Abstract

With the development of cloud computing technologies, more and more scientific workflows have been executed in clouds. However, cloud-based scientific workflows face many threats due to the resource sharing. Adversaries in clouds can directly or indirectly destroy them by means of side channels, virtual machine escape, and so on, which will cause interruption or produce incorrect outputs. Cloud-based scientific workflows are often applied in important scientific research fields, their failures will bring huge losses. Therefore, we propose an Intrusion toleraNt scHeduling algorIthm in cloud-Based scIenTific wORkflow system (INHIBITOR) to enhance the security. This algorithm constructs three replicas for each sub-task and designs a voting mechanism to realize the result verification. Based on this framework, INHIBITOR studies how to schedule these sub-task replicas and deduces the constraints which should be satisfied for intrusion tolerant scheduling. Furthermore, an elastic resource provisioning strategy is presented to improve resource utilization. To verify the effectiveness of INHIBITOR, we conduct experiments with WorkflowSim toolkit and use success rate, task completion rate and execution costs to evaluate it. Experimental results demonstrate that, compared with existing methods, INHIBITOR can not only increase the success rate by around 12.54%, but also improve the efficiency by about 4.7% and reduce execution costs by around 11.29%.

Full Text
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