(WIP) Tasks Selection Policies for Securing Sensitive Data on Workflow Scheduling in Clouds

Shishido, Henrique Yoshikazu; Estrella, Júlio Cézar; Toledo, Cláudio Fabiano Motta; Reiff-Marganiec, Stephan

doi:10.1109/scc.2018.00037

Cited by 4 publications

(3 citation statements)

References 12 publications

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“…Liu et al [14] presented a new searchable encryption scheme that guarantees data privacy as well as efficient data search and retrieval in a distributed environment. Because encryption increases execution times, Shishido et al [15] proposed a task selection strategy for private clouds according to the MPGA (multi-population genetic algorithm) method. Yin et al [16] proposed a location privacy protection method that satisfies differential privacy constraints to protect location data privacy and maximizes data and algorithm utility.…”

Section: Related Workmentioning

confidence: 99%

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Hybrid Cloud Workflow Scheduling Method With Privacy Data

2020

IEEE Access

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Privacy protection is an important problem in workflow scheduling, for which scheduling tasks with privacy constraints to reliable resources is essential. In this article, we consider the scheduling problem of Spark applications in a hybrid cloud with deadline and privacy constraints. A scheduling algorithm framework is proposed, which consists of four algorithm components. Candidate strategies are developed for each algorithm component. The components and parameter values are statistically calibrated over a comprehensive set of random instances. The proposed algorithm is compared to modified classical algorithms for similar problems. The experimental results indicate that the proposed algorithm outperforms the compared algorithms under different application scales, deadlines, and private VMs INDEX TERMS Spark, privacy task, cost optimization, hybrid cloud.

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Section: Related Workmentioning

confidence: 99%

“…Ten instances are generated for each number of jobs. The number of stages in each job is uniformly distributed in U (15,20). The number of tasks in each stage is uniformly distributed in U (50, 100).…”

Section: A Parameter Calibrationmentioning

confidence: 99%

Hybrid Cloud Workflow Scheduling Method With Privacy Data

2020

IEEE Access

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“…This extension is available on GitHub 1 . As part of the ongoing research carried out by the authors' group, the workflow management system simulator is employed in a study on security-and cost aware workflow scheduling algorithms in three publications [13], [18], [19]. The studies investigate the application of meta-heuristic algorithms for optimizing the assignment of different VM instances and security services for each task.…”

Section: Usage Examplementioning

confidence: 99%

A CloudSim Extension for Evaluating Security Overhead in Workflow Execution in Clouds

Shishido

Estrella

Toledo

et al. 2018

2018 Sixth International Symposium on Computing and Networking (CANDAR)

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Workflow scheduling algorithms for cloud environments are extensively studied using workflow management system simulators. The common criteria covered by algorithms and addressed in simulators are makespan, monetary cost, reliability, and energy consumption. Beyond these criteria, security is also a criterion and has been investigated recently. Scientific and business workflows typically handle sensitive and big data that can influence the makespan and cost significantly when a scheduling algorithm applies security services to these data. However, simulators for workflow execution do not address the overhead produced by applying security services to sensitive data. In this paper, we propose an extension for workflow simulator to support security services. We considered seven steps for measuring security overheads on workflow execution. The extension was validated by executing a real-world workflow applying three types of security services namely authentication, integrity verification, and encryption. Our extension proved useful for simulating workflow execution applying security services on sensitive data and analyzing the effects of security on makespan, cost and security criteria.

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