Scheduling for Workflows with Security-Sensitive Intermediate Data by Selective Tasks Duplication in Clouds - 2017


With the wide deployment of cloud computing in several business enterprises along with science and engineering domains, high quality security services are increasingly important for processing workflow applications with sensitive intermediate data. Unfortunately, most existing worklfow scheduling approaches disregard the safety requirements of the intermediate information created by workflows, and overlook the performance impact of encryption time of intermediate data on the start of subsequent workflow tasks. Furthermore, the idle time slots on resources, ensuing from data dependencies among workflow tasks, haven't been adequately exploited to mitigate the impact of information encryption time on workflows' makespans and financial price. To address these issues, this paper presents a novel task-scheduling framework for security sensitive workflows with 3 novel features. Initial, we tend to give comprehensive theoretical analyses on how selectively duplicating a task's predecessor tasks is useful for preventing each the data transmission time and encryption time from delaying task's begin time. Then, we have a tendency to define workflow tasks' latest end time, and prove that tasks will be completed before tasks' latest end time by using least expensive resources to cut back monetary value while not delaying tasks' successors' start time and workflows' makespans. Based on these analyses, we tend to devise a completely unique scheduling approach with selective tasks duplication, named SOLID, incorporating two important phases: 1) task scheduling with selectively duplicating predecessor tasks to idle time slots on resources; and 2) intermediate data encrypting by effectively exploiting tasks' laxity time. We tend to evaluate our solution approach through rigorous performance analysis study using each randomly generated workflows and a few real-world workflow traces. Our results show that the proposed SOLID approach prevails over existing algorithms in terms of makespan, financial costs and resource efficiency.

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