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title={Collective Abstractions booktitle = {2018 IEEE 3rd International Workshops on Foundations and Platforms for Large-Scale Self-Adaptive IoT},Applications of Self* Systems (FAS* W)},
author={Casadei, Roberto and Viroli, Mirko}, year = 2018,
booktitle={2018 IEEE 3rd International Workshops on Foundations and Applications of Self* Systems (FAS* W)}, status = {Published},
pages={106--111}, venue_list = {--},
year={2018}, author = {Casadei, Roberto and Viroli, Mirko},
organization={IEEE} title = {Collective Abstractions and Platforms for Large-Scale Self-Adaptive IoT},
} abstract = {On the way to the materialisation of the pervasive
computing vision, the technological progress swelling from mobile
computing and the Internet of Things (IoT) domain is already
rich of missed opportunities. Firstly, coordinating large numbers
of heterogeneous situated entities to achieve system-level goals in
a resilient and self-adaptive way is complex and requires novel
approaches to be seamlessly injected into mainstream distributed
computing models. Secondly, achieving effective exploitation of
computer resources is difficult, due to operational constraints
resulting from current paradigms and uncomprehensive software
infrastructures which hinder flexibility, adaptation, and smooth
coordination of computational tasks execution. Indeed, building
dynamic, context-oriented applications in small- or large-scale
IoT with traditional abstractions is hard: even harder is to
achieve opportunistic, QoS- and QoE-driven application task
management across available hardware and networking infrastructure. In this insight paper, we analyse by the collective adaptation perspective the key directions of the impelling paradigm
shift urged by forthcoming large-scale IoT scenarios. Specifically,
we consider how collective abstractions and platforms can synergistically assist in such a transformation, by better capturing and
enacting a notion of “collective service” as well as the dynamic,
opportunistic, and context-driven traits of space-time-situated
pages = {106--111},
doi = {10.1109/FAS-W.2018.00033}}