar, arranging the tokens such that they form the leaves of an abstract syntax tree (AST) which describes the syntactic content of the source text.
  • AST abstract syntax tree
  • the abstract syntax tree is then traversed by a series of algorithms which ultimately produce the blocks of instructions required to evaluate the functions described by the source.
  • Dataflow programming models a computer program as a directed graph, called a flowgraph, with each exterior node specifying an input or output of the program, and each interior node specifying an operation to be performed.
  • the data flowing into each node provides the input to its operation and the result of its operation provides the data flowing out of the node.
  • a directed edge between a pair of nodes causes the output of the one node to become the input of the other.
  • a node which transmits outputs is termed a producer, while a node which receives inputs data is termed a consumer.
  • An injector is a kind of producer, and an extractor is a kind of consumer.
  • a transducer is both a producer and a consumer.
  • Figure 16 depicts this relationship.
  • Figure 16 shows a hierarchy of kinds of nodes. An injector 1608 and a transducer 1613 input to a producer 1619. Transducer 1613 and an extractor 1622 input to a consumer 1625. Producer 1619 and consumer 1625 input to a node 1634.
  • op4 in Figure 14 is a transducer which consumes two streams of integers as input (along edges e5 and e6) and produces a stream of integers as output (along edge e7).
  • op4 is programmed in such a way that, each time an input arrives along e6, op4 will store a copy of the input internally. In this way, op4 will always know the most recent value from e6, but the arrival of values along e6 will not cause op4 to produce anything.
  • Pattern Rules A pattern rule a form of logical expression which declares a pattern to be expected in a stream of input. It looks similar to a lambda expression, but we distinguish it from such by introducing it with a lower-case pi ( ⁇ ) instead.
  • a pattern which has not yet been satisfied results in a cold transducer, while a pattern which is fully satisfied results in a hot transducer.
  • a pattern of variable length is partially met, we require a new state, warm, to describe the transducer.
  • a warm transducer is ready to produce an output, but need not do so. This is in contrast to a hot transducer, which is ready and must produce as soon as possible.
  • joining is a yoking together of two or more input streams which are to be evaluated together to produce a single output stream. For example, if we had two sensors in a refrigerator, one for the door and the other for temperature, we might join the two streams together to produce an average temperature when the door is closed.

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Software Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Hardware Design (AREA)
  • Quality & Reliability (AREA)
  • Databases & Information Systems (AREA)
  • Computing Systems (AREA)
  • Data Mining & Analysis (AREA)
  • Computer And Data Communications (AREA)
  • Debugging And Monitoring (AREA)
  • Stored Programmes (AREA)
  • Information Transfer Between Computers (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
  • Data Exchanges In Wide-Area Networks (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Devices For Executing Special Programs (AREA)
  • User Interface Of Digital Computer (AREA)
  • Testing Or Calibration Of Command Recording Devices (AREA)
PCT/US2017/023911 2016-03-23 2017-03-23 Composition of pattern-driven reactions in real-time dataflow programming Ceased WO2017165712A1 (en)

Priority Applications (7)

Application Number Priority Date Filing Date Title
EP17771200.7A EP3433769B1 (en) 2016-03-23 2017-03-23 Composition of pattern-driven reactions in real-time dataflow programming
CN202210437492.5A CN115373977A (zh) 2016-03-23 2017-03-23 实时数据流编程中模式驱动反应的组合
KR1020187030472A KR102092721B1 (ko) 2016-03-23 2017-03-23 실시간 데이터플로우 프로그래밍에서 패턴 구동형 반응의 구성
JP2018549799A JP6896759B2 (ja) 2016-03-23 2017-03-23 リアルタイムデータフロープログラミングにおけるパターン駆動型反応の合成
CN201780019786.3A CN108885580B (zh) 2016-03-23 2017-03-23 实时数据流编程中模式驱动反应的组合
AU2017238637A AU2017238637B2 (en) 2016-03-23 2017-03-23 Composition of pattern-driven reactions in real-time dataflow programming
SA518400084A SA518400084B1 (ar) 2016-03-23 2018-09-23 تركيبة من تفاعلات قائمة على الأنماط في برمجة تدفق البيانات في الوقت الحقيقي

Applications Claiming Priority (8)

Application Number Priority Date Filing Date Title
US201662312255P 2016-03-23 2016-03-23
US201662312106P 2016-03-23 2016-03-23
US201662312187P 2016-03-23 2016-03-23
US201662312223P 2016-03-23 2016-03-23
US62/312,106 2016-03-23
US62/312,187 2016-03-23
US62/312,223 2016-03-23
US62/312,255 2016-03-23

Publications (1)

Publication Number Publication Date
WO2017165712A1 true WO2017165712A1 (en) 2017-09-28

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Application Number Title Priority Date Filing Date
PCT/US2017/023911 Ceased WO2017165712A1 (en) 2016-03-23 2017-03-23 Composition of pattern-driven reactions in real-time dataflow programming
PCT/US2017/023906 Ceased WO2017165708A1 (en) 2016-03-23 2017-03-23 Efficient state machines for real-time dataflow programming
PCT/US2017/023912 Ceased WO2017165713A1 (en) 2016-03-23 2017-03-23 Tools and methods for real-time dataflow programming language

Family Applications After (2)

Application Number Title Priority Date Filing Date
PCT/US2017/023906 Ceased WO2017165708A1 (en) 2016-03-23 2017-03-23 Efficient state machines for real-time dataflow programming
PCT/US2017/023912 Ceased WO2017165713A1 (en) 2016-03-23 2017-03-23 Tools and methods for real-time dataflow programming language

Country Status (8)

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US (12) US10564941B2 (enExample)
EP (3) EP3433711B1 (enExample)
JP (5) JP2019516167A (enExample)
KR (3) KR102092722B1 (enExample)
CN (5) CN108885545B (enExample)
AU (4) AU2017238633B2 (enExample)
SA (3) SA518400084B1 (enExample)
WO (3) WO2017165712A1 (enExample)

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