attribute-lifetime-measurement
https://github.com/shakthiyasas/attribute-lifetime-measurement
Science Score: 67.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 3 DOI reference(s) in README -
✓Academic publication links
Links to: arxiv.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (8.9%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: ShakthiYasas
- Language: Python
- Default Branch: master
- Size: 947 KB
Statistics
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
ACOCA-A PROTOTYPE
This code repository contains the ACOCA-A Prototype. Please use the "microservices" branch as not all artifacts mentioned below may NOT be available in the "master".
Publications arising from the repository:
1) S. Weerasinghe, A. Zaslavsky, S. W. Loke, A. Medvedev, and A. Abken, ‘Estimating the Lifetime of Transient Context for Adaptive Caching in IoT Applications’, in ACM Symposium on Applied Computing, Brno, Czech Republic: ACM, Apr. 2022, p. 10. doi: 10.1145/3477314.3507075. 2) S. Weerasinghe, A. Zaslavsky, S. W. Loke, A. Medvedev, and A. Abken, ‘Estimating the dynamic lifetime of transient context in near real-time for cost-efficient adaptive caching’, SIGAPP Appl. Comput. Rev., vol. 22, no. 2, pp. 44–58, Jun. 2022, doi: 10.1145/3558053.3558057. 3) S. Weerasinghe, A. Zaslavsky, S. W. Loke, A. Abken, A. Hassani, and A. Medvedev, ‘Adaptive Context Caching for Efficient Distributed Context Management Systems’, in ACM Symposium on Applied Computing, Tallinn, Estonia: ACM, Mar. 2023, p. 10. doi: 10.1145/3555776.3577602. 4) An Agent Based Learning Approach to Adaptive Context Caching in Distributed Context Management Systems (Journal Paper - Being processed at ACM Transactions in IoT Journal) - also available in S. Weerasinghe, A. Zaslavsky, S. W. Loke, A. Abken, and A. Hassani, ‘Reinforcement Learning Based Approaches to Adaptive Context Caching in Distributed Context Management Systems’. arXiv, Dec. 22, 2022. Accessed: Dec. 23, 2022. [Online]. Available: http://arxiv.org/abs/2212.11709.
Datasets
Dataset used to simulate the behaviours of the entities involved in the use case can be found at /datasets. Datasets related to carparks, vehicles, weather, and places can be found here. These datasets can be simulated using the entitySimulator found in the code OR using the IoT dats simulator (https://github.com/IBA-Group-IT/IoT-data-simulator/tree/master).
Context consumer SLAs are available in contextConsumer.json. All the registered Context Providers are available in contextService.json.
Experimental Setup
The JMeter file (.jmx) used to simulate the context queries can be found at /experiment/test-plan.jmx. Use the requests.csv in /datasets to set the context query load.
NOTICES
The service containers assuming an alreday running container instance of 'mongodb'. Please use the dockerized-solution branch for the solution using Docker containers related to the publication 'Estimating the lifetime of transient context items'.
Owner
- Name: Shakthi Weerasinghe
- Login: ShakthiYasas
- Kind: user
- Location: Katubedda
- Company: University of Moratuwa
- Website: https://techscopehq.blogspot.com
- Repositories: 2
- Profile: https://github.com/ShakthiYasas
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: Weerasinghe
given-names: Shakthi
title: "Context Attribute Lifetime Estimation"
version: 1.1.0
date-released: 2021-09-26