Memory-Constrained Context-Aware Reasoning

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

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Citation (Scopus)

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.
Original languageEnglish
Title of host publicationContext-Aware Systems and Applications. ICCASA 2021
EditorsPhan Cong Vinh, Abdur Rakib
Place of PublicationSpringer, Cham
PublisherSpringer
Pages133-146
Number of pages14
Edition1
ISBN (Electronic)978-3-030-93179-7
ISBN (Print)978-3-030-93178-0
DOIs
Publication statusPublished - 22 Jan 2022
Externally publishedYes
Event10th EAI International Conference on Context-Aware Systems and Applications - Online, Ho Chi Minh City, Viet Nam
Duration: 28 Oct 202129 Oct 2021
https://iccasa.eai-conferences.org/2021/

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
PublisherSpringer
Volume409

Conference

Conference10th EAI International Conference on Context-Aware Systems and Applications
Abbreviated titleICCASA
Country/TerritoryViet Nam
CityHo Chi Minh City
Period28/10/2129/10/21
Internet address

Keywords

  • Context-aware systems
  • Rule-based reasoning
  • Working memory

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