Policy based generic autonomic adapter for a context-aware social-collaborative system

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Autonomic computing was intended to tackle the growing complexity of Information Technology infrastructure by making it self-managing and self-adaptive. The core idea is to endow the system with enough intelligence to monitor continuously all aspects of the changing environments and resources, and to control management decisions according to high-level policies. For several years, great efforts have been devoted to the study of system performance, security, and fault management issues, but without much attention paid to self-adaptive social-collaborative system development. This may be because it is difficult to create such autonomic systems, which must sense and adapt to ongoing social context changes and support cyber-physical collaborations with minimal human involvement. These collaborations will have interactions between human and non-human entities that need to be self-managing with adaptive goals. This paper tackles the problem by introducing a new Generic Autonomic Social-Collaborative Framework (GASCF). It focuses on a high-level social-context based self-adaptive system, and its use of intelligent agents called autonomic adapters(AAs) that are driven by predefined policies. The paper describes the architecture of autonomic adapters and the general representation of policies. It explores the effectiveness of the approach by applying it to a large-scale collaborative healthcare service called GRaCE (https://www.egrist.org/) that supports mental-health within the United Kingdom National Health Service and other organisations.
Original languageEnglish
Title of host publication2018 International Conference on Intelligent Systems and Computer Vision (ISCV)
PublisherIEEE
Pages1-9
ISBN (Electronic) 978-1-5386-4396-9
ISBN (Print)978-1-5386-4397-6
DOIs
Publication statusPublished - 7 May 2018
Event2018 International Conference on Intelligent Systems and Computer Vision (ISCV) - Fez, Morocco
Duration: 2 Apr 20184 Apr 2018

Conference

Conference2018 International Conference on Intelligent Systems and Computer Vision (ISCV)
CountryMorocco
CityFez
Period2/04/184/04/18

Fingerprint

Health
Intelligent agents
Adaptive systems
Information technology

Cite this

Hussain, N., Wang, H., & Buckingham, C. D. (2018). Policy based generic autonomic adapter for a context-aware social-collaborative system. In 2018 International Conference on Intelligent Systems and Computer Vision (ISCV) (pp. 1-9). IEEE. https://doi.org/10.1109/ISACV.2018.8354044
Hussain, Nazmul ; Wang, Hai ; Buckingham, Christopher D. / Policy based generic autonomic adapter for a context-aware social-collaborative system. 2018 International Conference on Intelligent Systems and Computer Vision (ISCV). IEEE, 2018. pp. 1-9
@inproceedings{76759455e0044e63aca1dab1822de4e4,
title = "Policy based generic autonomic adapter for a context-aware social-collaborative system",
abstract = "Autonomic computing was intended to tackle the growing complexity of Information Technology infrastructure by making it self-managing and self-adaptive. The core idea is to endow the system with enough intelligence to monitor continuously all aspects of the changing environments and resources, and to control management decisions according to high-level policies. For several years, great efforts have been devoted to the study of system performance, security, and fault management issues, but without much attention paid to self-adaptive social-collaborative system development. This may be because it is difficult to create such autonomic systems, which must sense and adapt to ongoing social context changes and support cyber-physical collaborations with minimal human involvement. These collaborations will have interactions between human and non-human entities that need to be self-managing with adaptive goals. This paper tackles the problem by introducing a new Generic Autonomic Social-Collaborative Framework (GASCF). It focuses on a high-level social-context based self-adaptive system, and its use of intelligent agents called autonomic adapters(AAs) that are driven by predefined policies. The paper describes the architecture of autonomic adapters and the general representation of policies. It explores the effectiveness of the approach by applying it to a large-scale collaborative healthcare service called GRaCE (https://www.egrist.org/) that supports mental-health within the United Kingdom National Health Service and other organisations.",
author = "Nazmul Hussain and Hai Wang and Buckingham, {Christopher D}",
year = "2018",
month = "5",
day = "7",
doi = "10.1109/ISACV.2018.8354044",
language = "English",
isbn = "978-1-5386-4397-6",
pages = "1--9",
booktitle = "2018 International Conference on Intelligent Systems and Computer Vision (ISCV)",
publisher = "IEEE",
address = "United States",

