HASLab - Indexed Articles in Journals

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Browsing HASLab - Indexed Articles in Journals by Author "5594"
  • Item
    Decentralized Privacy-Preserving Proximity Tracing
    ( 2020) Binns,R ; Barrat,A ; Fiore,D ; Manuel Barbosa ; Rui Carlos Oliveira ; José Orlando Pereira ; Basin,DA ; Beutel,J ; Jackson,D ; Roeschlin,M ; Leu,P ; Preneel,B ; Smart,NP ; Abidin,A ; Gürses,SF ; Veale,M ; Cremers,C ; Backes,M ; