Context-aware Programming for Hybrid and Diversity-aware Collective Adaptive Systems

Abstract: Collective adaptive systems (CASs) have been researched intensively since many years. However, the recent emerging developments and advanced models in service-oriented computing, cloud computing and human computation have fostered several new forms of CASs. Among them, Hybrid and Diversity-aware CASs (HDA-CASs) characterize new types of CASs in which a collective is composed of hybrid machines and humans that collaborate together with different complementary roles. This emerging HDA-CAS poses several research challenges in terms of programming, management and provisioning. In this paper, we investigate the main issues in programming HDA-CASs. First, we analyze context characterizing HDA-CASs. Second, we propose to use the concept of hybrid compute units to implement HDA-CASs that can be elastic. We call this type of HDA-CASs h2h2 CAS (Hybrid Compute Unit-based HDA-CAS). We then discuss a meta-view of h2h2 CAS that describes a h2h2 CAS program. We analyze and present program features for h2h2 CAS in four main different contexts.

Citation: Hong-Linh Truong, Schahram Dustdar, “Context-aware Programming for Hybrid and Diversity-aware Collective Adaptive Systems”, Springer, International Workshop on Business Processes in Collective Adaptive Systems (BPCAS 2014), 12th Intl. Conf. on Business Process Management (BPM14), Eindhoven, The Netherlands, September 7-12, 2014


About P. Andreadis

Pre-Doctoral Research Assistant in AI and Social Computation @ University of Edinburgh.

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