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https://doi.org/10.1109/icdcs....
Article . 2018 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2018
License: arXiv Non-Exclusive Distribution
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Massivizing Computer Systems: A Vision to Understand, Design, and Engineer Computer Ecosystems Through and Beyond Modern Distributed Systems

A vision to understand, design, and engineer computer ecosystems through and beyond modern distributed systems
Authors: Iosup, Alexandru; Uta, Alexandru; Versluis, Laurens; Andreadis, Georgios; Van Eyk, Erwin; Hegeman, Tim; Talluri, Sacheendra; +2 Authors

Massivizing Computer Systems: A Vision to Understand, Design, and Engineer Computer Ecosystems Through and Beyond Modern Distributed Systems

Abstract

Our society is digital: industry, science, governance, and individuals depend, often transparently, on the inter-operation of large numbers of distributed computer systems. Although the society takes them almost for granted, these computer ecosystems are not available for all, may not be affordable for long, and raise numerous other research challenges. Inspired by these challenges and by our experience with distributed computer systems, we envision Massivizing Computer Systems, a domain of computer science focusing on understanding, controlling, and evolving successfully such ecosystems. Beyond establishing and growing a body of knowledge about computer ecosystems and their constituent systems, the community in this domain should also aim to educate many about design and engineering for this domain, and all people about its principles. This is a call to the entire community: there is much to discover and achieve.

Keywords

FOS: Computer and information sciences, Design, Vision, Science, Cloud Computing, Datacenters, Software Engineering (cs.SE), Computer Science - Software Engineering, Engineering, Computer Science - Distributed, Parallel, and Cluster Computing, Distributed Systems, Edge Computing, Massivizing Computer Systems, Distributed, Parallel, and Cluster Computing (cs.DC)

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    15
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
15
Top 10%
Top 10%
Top 10%
Green