}

Hussain, N, Wang, H & Buckingham, CD 2018, Policy based generic autonomic adapter for a context-aware social-collaborative system. in 2018 International Conference on Intelligent Systems and Computer Vision (ISCV). IEEE, pp. 1-9, 2018 International Conference on Intelligent Systems and Computer Vision (ISCV), Fez, Morocco, 2/04/18. https://doi.org/10.1109/ISACV.2018.8354044

Policy based generic autonomic adapter for a context-aware social-collaborative system. / Hussain, Nazmul; Wang, Hai; Buckingham, Christopher D.

2018 International Conference on Intelligent Systems and Computer Vision (ISCV). IEEE, 2018. p. 1-9.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Policy based generic autonomic adapter for a context-aware social-collaborative system

AU - Hussain, Nazmul

AU - Wang, Hai

AU - Buckingham, Christopher D

PY - 2018/5/7

Y1 - 2018/5/7

N2 - Autonomic computing was intended to tackle the growing complexity of Information Technology infrastructure by making it self-managing and self-adaptive. The core idea is to endow the system with enough intelligence to monitor continuously all aspects of the changing environments and resources, and to control management decisions according to high-level policies. For several years, great efforts have been devoted to the study of system performance, security, and fault management issues, but without much attention paid to self-adaptive social-collaborative system development. This may be because it is difficult to create such autonomic systems, which must sense and adapt to ongoing social context changes and support cyber-physical collaborations with minimal human involvement. These collaborations will have interactions between human and non-human entities that need to be self-managing with adaptive goals. This paper tackles the problem by introducing a new Generic Autonomic Social-Collaborative Framework (GASCF). It focuses on a high-level social-context based self-adaptive system, and its use of intelligent agents called autonomic adapters(AAs) that are driven by predefined policies. The paper describes the architecture of autonomic adapters and the general representation of policies. It explores the effectiveness of the approach by applying it to a large-scale collaborative healthcare service called GRaCE (https://www.egrist.org/) that supports mental-health within the United Kingdom National Health Service and other organisations.

AB - Autonomic computing was intended to tackle the growing complexity of Information Technology infrastructure by making it self-managing and self-adaptive. The core idea is to endow the system with enough intelligence to monitor continuously all aspects of the changing environments and resources, and to control management decisions according to high-level policies. For several years, great efforts have been devoted to the study of system performance, security, and fault management issues, but without much attention paid to self-adaptive social-collaborative system development. This may be because it is difficult to create such autonomic systems, which must sense and adapt to ongoing social context changes and support cyber-physical collaborations with minimal human involvement. These collaborations will have interactions between human and non-human entities that need to be self-managing with adaptive goals. This paper tackles the problem by introducing a new Generic Autonomic Social-Collaborative Framework (GASCF). It focuses on a high-level social-context based self-adaptive system, and its use of intelligent agents called autonomic adapters(AAs) that are driven by predefined policies. The paper describes the architecture of autonomic adapters and the general representation of policies. It explores the effectiveness of the approach by applying it to a large-scale collaborative healthcare service called GRaCE (https://www.egrist.org/) that supports mental-health within the United Kingdom National Health Service and other organisations.

UR - https://ieeexplore.ieee.org/document/8354044/?tp=&arnumber=8354044&contentType=Conferences&dld=YXN0b24uYWMudWs%3D&source=SEARCHALERT

U2 - 10.1109/ISACV.2018.8354044

DO - 10.1109/ISACV.2018.8354044

M3 - Conference contribution

SN - 978-1-5386-4397-6

SP - 1

EP - 9

BT - 2018 International Conference on Intelligent Systems and Computer Vision (ISCV)

PB - IEEE

ER -

Hussain N, Wang H, Buckingham CD. Policy based generic autonomic adapter for a context-aware social-collaborative system. In 2018 International Conference on Intelligent Systems and Computer Vision (ISCV). IEEE. 2018. p. 1-9 https://doi.org/10.1109/ISACV.2018.8354044