activity
20182026
most citedFaaSdom: A Benchmark Suite for Serverless Computing

69 citations · 707 across the 60 of their papers we have counts for

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Showing 2021Show all

8 papers · 1 filter

cs.DC2021★ 3 cited

Scrooge Attack: Undervolting ARM Processors for Profit

Christian Göttel, Konstantinos Parasyris, Osman Unsal +3

Latest ARM processors are approaching the computational power of x86 architectures while consuming much less energy. Consequently, supply follows demand with Amazon EC2, Equinix Me…

cs.CR2021★ 2 cited

Analysis and Improvement of Heterogeneous Hardware Support in Docker Images

Panagiotis Gkikopoulos, Valerio Schiavoni, Josef Spillner

Docker images are used to distribute and deploy cloud-native applications in containerised form. A container engine runs them with separated privileges according to namespaces. Rec…

cs.DC2021★ 6 cited

NVCache: A Plug-and-Play NVMM-based I/O Booster for Legacy Systems

Rémi Dulong, Rafael Pires, Andreia Correia +4

This paper introduces NVCache, an approach that uses a non-volatile main memory (NVMM) as a write cache to improve the write performance of legacy applications. We compare NVCache…

cs.CR2021

KEVLAR-TZ: A Secure Cache for ARM TrustZone

Oscar Benedito, Ricard Delgado-Gonzalo, Valerio Schiavoni

Edge devices are increasingly in charge of storing privacy-sensitive data, in particular implantables, wearables, and nearables can potentially collect and process high-resolution…

cs.DC2021★ 2 cited

Security, Performance and Energy Implications of Hardware-assisted Memory Protection Mechanisms on Event-based Streaming Systems

Christian Göttel, Rafael Pires, Isabelly Rocha +4

Major cloud providers such as Amazon, Google and Microsoft provide nowadays some form of infrastructure as a service (IaaS) which allows deploying services in the form of virtual m…

cs.CR2021

Plinius: Secure and Persistent Machine Learning Model Training

Peterson Yuhala, Pascal Felber, Valerio Schiavoni +1

With the increasing popularity of cloud based machine learning (ML) techniques there comes a need for privacy and integrity guarantees for ML data. In addition, the significant sca…