Fog computing extends cloud capabilities to the net-work edge, providing low-latency services for mission-critical applications such as healthcare and industrial automation. However, validating security-aware scheduling policies in this distributed paradigm remains a challenge due to the lack of native support for trust modeling in standard simulation tools like CloudSim and iFogSim. Existing simulators focus primarily on resource provisioning, cost, and energy metrics, often neglecting “Trust” and “Data Confidentiality” as first-class simulation parameters. This study presents the design and implementation of a trust-aware extension for WorkflowSim. We detail the software architecture modifications required to support attribute-based trust verification, secure task fragmentation, and encryption overhead modeling. Unlike standard simulators, our extended framework treats Trust as a dynamic entity in the Virtual Machine (VM) and Task class hierarchy. We validate the framework’s correctness through unit tests and scenario-based trace analysis, demonstrating its ability to accurately model security-performance trade-offs in heterogeneous fog environments. Experimental results indicate that enabling trust-aware scheduling increases makespan by approximately 19% and cost by 16%, while achieving a security score of 0.88 compared to 0.65 for the baseline. The simulation engine overhead remains below 7.1% even for 1000-task workflows. The source code and design patterns presented provide researchers with a robust, extensible tool for evaluating secure scheduling algorithms without the cost of physical testbeds.
Wu et al. (2026) studied this question.