Profiling And Optimization Of Software Base Network Analysis Applications
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This document discusses profiling and optimizing software-based network analysis applications. It identifies components involved in network analysis like packet filtering, buffering, and copying. It analyzes the costs of unoptimized and optimized packet processing, showing how optimizations like hardware timestamps and shared buffers can reduce overhead. It also evaluates the performance of software-only packet capture at different network speeds.
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https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
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