Memory-constrained context-aware reasoning

Uddin, Ijaz; Rakib, Abdur; Ali, Mumtaz; Vinh, Phan Cong

Abstract

The context-aware computing paradigm introduces environments, known as smart spaces, which can unobtrusively and proactively assist their users. These systems are currently mostly implemented on mobile platforms considering various techniques, including ontology-driven multi-agent rule-based reasoning. Rule-based reasoning is a relatively simple model that can be adapted to different real-world problems. It can be developed considering a set of assertions, which collectively constitute the working memory, and a set of rules that specify how to act on the assertion set. However, the size of the working memory is crucial when developing context-aware systems in resource constrained devices such as smartphones and wearables. In this paper, we discuss rule-based context-aware systems and techniques for determining the required working memory size for a fixed set of rules.

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 10th EAI International Conference on Context-Aware Systems and Applications
• Start Date: Oct 28, 2021
• End Date: Oct 29, 2021
• Acceptance Date: Aug 31, 2021
• Online Publication Date: Jan 1, 2022
• Publication Date: Jan 1, 2022
• Deposit Date: Dec 14, 2021
• Publicly Available Date: Jan 2, 2023
• Publisher: Springer
• Volume: 409
• Pages: 133-146
• Series Title: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
• Book Title: Context-Aware Systems and Applications
• ISBN: 9783030931780
• DOI: https://doi.org/10.1007/978-3-030-93179-7_11
• Keywords: Context-Aware Systems;Rule-based Reasoning;Working Memory
• Public URL: https://uwe-repository.worktribe.com/output/7952707