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Social Clouds: Crowdsourcing Cloud Infrastructure

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Book cover Crowdsourcing

Part of the book series: Progress in IS ((PROIS))

Abstract

Software crowdsourcing is becoming an increasingly viable model for creating production software addressing every aspect of the software development lifecycle. However, as software development processes become yet more complex requiring dedicated systems for development, testing, and deployment, software crowdsourcing projects must also acquire considerable infrastructure in order to facilitate development. We propose the use of an infrastructure crowdsourcing model, termed a Social Cloud, to facilitate a user-contributed cloud fabric on which software development services and systems can be hosted. Social Clouds are motivated by the needs of individuals or groups for specific resources or capabilities that can be made available by connected peers. Social Clouds leverage lessons learned through volunteer computing and crowdsourcing projects such as the willingness of individuals to make their resources available and offer their expertise altruistically for “good causes” or in exchange for other resources or payment. In this chapter we present the Social Cloud model and describe how it can be used to crowdsource software infrastructure.

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Notes

  1. 1.

    http://www.topcoder.com/.

  2. 2.

    Tasks where the solution is known ex-ante to test worker accuracy.

  3. 3.

    http://www.facebook.com/progressthruprocessors.

  4. 4.

    https://joindiaspora.com/.

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Author information

Authors and Affiliations

  1. Computation Institute, University of Chicago and Argonne National Laboratory, Lemont, USA

    Kyle Chard

  2. Karlsruhe Service Research Institute, Karlsruhe Institute of Technology, Karlsruhe, Germany

    Simon Caton

Authors
  1. Kyle Chard
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  2. Simon Caton
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Corresponding author

Correspondence to Kyle Chard .

Editor information

Editors and Affiliations

  1. State Key Laboratory of Software Development Environment, School of Computer Science and Engineering, Beihang University, Beijing, China

    Wei Li

  2. Dept. of Computer Science & Engineering, University of South Carolina, Columbia, South Carolina, USA

    Michael N. Huhns

  3. School of Computing, Informatics & Decision Systems Engineering, Arizona State University Dept. Computer Science & Engineering, Tempe, Arizona, USA

    Wei-Tek Tsai

  4. School of Computer Science & Engineering, Beihang University, Beijing, China

    Wenjun Wu

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Chard, K., Caton, S. (2015). Social Clouds: Crowdsourcing Cloud Infrastructure. In: Li, W., Huhns, M., Tsai, WT., Wu, W. (eds) Crowdsourcing. Progress in IS. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-47011-4_11

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