Guarding Against Universal Adversarial Perturbations in Data-driven Cloud/Edge Services

Zhou, Xingyu; Canady, Robert; Li, Yang; Bao, Shunxing; Barve, Yogesh; Balasubramanian, Daniel; Gokhālé, Anirüddhā

doi:10.1109/ic2e55432.2022.00032

Cited by 4 publications

(1 citation statement)

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“…Regardless of whether we are using CPUs or GPUs for inference executing, an inference request often goes through logical steps of loading models and waiting in queues. As prior studies demonstrate, model loading time can be orders of magnitude higher than other inference time components using current deep learning frameworks like TensorFlow or with serverless computing [86]- [90]. One naïve solution to reduce model loading time is to keep models in memory; this might work well for popular models but can lead to low resource utilization for less popular models.…”

Section: Iot and Ai Are Becoming The Main Applicationsmentioning

confidence: 99%

On the Future of Cloud Engineering

Bermbach

Chandra

Krintz

et al. 2021

2021 IEEE International Conference on Cloud Engineering (IC2E)

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Ever since the commercial offerings of the Cloud started appearing in 2006, the landscape of cloud computing has been undergoing remarkable changes with the emergence of many different types of service offerings, developer productivity enhancement tools, and new application classes as well as the manifestation of cloud functionality closer to the user at the edge. The notion of utility computing, however, has remained constant throughout its evolution, which means that cloud users always seek to save costs of leasing cloud resources while maximizing their use. On the other hand, cloud providers try to maximize their profits while assuring service-level objectives of the cloud-hosted applications and keeping operational costs low. All these outcomes require systematic and sound cloud engineering principles. The aim of this paper is to highlight the importance of cloud engineering, survey the landscape of best practices in cloud engineering and its evolution, discuss many of the existing cloud engineering advances, and identify both the inherent technical challenges and research opportunities for the future of cloud computing in general and cloud engineering in particular.

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Section: Iot and Ai Are Becoming The Main Applicationsmentioning

confidence: 99%