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Final published version
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
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TY - GEN
T1 - REX
T2 - 12th USENIX Symposium on Operating Systems Design and Implementation
AU - Porter, Barry Francis
AU - Grieves, Matthew
AU - Rodrigues Filho, Roberto
AU - Leslie, David Stuart
N1 - Conference code: 12th
PY - 2016/11/2
Y1 - 2016/11/2
N2 - Conventional approaches to self-adaptive software architectures require human experts to specifymodels, policies and processes by which software can adapt to its environment. We present REX, a complete platform and online learning approach for runtime emergent software systems, in which all decisions about the assembly and adaptation of software are machine-derived.REX is built with three major, integrated layers: (i) a novel component-based programming language called Dana, enabling discovered assembly of systems and very low cost adaptation of those systems for dynamic re-assembly; (ii) a perception, assembly and learning framework (PAL)built on Dana, which abstracts emergent software into configurations and perception streams; and (iii) an online learning implementation based on a linear bandit model, which helps solve the search space explosion problem inherent in runtime emergent software. Using an emergentweb server as a case study, we show how software can be autonomously self-assembled from discovered parts, and continually optimized over time (by using alternative parts) as it is subjected to different deployment conditions.Our system begins with no knowledge that it is specifically assembling a web server, nor with knowledge of the deployment conditions that may occur at runtime.
AB - Conventional approaches to self-adaptive software architectures require human experts to specifymodels, policies and processes by which software can adapt to its environment. We present REX, a complete platform and online learning approach for runtime emergent software systems, in which all decisions about the assembly and adaptation of software are machine-derived.REX is built with three major, integrated layers: (i) a novel component-based programming language called Dana, enabling discovered assembly of systems and very low cost adaptation of those systems for dynamic re-assembly; (ii) a perception, assembly and learning framework (PAL)built on Dana, which abstracts emergent software into configurations and perception streams; and (iii) an online learning implementation based on a linear bandit model, which helps solve the search space explosion problem inherent in runtime emergent software. Using an emergentweb server as a case study, we show how software can be autonomously self-assembled from discovered parts, and continually optimized over time (by using alternative parts) as it is subjected to different deployment conditions.Our system begins with no knowledge that it is specifically assembling a web server, nor with knowledge of the deployment conditions that may occur at runtime.
M3 - Conference contribution/Paper
SN - 9781931971331
SP - 333
EP - 348
BT - Proceedings of the 12th USENIX Symposium on Operating Systems Design and Implementation
PB - USENIX Association
Y2 - 2 November 2016 through 4 November 2016
ER -