Cookies Policy
The website need some cookies and similar means to function. If you permit us, we will use those means to collect data on your visits for aggregated statistics to improve our service. Find out More
Accept Reject
  • Menu
Interest
Topics
Details

Details

  • Name

    Mariana Martins Miranda
  • Role

    Research Assistant
  • Since

    15th January 2020
002
Publications

2023

Distributed and Dependable Software-Defined Storage Control Plane for HPC

Authors
Miranda, M;

Publication
2023 IEEE/ACM 23RD INTERNATIONAL SYMPOSIUM ON CLUSTER, CLOUD AND INTERNET COMPUTING WORKSHOPS, CCGRIDW

Abstract
The Software-Defined Storage (SDS) paradigm has emerged as a way to ease the orchestration and management complexities of storage systems. This work aims to mitigate the storage performance issues that large-scale HPC infrastructures are currently facing by developing a scalable and dependable control plane that can be integrated into an SDS design to take full advantage of the tools this paradigm offers. The proposed solution will enable system administrators to define storage policies (e.g., I/O prioritization, rate limiting) and, based on them, the control plane will orchestrate the storage system to provide better QoS for data-centric applications.

2022

Protecting Metadata Servers From Harm Through Application-level I/O Control

Authors
Macedo, R; Miranda, M; Tanimura, Y; Haga, J; Ruhela, A; Harrell, SL; Evans, RT; Paulo, J;

Publication
2022 IEEE INTERNATIONAL CONFERENCE ON CLUSTER COMPUTING (CLUSTER 2022)

Abstract
Modern large-scale I/O applications that run on HPC infrastructures are increasingly becoming metadata-intensive. Unfortunately, having multiple concurrent applications submitting massive amounts of metadata operations can easily saturate the shared parallel file system's metadata resources, leading to unresponsiveness of the storage backend and overall performance degradation. To address these challenges, we present PADLL, a storage middleware that enables system administrators to proactively control and ensure QoS over metadata workflows in HPC storage systems. We demonstrate its performance and feasibility by controlling the rate of both synthetic and realistic I/O workloads. Results show that PADLL can dynamically control metadata-aggressive workloads, prevent I/O burstiness, and ensure I/O fairness and prioritization.

2021

S2Dedup: SGX-enabled secure deduplication

Authors
Miranda, M; Esteves, T; Portela, B; Paulo, J;

Publication
SYSTOR '21: The 14th ACM International Systems and Storage Conference, Haifa, Israel, June 14-16, 2021.

Abstract
Secure deduplication allows removing duplicate content at third-party storage services while preserving the privacy of users' data. However, current solutions are built with strict designs that cannot be adapted to storage service and applications with different security and performance requirements. We present S2Dedup, a trusted hardware-based privacy-preserving deduplication system designed to support multiple security schemes that enable different levels of performance, security guarantees and space savings. An in-depth evaluation shows these trade-offs for the distinct Intel SGX-based secure schemes supported by our prototype. Moreover, we propose a novel Epoch and Exact Frequency scheme that prevents frequency analysis leakage attacks present in current deterministic approaches for secure deduplication while maintaining similar performance and space savings to state-of-the-art approaches.

2021

S2Dedup: SGX-enabled Secure Deduplication

Authors
Esteves, T; Miranda, M; Paulo, J; Portela, B;

Publication
IACR Cryptol. ePrint Arch.

Abstract