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 h 2 CAS (Hybrid Compute Unit-based HDA-CAS). We then discuss a meta-view of h 2 CAS that describes a h 2 CAS program. We analyze and present program features for h 2 CAS in four main different contexts.

Trust-Aware Elastic Social Compute Units

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Application of provenance in social computing: A case study

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