Workshop Paper

CHARIOT — Towards a Continuous High-Level Adaptive Runtime Integration Testbed

Posted on June 16, 2019 by Publication Workshop Paper

Chloe M. Barnes, Kirstie Bellman, Jean Botev, Ada Diaconescu, Lukas Esterle, Christian Gruhl, Chris Landauer, Peter R. Lewis, Phyllis R. Nelson, Anthony Stein, Christopher Stewart, Sven Tomforde: CHARIOT -- Towards a Continuous High-Level Adaptive Runtime Integration Testbed. In: Proceedings of the IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W), pp. 52–55, IEEE, 2019.

Abstract

Integrated networked systems sense a common environment, learn to navigate the environment and share their experiences. Sharing experiences simplifies learning, reducing costly trial and error in complex environments. However, integration produces dependencies that make constituent systems less robust to failures, unexpected outputs and performance anomalies. Even with APIs and reflective, self-aware techniques, system integration still requires expert programming and tuning. Self-integrating systems proposed in recent research automate integration, but can be challenging to validate at scale. We therefore propose CHARIOT, a common test environment to allow for different approaches and systems to be deployed, assessed and compared on a shared platform for the development of self-integrating systems. In this paper, we discuss the underlying requirements and challenges, potential metrics, and a system metamodel to accommodate these.


BibTeX (Download)

@inproceedings{Barnes2019CHARIOTTestbed,
title = {CHARIOT -- Towards a Continuous High-Level Adaptive Runtime Integration Testbed},
author = {Chloe M. Barnes and Kirstie Bellman and Jean Botev and Ada Diaconescu and Lukas Esterle and Christian Gruhl and Chris Landauer and Peter R. Lewis and Phyllis R. Nelson and Anthony Stein and Christopher Stewart and Sven Tomforde},
url = {https://ieeexplore.ieee.org/document/8791947},
doi = {10.1109/FAS-W.2019.00026},
year  = {2019},
date = {2019-06-19},
urldate = {2019-01-01},
booktitle = {Proceedings of the IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W)},
pages = {52--55},
publisher = {IEEE},
abstract = {Integrated networked systems sense a common environment, learn to navigate the environment and share their experiences. Sharing experiences simplifies learning, reducing costly trial and error in complex environments. However, integration produces dependencies that make constituent systems less robust to failures, unexpected outputs and performance anomalies. Even with APIs and reflective, self-aware techniques, system integration still requires expert programming and tuning. Self-integrating systems proposed in recent research automate integration, but can be challenging to validate at scale. We therefore propose CHARIOT, a common test environment to allow for different approaches and systems to be deployed, assessed and compared on a shared platform for the development of self-integrating systems. In this paper, we discuss the underlying requirements and challenges, potential metrics, and a system metamodel to accommodate these.},
keywords = {Adaptive Systems, Runtime Systems Integration},
pubstate = {published},
tppubtype = {inproceedings}
}

“When You Believe in Things That You Don’t Understand”: The Effect of Cross-Generational Habits on Self-Improving System Integration

Posted on June 16, 2019 by Publication Workshop Paper

Chloe M. Barnes, Lukas Esterle, John N. A. Brown: ``When You Believe in Things That You Don't Understand. In: Proceedings of the IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W), pp. 28–31, IEEE, 2019.

Abstract

Humans experiencing unexpected feedback to certain actions which they are not able to explain, might develop superstitious behaviour. In this paper, we discuss that similar behaviour might also occur in engineered systems. We provide a thought-experiment regarding such behaviour in computational systems. In this paper, we propose a first step towards improved runtime systems integration based on a the ability to become aware of previously-unknown others and their actions, as described in networked self-awareness.


BibTeX (Download)

@inproceedings{Barnes2019SISSY,
title = {``When You Believe in Things That You Don't Understand},
author = {Chloe M. Barnes and Lukas Esterle and John N. A. Brown},
url = {https://ieeexplore.ieee.org/abstract/document/8791979},
doi = {10.1109/FAS-W.2019.00020},
year  = {2019},
date = {2019-06-16},
urldate = {2019-01-01},
booktitle = {Proceedings of the IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W)},
pages = {28--31},
publisher = {IEEE},
abstract = {Humans experiencing unexpected feedback to certain actions which they are not able to explain, might develop superstitious behaviour. In this paper, we discuss that similar behaviour might also occur in engineered systems. We provide a thought-experiment regarding such behaviour in computational systems. In this paper, we propose a first step towards improved runtime systems integration based on a the ability to become aware of previously-unknown others and their actions, as described in networked self-awareness.},
keywords = {Computational Superstition, Networked Self-Awareness, Runtime Systems Integration, Self-Awareness},
pubstate = {published},
tppubtype = {inproceedings}
}