Volume 11 • Issue 2 • PP: 10–15 • 2026
Computer Resource Usability Modelling from Virtual-Machine Workload Traces: A Cognitive HCI Perspective
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Computer usability is often discussed through screen layout, navigation, and task flow, although the experience of using a computer also depends on whether processor, memory, storage, and network resources remain available when the user needs them. This paper develops a Computer Resource Usability Index (CRUI) for interpreting virtual-machine resource traces as indicators of user-facing usability risk. The proposed index converts CPU, memory, disk, and network measurements into a bounded resource-friction score and then maps this score into four actionable usability states: comfortable, watch, constrained, and strained. The analysis uses a processed extract following the public GWA-T-12 Bitbrains trace structure, which records VM-level resource metrics for enterprise applications. The results show that resource usability is not explained by CPU usage alone; imbalance across resource channels, I/O pressure, and variability also contribute to predicted friction. The findings provide a practical bridge between infrastructure monitoring and cognitive HCI by translating low-level resource traces into interface-relevant decisions such as when to defer background tasks, warn the user, or allocate additional headroom.
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