SECA: Snapshot-based Event Detection for Checking Asynchronous Context Consistency in Ubiquitous Computing
Daqiang Zhang, Qin Zou, Zhiren Sun

TL;DR
SECA is a novel snapshot-based event detection method that improves asynchronous context consistency checking in ubiquitous computing by reducing complexity and increasing accuracy over existing methods like CEDA.
Contribution
SECA introduces a snapshot-based timestamp approach that simplifies logical clocks, enhancing detection accuracy and scalability in context consistency checking.
Findings
SECA outperforms CEDA in detection accuracy.
SECA reduces time and space complexity.
SECA demonstrates better scalability in empirical tests.
Abstract
Context-consistency checking is challenging in the dynamic and uncertain ubiquitous computing environments. This is because contexts are often noisy owing to unreliable sensing data streams, inaccurate data measurement, fragile connectivity and resource constraints. One of the state-of-the-art efforts is CEDA, which concurrently detects context consistency by exploring the \emph{happened-before} relation among events. However, CEDA is seriously limited by several side effects --- centralized detection manner that easily gets down the checker process, heavy computing complexity and false negative. In this paper, we propose SECA: Snapshot-based Event Detection for Checking Asynchronous Context Consistency in ubiquitous computing. SECA introduces snapshot-based timestamp to check event relations, which can detect scenarios where CEDA fails. Moreover, it simplifies the logical clock…
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Taxonomy
TopicsContext-Aware Activity Recognition Systems · IoT and Edge/Fog Computing · Personal Information Management and User Behavior
