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Computing Paradigms

  • Chapter
Metasynthetic Computing and Engineering of Complex Systems

Part of the book series: Advanced Information and Knowledge Processing ((AI&KP))

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Abstract

To analyze, design, and implement problem-solving solutions for complex systems, we need effective computing paradigms. The methodologies for engineering complex systems have been evolving toward:

  1. 1.

    Addressing increasingly complex problems and building corresponding systems

  2. 2.

    Providing more user-friendly interfaces

  3. 3.

    Supporting enterprise application integration

Usually, a computing paradigm (methodology) is proposed on top of a core metaphor and concept. With the proposal of core concepts such as objects, components, services, agents, agent service, organization, and cloud, corresponding software engineering methodologies have also been proposed or are the subject of study at the same time. Objects [1], components [2], services [3], and agents [4] are very popular but high-level abstraction conceptions. They have been or are currently used by software academic designers and industrial architects to construct software systems that model the real world. Subsequently, methodologies including object-oriented methodology, component-based methodology, service-oriented methodology, and agent-oriented methodology have been proposed to analyze, design, and implement the complexities in complex systems (usually engineering systems).

In addition, increased attention has been paid to other general concepts in the social science, economics, and cultural domains; for instance, behavior, organization, autonomy, sociality, cloud, and service. These have formed new computing paradigms, including autonomic computing, behavior computing, social computing, and cloud computing. More recently, to address the system complexities in open complex systems, metasynthetic computing has been proposed.

In this chapter, the concepts, basic principles, and strengths and weaknesses of the above core concepts and computing paradigms are discussed. The aim is to provide basic concepts to understand what computing and engineering methodologies are available and which of these are the most suitable for analyzing, designing, and implementing open complex systems.

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Authors and Affiliations

  1. Advanced Analytics Institute, University of Technology, Sydney, Sydney, New South Wales, Australia

    Longbing Cao

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  1. Longbing Cao
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Cao, L. (2015). Computing Paradigms. In: Metasynthetic Computing and Engineering of Complex Systems. Advanced Information and Knowledge Processing. Springer, London. https://doi.org/10.1007/978-1-4471-6551-4_4

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  • DOI: https://doi.org/10.1007/978-1-4471-6551-4_4

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-6550-7

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