Research challenges of autonomic computing
By Jeffrey O. Kephart. Proceedings. 27th International Conference on Software Engineering, 2005. ICSE 2005., 2005
346 citations recorded by the source corpus.
Autonomic computing is a grand-challenge vision in which computing systems manage themselves in accordance with high-level objectives specified by humans. The IT industry recognizes that meeting this challenge is imperative; otherwise, IT systems will soon become virtually impossible to administer. But meeting this challenge is also extremely difficult, and requires a worldwide collaboration among the best minds of academia and industry. In the hope of motivating researchers in relevant areas to apply their expertise to this vitally important problem, the author outlines some of the main scientific and engineering challenges that collectively make up the grand challenge of autonomic computing, and provide pointers to initial efforts to address these challenges.
Subfields: Computer Networks and Communications
View Paper: https://www.semanticscholar.org/paper/c25381cb6eb72d16748ab98a126f97826df686a6
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Citations in the corpus
- Smart Contract Development: Challenges and Opportunities (2021, background): “Kephart [74] outlined some scientific and engineering challenges of autonomic computing.”
- Live Video Analytics at Scale with Approximation and Delay-Tolerance (2017, background): “Utility functions are used extensively throughout economics [65, 73], compute science [48, 55, 57, 63], and other disciplines to map how users benefit from performance [50, 58, 80].”
- Resilience and survivability in communication networks: Strategies, principles, and survey of disciplines (2010, background): “[148,149,101] is necessary for network resilience that is highly reactive with minimal human intervention.”
- Self-adaptive software: Landscape and research challenges (2009, background): “1999] and [Kephart 2005].”