Context Caching for IoT-Based Applications: Opportunities and Challenges
Author:
Affiliation:
1. Deakin University, School of Information Technology,Australia
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/8548628/10364353/10364652.pdf?arnumber=10364652
Reference15 articles.
1. Towards a Better Understanding of Context and Context-Awareness
2. Towards a Practical Crowdsensing System for Road Surface Conditions Monitoring
3. Context Definition and Query Language: Conceptual Specification, Implementation, and Evaluation
4. Applying machine learning techniques for caching in next-generation edge networks: A comprehensive survey
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1. A Latency Aware and Dynamic Caching Model for Heterogeneous Datalake Environments;2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC);2024-07-02
2. Proactive Context Caching Based on Situation Prediction for Real-Time Mobile IoT Applications;2024 25th IEEE International Conference on Mobile Data Management (MDM);2024-06-24
3. Reinforcement Learning Based Approaches to Adaptive Context Caching in Distributed Context Management Systems;ACM Transactions on Internet of Things;2024-04-23
4. 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);2024-03-11
5. Towards World Wide Context Management: Architecting Distributed Contextual Intelligence Systems for Real-Time IoT Applications;2023 24th IEEE International Conference on Mobile Data Management (MDM);2023-07
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