Abstract: Modern development of computing systems caters the collaboration of human-based resources together with machine-based resources as active compute units. Those units can be dynamically provisioned on-demand for solving complex tasks, such as observed in collaborative applications, crowd sourced applications, and human task workflows. Such collaborations involve very diverse compute units, which have different capabilities and reliability. While the reliability analysis for machine-based compute units has been widely developed, the reliability analysis for the hybrid human-machine collaborations has not been extensively studied. In this paper we present models and a framework for analyzing the reliability of hybrid compute units (HCU), which represent on-demand collectives of humans collaboration supported by machines (hardware and software units) for performing tasks. We present the implementation of our models and study the reliability of HCUs in a simulated system for infrastructure maintenance scenarios. Our evaluation shows that the proposed framework is effective for measuring the reliability of the collaboration collectives, and beneficial to obtain insights for improvements.

Citation: Candra, Muhammad ZC, Hong-Linh Truong, and Schahram Dustdar. “Analyzing Reliability in Hybrid Compute Units.” In: Collaboration and Internet Computing (CIC), IEEE Conference on, 2015.

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Abstract: In this paper, we introduce a privacy-enhanced Peer Manager, which is a fundamental building block for the implementation of a privacy-preserving collective adaptive systems computing platform. The Peer Manager is a user-centered identity management platform that keeps information owned by a user private and is built upon an attribute based privacy policy. Furthermore, this paper explores the ethical, privacy and social values aspects of collective adaptive systems and their extensive capacity to transform lives. We discuss the privacy, social and ethical issues around profiles and present their legal privacy requirements from the European legislation perspective. © IFIP International Federation for Information Processing 2015.

Citation: Mark Hartswood, Marina Jirotka, Ronald Chenu-Abente, Alethia Hume, Fausto Giunchiglia, Leonardo A. Martucci, Simone Fischer-Hübner. “Privacy for Peer Profiling in Collective Adaptive Systems.” Privacy and Identity Management for the Future Internet in the Age of Globalisation. Springer International Publishing, 2014. 237-252.

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