Simulating IoT Workflows in DISSECT-CF-Fog.

Area of Science:

• Computer Science
• Cloud Computing
• Internet of Things

Background:

• Modeling Internet of Things (IoT) applications in cloud and fog computing presents challenges due to complex trigger-based events and workflow compositions.
• Real-world deployment of IoT workflows faces hurdles like high operational costs and access limitations, necessitating simulation solutions.

Purpose of the Study:

• To introduce a novel simulator extension, DISSECT-CF-Fog, for modeling IoT use cases by leveraging workflow scheduling and execution capabilities.
• To address the omission of the IoT factor in state-of-the-art scientific workflow evaluation simulators.
• To present a scalability study on scientific workflows and their interoperability with IoT workflows within the DISSECT-CF-Fog simulator.

Main Methods:

• Development of a novel extension for the DISSECT-CF-Fog simulator.
• Integration of workflow scheduling and execution capabilities to model IoT use cases.
• Conducting a scalability study focusing on scientific and IoT workflow interoperability.

Main Results:

• The novel simulator extension effectively models real-life IoT use cases, including complex workflow compositions.
• The study highlights the limitations of current simulators in evaluating scientific workflows with an IoT component.
• The DISSECT-CF-Fog simulator demonstrates capabilities for scalability studies and assessing the interoperability of scientific and IoT workflows.

Conclusions:

• The enhanced DISSECT-CF-Fog simulator provides a valuable tool for modeling and evaluating complex IoT applications and workflows.
• The research emphasizes the need for simulators that can handle the integration of IoT factors in scientific workflow analysis.
• The findings support the use of DISSECT-CF-Fog for investigating the scalability and interoperability of diverse workflow types in distributed computing environments.