SEDCNISYNov 1, 2016

Self-Awareness of Cloud Applications

arXiv:1611.00323v19 citations
Originality Synthesis-oriented
AI Analysis

This work provides a roadmap for addressing open challenges in self-aware cloud and datacenter applications, which is incremental as it synthesizes existing approaches rather than introducing new methods.

The authors proposed a conceptual framework to analyze state-of-the-art self-awareness approaches used in cloud applications, mapping applications to this framework and comparing their practical characteristics, benefits, and drawbacks.

Cloud applications today deliver an increasingly larger portion of the Information and Communication Technology (ICT) services. To address the scale, growth, and reliability of cloud applications, self-aware management and scheduling are becoming commonplace. How are they used in practice? In this chapter, we propose a conceptual framework for analyzing state-of-the-art self-awareness approaches used in the context of cloud applications. We map important applications corresponding to popular and emerging application domains to this conceptual framework, and compare the practical characteristics, benefits, and drawbacks of self-awareness approaches. Last, we propose a roadmap for addressing open challenges in self-aware cloud and datacenter applications.

Foundations

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