Research Article
A Hybrid Approach to Monitor Context Parameters for Optimising Caching for Context-Aware IoT Applications
@INPROCEEDINGS{10.1007/978-3-031-63989-0_8, author={Ashish Manchanda and Prem Prakash Jayaraman and Abhik Banerjee and Arkady Zaslavsky and Shakthi Weerasinghe and Guang-Li Huang}, title={A Hybrid Approach to Monitor Context Parameters for Optimising Caching for Context-Aware IoT Applications}, proceedings={Mobile and Ubiquitous Systems: Computing, Networking and Services. 20th EAI International Conference, MobiQuitous 2023, Melbourne, VIC, Australia, November 14--17, 2023, Proceedings, Part I}, proceedings_a={MOBIQUITOUS}, year={2024}, month={7}, keywords={Context parameter monitoring Cached context freshness Real-Time IoT applications System efficiency}, doi={10.1007/978-3-031-63989-0_8} }- Ashish Manchanda
Prem Prakash Jayaraman
Abhik Banerjee
Arkady Zaslavsky
Shakthi Weerasinghe
Guang-Li Huang
Year: 2024
A Hybrid Approach to Monitor Context Parameters for Optimising Caching for Context-Aware IoT Applications
MOBIQUITOUS
Springer
DOI: 10.1007/978-3-031-63989-0_8
Abstract
Internet of Things (IoT) has seen a prolific rise in recent times and provides the ability to solve several key challenges faced by our societies and environment. Data produced by IoT provides a significant opportunity to infer context that is key for IoT applications to make decisions/actuations. Context Management Platform (CMP) is a middleware to facilitate the exchange and management of such context information among IoT applications. In this paper, we propose a novel approach to monitoring context freshness as a key metric, to improving the CMP’s caching performance to support the real-time context needs of IoT applications. Our proposed hybrid algorithm uses Analytic Hierarchy Process (AHP) and Sliding Window technique to ensure the most relevant (as needed by the IoT applications) context information is cached. By continuously monitoring and prioritizing context attributes, the strategy adapts to IoT environment changes, keeping cached context fresh and reliable. Through experimental evaluation and using mock data obtained from a real-world mobile IoT scenario in Sect.1, we demonstrate that the proposed algorithm can substantially enhance context cache performance, by monitoring the context attributes in real time.
