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DAMCREM: Dynamic Allocation Method of Computation REsource to Macro-Tasks for Fully Homomorphic Encryption Applications

机译:DAMCREM:用于全同态加密应用程序的宏任务计算资源的动态分配方法

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Smart computing aims to improve the quality of life by utilizing Internet-of-Things devices and cloud computing. Typically, this computing handles private and/or personal information so concealing such sensitive information is a challenge. Adopting fully homomorphic encryption (FHE) is one approach for handling such sensitive information safely; that is, we can calculate the encrypted data without decryption. However, the time and space complexity of the FHE operation is high. Thus, its computation takes a long time. In this study, we aim to shorten FHE execution time by adopting our new scheduling algorithm, which divides a task into several macro-tasks and then assigns a set of threads. We assume a cloud computing system that is equipped with a many-core CPU. Thus, we propose the dynamic allocation method of computation resource to macro-tasks (DAMCREM), which dynamically allocates a certain number of threads (selected from pre-defined candidates) to each macro-task of every given job. In the evaluation, we compared DAMCREM to naive methods that allocate a pre-defined number of threads to each macro-task. The result shows that the average latency and maximum latency of job execution is less than those of naive methods, even when the average interval of job arrival is short.
机译:智能计算旨在通过利用物联网设备和云计算来改善生活质量。通常,该计算处理私人和/或个人信息,因此隐藏此类敏感信息是一个挑战。采用完全同态加密(FHE)是安全处理此类敏感信息的一种方法。也就是说,我们无需解密即可计算加密数据。然而,FHE操作的时间和空间复杂度很高。因此,其计算需要很长时间。在本研究中,我们旨在通过采用新的调度算法来缩短FHE执行时间,该算法将一个任务划分为多个宏任务,然后分配一组线程。我们假设云计算系统配备了多核CPU。因此,我们提出了一种将计算资源动态分配给宏任务的方法(DAMCREM),该方法为每个给定作业的每个宏任务动态分配一定数量的线程(从预定义的候选对象中选择)。在评估中,我们将DAMCREM与朴素的方法进行了比较,朴素的方法为每个宏任务分配了预定义数量的线程。结果表明,即使平均到达作业间隔很短,作业执行的平均延迟和最大延迟也比朴素的方法要短。

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