Publications

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.

Ashish Manchanda, Prem Prakash Jayaraman, Abhik Banerjee, Arkady Zaslavsky, Shakthi Weerasinghe, and Guang-Li Huang, ‘A Hybrid Approach to Monitor Context Parameters for Optimising Caching for Context-Aware IoT Applications’, in EAI MobiQuitous, Melbourne, Australia: Springer, November 2023, p. 16. doi: 10.1007/978-3-031-63989-0_8.

C. Bombuwala, K. Kahatapitiya, R. Kumaranayaka, S. Weerasinghe, U. Ganegoda, and I. Manawadu, ‘Event Driven Share Price Forecasting based on Change based Impact Analysis’, in 2022 7th International Conference on Information Technology Research (ICITR), Moratuwa, Sri Lanka: IEEE, Dec. 2022, pp. 1–6. doi: 10.1109/ICITR57877.2022.9992415.

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.

S. Weerasinghe and S. Ahangama, ‘Predictive Maintenance and Performance Optimisation in Aircrafts using Data Analytics’, in 2018 3rd International Conference on Information Technology Research (ICITR), Moratuwa, Sri Lanka: IEEE, Dec. 2018, pp. 1–8. doi: 10.1109/ICITR.2018.8736157

S. Weerasinghe, A. Zaslavsky, S. W. Loke, A. Abken, A. Hassani, and G.-L. Huang, ‘Reinforcement Learning Based Approaches to Adaptive Context Caching in Distributed Context Management Systems’, ACM Trans. IoT, p. 30, Feb. 2024, doi: 10.1145/3648571.

S. Weerasinghe, A. Zaslavsky, S. W. Loke, A. Hassani, A. Medvedev, and A. Abken, ‘Adaptive Context Caching for IoT-Based Applications: A Reinforcement Learning Approach’, Sensors, vol. 23, no. 10, p. 4767, May 2023, doi: 10.3390/s23104767.

A. Medvedev, A. Hassani, G. Belov, S. Weerasinghe, G. Huang, A. Zaslavsky, S. W. Loke, and P. Jayaraman, ‘Refresh Rate Based Caching and Prefetching Strategies for Intenet of Things Middleware’, Sensors, vol. 23, no. 21, p. 8779, October 2023, doi: 10.3390/s23218779.

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.

S. Weerasinghe, A. Udadeniya, N. Waduge, R. de Zoysa, and U. Ganegoda, ‘Novel Method to Analyze and Forecast Social Impact on Macro- and Micro-Economies Using Social Media Data’, in Proceedings of International Conference on Sustainable Expert Systems, S. Shakya, V. E. Balas, W. Haoxiang, and Z. Baig, Eds., in Lecture Notes in Networks and Systems, vol. 176. Singapore: Springer Singapore, 2021, pp. 261–277. doi: 10.1007/978-981-33-4355-9_21.

S. Weerasinghe, A. Zaslavsky, S. W. Loke, A. Medvedev, A. Abken, and A. Hassani, ‘Context Caching for IoT-Based Applications: Opportunities and Challenges’, IEEE Internet Things M., vol. 6, no. 4, pp. 96–102, Dec. 2023, doi: 10.1109/IOTM.001.2200247.

S. Weerasinghe, B.D. Mach, A. Zaslavsky, and V. Moghaddam, ‘Unlocking Contextual Intelligence - Anywhere, Anytime, and Everywhere’, in 2025 26th IEEE International Conference on Mobile Data Management (MDM), Irvine, California, USA: IEEE, Jun. 2025, , pp. 1-7, doi: 10.1109/MDM65600.2025.00050.

S. Weerasinghe, K. S. Jagarlamudi, A. Zaslavsky, S. W. Loke, K. Lee and G. -L. Huang, "Improving the Usefulness of Context Information for IoT Applications: A Middleware-based Approach," 2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), Biarritz, France, 2024, pp. 1-7, doi: 10.1109/PerComWorkshops59983.2024.10503179.

S. Weerasinghe, A. Zaslavsky, S. W. Loke, and G. Li-Huang, ‘Proactive Context Caching Based on Situation Prediction for Real-Time Mobile IoT Applications’, in 2024 25th IEEE International Conference on Mobile Data Management (MDM), Brussels,  Belgium: IEEE, Jun. 2024, pp. 313-3158, doi: 10.1109/MDM61037.2024.00064.

S. Weerasinghe, A. Zaslavsky, S. W. Loke, V. Moghaddam, and C. Becker, ‘Towards World Wide Context Management: Architecting Distributed Contextual Intelligence Systems for Real-Time IoT Applications’, in 2023 24th IEEE International Conference on Mobile Data Management (MDM), Singapore, Singapore: IEEE, Jul. 2023, pp. 340–345. doi: 10.1109/MDM58254.2023.00062.

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

S. Weerasinghe, A. Zaslavsky, S. W. Loke, A. Hassani, A. Abken, and A. Medvedev, ‘From Traditional Adaptive Data Caching to Adaptive Context Caching: A Survey’, arXiv:2211.11259 [cs.HC], p. 35, Nov. 2022.

S. Weerasinghe, U. Ganegoda, C. Bombuwela, K. Kahatapitiya, and R. Kumaranayaka, ‘Architecting an event-driven forecasting model for stock market variations’, p. 9.