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In-network Processing for Context-Aware SOA-based Manufacturing Systems
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.ORCID iD: 0000-0001-9484-9766
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.ORCID iD: 0000-0001-9586-0991
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.ORCID iD: 0000-0002-4133-3317
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.ORCID iD: 0000-0003-3874-9968
2017 (English)In: Proceedings IECON 2017: 43rd Annual Conference of the IEEE Industrial Electronics Society, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017, , p. 6p. 3460-3465Conference paper, Published paper (Refereed)
Abstract [en]

To achieve flexible manufacturing, increasingly largeamounts of data are being generated, stored, analyzed, archivedand eventually fed back into the product life cycle. But whereis this data stored and how is it transported? Current methodsrely on centralized or federated databases to manage the datastorage. This approach has several challenges, such as collectionbottlenecks, secure retrieval, single point of failure and dataschemefragility as data heterogeneity increases. Additionally,manufacturers are finding the need to open their networks forservice based equipment suppliers. This means previous securityassumptions regarding network encryption and informationaccess-control must be re-evaluated.Proposed here is a method of in-network processing thatgathers information only where and when it is needed. Systemsbuild context at runtime by creating dynamic queries whichmake service composition. The service composition processes rawdata and presents it as information to the calling system. Thisreduces the movement of data/information and removes singlepoint collection bottlenecks. Furthermore, fine grained accesscontrol and shared trust can be granted between untrustedsystems. The proposed methods are demonstrated on a lab setupof an industrial use case.

Place, publisher, year, edition, pages
Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017. , p. 6p. 3460-3465
Series
IEEE Industrial Electronics Society, ISSN 1553-572X
National Category
Engineering and Technology Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Industrial Electronics
Identifiers
URN: urn:nbn:se:ltu:diva-66354DOI: 10.1109/IECON.2017.8216586ISI: 000427164803070Scopus ID: 2-s2.0-85046654831ISBN: 978-1-5386-1127-2 (electronic)OAI: oai:DiVA.org:ltu-66354DiVA, id: diva2:1154293
Conference
43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017, Bejing, China, 29 October - 1 November 2017
Available from: 2017-11-02 Created: 2017-11-02 Last updated: 2018-05-21Bibliographically approved
In thesis
1. Architectural Design Principles For Industrial Internet of Things
Open this publication in new window or tab >>Architectural Design Principles For Industrial Internet of Things
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Arkitektuella designprinciper för industriellt internet
Abstract [en]

As society has progressed through periods of evolution and revolution, technology hasplayed a key role as an enabler. In the same manner that mechanical machines of the1800’s drove the industrial revolution, now digitalized machines are driving another one.With this recognition of a fourth industrial revolution, the Industry 4.0 initiative wasfounded. One of the drivers of Industry 4.0 is the Industrial Internet of Things (IIoT).

The IIoT is a consequence of widely present computing ubiquity and interconnected-ness. Software has become a crucial tool of almost all industries from bakeries and arts to manufacturing facilities and banking. Programming is now a required competenceand used by a variety of professions. It is not only about algorithm development, it has become more about engineering and integrating existing designs and tools. This impacts the way software is architected and drives a large body of research in the area.

Software solutions are becoming more distributed, not only over multiple processes, but over heterogeneous hardware and business domains. Computing platforms could bemobile or geographically separated over large distances, exposing the solutions to network disturbances, performance degradation and security vulnerabilities.

Hence, IIoT introduces complexity on a scale previously unseen in the software in-dustry. Software architecture must accommodate these heterogeneous domains and com-petencies and handle the increasing levels of complexity.

This thesis proposes an architectural style for designing IIoT software architectures.The popular Service Oriented Architecture (SOA) style is not sufficient to define a com-plete architecture for IIoT applications. SOA fundamental principles are defined as loose coupling, lookup and late binding. The proposed architecture style extends these SOA principles with autonomy, specialization, data at its source and first person perspective. It preserves the benefits of SOA that models functionalities as reusable services with standardized interfaces. Thus, the proposed style helps to capture the heterogeneity of IIoT (e.g. systems, capabilities, domains, competencies etc.), while handling challenges imposed by it. The style also captures resource constraints of IIoT platforms; distri-bution of application logic across IIoT; dependence between services within IIoT; and presentation of the solution in various stakeholder perspectives.

The IIoT generates large amounts of data that is subsequently stored, analysed, archived and eventually fed back into the product life cycle. Centralization of data has well known challenges. This thesis proposes a method of information extraction based on the principle of data at its source. Such data preserves implicit context, reducing the burden of semantic data within the system. Desired information is expressed through dynamic (runtime) queries. Using the queries, a path is created to retrieve the requested data. It alleviates the need for data to be stored in intermediary nodes; data remains atthe source. Thus, IIoT applications extract information and present it to requesting sys-tems without redundant source related context. This helps with issues of data ownership, access control and stale data.

Another IIoT challenge tackled in this work is decentralization of Manufacturing Execution System (MES). It is motivated by a need to mitigate the impact of vulnerable shared networks on the factory floor; and by business requirements to reduce dependence on local factory infrastructure. This thesis explores a solution where functions of MES are distributed to the workstations that enables them to operate autonomously. Such autonomous workstations utilize the proposed Intelligent Product, Workflow Managerand Workflow Executor systems. Thus, MES can be decentralized to edge nodes as envisioned by Industry 4.0.

Place, publisher, year, edition, pages
Luleå: Luleå University of Technology, 2018
Series
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
National Category
Computer Systems Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Industrial Electronics
Identifiers
urn:nbn:se:ltu:diva-68463 (URN)978-91-7790-128-0 (ISBN)978-91-7790-129-7 (ISBN)
Public defence
2018-05-29, C305, Luleå, 10:00 (English)
Opponent
Supervisors
Available from: 2018-04-24 Created: 2018-04-23 Last updated: 2018-05-21Bibliographically approved

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Derhamy, Hasan

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