Abstract
Autonomic systems have broad scope in the telecommunication industry, where the prime objective is to provide quality services to customers whilst obeying certain financial constraints. Therefore, an autonomic system is designed and developed in this study to determine a trade-off between cost and quality. The developed simulator is capable of responding to unforeseen changes appearing over time as well as in business policy without human intervention. It learns from data using a machine learning algorithm and performs classification to assign the instances of data to corresponding groups. Various experiments are carried out to observe the performance and behaviour of the simulator.
Original language | English |
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Title of host publication | 2019 6th International Conference on Soft Computing and Machine Intelligence, ISCMI 2019 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 116-120 |
Number of pages | 5 |
ISBN (Electronic) | 9781728145778 |
DOIs | |
Publication status | Published (in print/issue) - 20 Feb 2020 |
Event | 6th International Conference on Soft Computing and Machine Intelligence, ISCMI 2019 - Johannesburg, South Africa Duration: 19 Nov 2019 → 20 Nov 2019 |
Publication series
Name | 2019 6th International Conference on Soft Computing and Machine Intelligence, ISCMI 2019 |
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Conference
Conference | 6th International Conference on Soft Computing and Machine Intelligence, ISCMI 2019 |
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Country/Territory | South Africa |
City | Johannesburg |
Period | 19/11/19 → 20/11/19 |
Bibliographical note
Funding Information:ACKNOWLEDGMENT This work was supported by BTIIC (BT Ireland Innovation Centre), funded by BT and Invest Northern Ireland.
Publisher Copyright:
© 2019 IEEE.
Keywords
- Business policy
- Cost and quality
- Decision tree
- Self-adaptive system
- Stability