SEAS: Security and Efficiency-Aware Scheduler for Workflow Execution in Edge-Cloud Platform

Abstract

In heterogeneous cloud environments, efficient and secure execution of scientific workflows is a critical challenge due to diverse resource capabilities and varying security requirements. This paper presents SEAS (Security and Efficiency-Aware Scheduler), a novel scheduling algorithm designed to optimize energy consumption and makespan during workflow execution. SEAS leverages an optimization strategy that integrates energy profiling and dynamic security evaluation to select the most appropriate resource for each task. The total energy consumed is calculated as the sum of computational and communication energy, while security is evaluated through trust-based interaction metrics. By incorporating these factors into the task-resource mapping decision process, SEAS ensures energy-efficient execution without compromising security. Experimental results on scientific workflows namely Inspiral and CyberShake demonstrate effectiveness of SEAS. Specifically, SEAS reduces energy consumption by up to 44.02% compared to Reliability and Trust-Aware Task Scheduler (RTATS) and 58.78% compared to Makespan and Security-Aware Scheduler (MSAWS), while achieving makespan reductions of up to 90.1% and 81.8% relative to RTATS and MSAWS, respectively. Furthermore, SEAS consistently maintains high security compliance through trust-aware task-resource pairing. These results show SEAS as a robust, multi-objective scheduler that significantly outperforms conventional trust and security-aware scheduling approaches. Its ability to deliver low-latency and energy-aware execution makes it particularly suitable for energy-constrained and security-sensitive applications in modern cloud and edge computing environments.