Toward Efficient and Secure Task Scheduling Using Trust Optimizer Multi‐Cloud Scheduler

ABSTRACT The growing demand for computational resources has led to the adoption of multi‐cloud frameworks that distribute workloads across various cloud service providers to enhance scalability and availability. However, existing task scheduling algorithms in such environments often suffer from inefficient prioritization, lack of dependency handling, and inadequate security measures. To address these challenges, this paper introduces the Multi‐Cloud Secure Task Scheduling Optimizer (MCSTSO) framework, which combines two core innovations: the Paired Flutter Optimization (PFO) algorithm and the SecureX RSA encryption mechanism. PFO is a hybrid algorithm that integrates task pairing with a modified Butterfly Optimization Algorithm (BOA) for efficient multi‐cloud scheduling. It begins by grouping tasks into pairs based on calculated attributes and threshold values. These pairs are then scheduled using the modified BOA, which considers deadlines, resource availability, and execution costs. This approach improves scheduling efficiency, minimizes completion time, and enhances resource utilization. Simultaneously, SecureX RSA ensures robust data protection through a multi‐layered cryptographic scheme, safeguarding task data during transmission and execution. The SecureX RSA mechanism ensures data confidentiality by encrypting task data during transmission and execution in the multi‐cloud environment. It works in tandem with the PFO algorithm, securing each task pair while PFO optimizes their scheduling and resource allocation. Experimental results demonstrate a makespan of 1471 s, throughput of 0.28 s, and 91.11% Virtual Machine utilization, confirming the framework's effectiveness in balancing performance with strong data security, even under added cryptographic overhead.