Elasticity plays an important role in modern cloud computing systems. Elastic computing allows virtual machines (i.e., computing nodes) to be preempted when high-priority jobs arise, and also allows new virtual machines to participate in the computation. In 2018, Yang et al. introduced Coded Storage Elastic Computing (CSEC) to address the elasticity using coding technology, with lower storage and computation load requirements. However, CSEC is limited to certain types of computations (e.g., linear) due to the coded data storage based on linear coding. Then Centralized Uncoded Storage Elastic Computing (CUSEC) with heterogeneous computation speeds was proposed, which directly copies parts of data into the virtual machines. In all existing works in elastic computing, the storage assignment is centralized, meaning that the number and identity of all virtual machines possible used in the whole computation process are known during the storage assignment. In this paper, we consider Decentralized Uncoded Storage Elastic Computing (DUSEC) with heterogeneous computation speeds, where any available virtual machine can join the computation which is not predicted and thus coordination among different virtual machines' storage assignments is not allowed. Under a decentralized storage assignment originally proposed in coded caching by Maddah-Ali and Niesen, we propose a computing scheme with closed-form optimal computation time. We also run experiments over MNIST dataset with Softmax regression model through the Tencent cloud platform, and the experiment results demonstrate that the proposed DUSEC system approaches the state-of-art best storage assignment in the CUSEC system in computation time.

翻译：弹性在现代云计算系统中扮演重要角色。弹性计算允许虚拟机（即计算节点）在出现高优先级任务时被抢占，同时也允许新虚拟机参与计算。2018年，Yang等人提出编码存储弹性计算（CSEC），利用编码技术解决弹性问题，所需存储与计算负载较低。然而，由于基于线性编码的编码数据存储，CSEC仅限于特定类型的计算（如线性计算）。随后，研究者提出异构计算速度下的集中式无编码存储弹性计算（CUSEC），该方法将数据部分直接复制到虚拟机中。现有弹性计算研究中，存储分配均为集中式，即存储分配时已知整个计算过程中可能使用的所有虚拟机的数量与身份。本文研究异构计算速度下的去中心化无编码存储弹性计算（DUSEC），其中任意可用虚拟机均可参与计算，且无法预测其加入，因此不同虚拟机的存储分配之间不允许协同。基于Maddah-Ali与Niesen在编码缓存中提出的去中心化存储分配方案，我们提出了一种具有闭式最优计算时间的计算方案。通过腾讯云平台，利用Softmax回归模型在MNIST数据集上开展实验，结果表明，本文提出的DUSEC系统在计算时间上接近CUSEC系统中当前最优的存储分配方案。