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Coded elastic computing enables virtual machines to be preempted for high-priority tasks while allowing new virtual machines to join ongoing computation seamlessly. This paper addresses coded elastic computing for matrix-matrix multiplications with straggler tolerance by encoding both storage and download using Lagrange codes. In 2018, Yang et al. introduced the first coded elastic computing scheme for matrix-matrix multiplications, achieving a lower computational load requirement. However, this scheme lacks straggler tolerance and suffers from high upload cost. Zhong et al. (2023) later tackled these shortcomings by employing uncoded storage and Lagrange-coded download. However, their approach requires each machine to store the entire dataset. This paper introduces a new class of elastic computing schemes that utilize Lagrange codes to encode both storage and download, achieving a reduced storage size. The proposed schemes efficiently mitigate both elasticity and straggler effects, with a storage size reduced to a fraction 1/L of Zhong et al.'s approach, at the expense of doubling the download cost. Moreover, we evaluate the proposed schemes on AWS EC2 by measuring computation time under two different tasks allocations: heterogeneous and cyclic assignments. Both assignments minimize computation redundancy of the system while distributing varying computation loads across machines. 

Coded elastic computing, introduced by Yang et al. in 2018, is a technique designed to mitigate the impact of elasticity in cloud computing systems, where machines can be preempted or be added during computing rounds. This approach utilizes maximum distance separable (MDS) coding for both storage and download in matrix-matrix multiplications. The proposed scheme is unable to tolerate stragglers and has high encoding complexity and upload cost. In 2023, we addressed these limitations by employing uncoded storage and Lagrange-coded download. However, it results in a large storage size. To address the challenges of storage size and upload cost, in this paper, we focus on Lagrange-coded elastic computing based on uncoded download. We propose a new class of elastic computing schemes, using Lagrange-coded storage with uncoded download (LCSUD). Our proposed schemes address both elasticity and straggler challenges while achieving lower storage size, reduced encoding complexity, and upload cost compared to existing methods. 

In cloud computing systems, elastic events and stragglers increase the uncertainty of the system, leading to computation delays. Coded elastic computing (CEC) introduced by Yang et al. in 2018 is a framework which mitigates the impact of elastic events using Maximum Distance Separable (MDS) coded storage. It proposed a CEC scheme for both matrix-vector multiplication and general matrix-matrix multiplication applications. However, in these applications, the proposed CEC scheme cannot tolerate stragglers due to the limitations imposed by MDS codes. In this paper we propose a new elastic computing scheme using uncoded storage and Lagrange coded computing approaches. The proposed scheme can effectively mitigate the effects of both elasticity and stragglers. Moreover, it produces a lower complexity and smaller recovery threshold compared to existing coded storage based schemes. 

Abstract The ionization fraction is a key figure of merit for optimizing the performance of plasma device. This work presents an optical emission spectroscopy (OES) method to determine the ionization fraction in low-temperature xenon plasma. The emission line-ratio of xenon ionic and atomic 6p–6stransitions is used in this method. A comprehensive collisional-radiative model developed in our previous work is employed to describe the relationship between the line-ratios and the plasma parameters. It is found that some special line-ratios have a sensitive relationship to the ionization fraction, e.g. the ratio of the 460.30 nm line and 828.01 nm lines. These line-ratios are selected for the diagnostic method. The method is demonstrated in a magnetized discharge chamber. The axially-resolved emission spectra of the ionization chamber are measured, and from those the ionization fraction along the chamber axis is determined via the OES method. The axially-resolved ionization fraction is found to be dependent on the magnetic field and agrees well with those obtained from a Langmuir probe. In the experiment, the probe is overheated under some conditions, possibly due to the bombardment by energetic particles. In this case, no results can be obtained from the probe, while the OES method can still obtain reasonable results. Combined with optical tomography and spectral imaging technology, the OES method can also provide the spatial distribution of the ionization fraction, which is needed for revealing the discharge mechanisms of plasma devices.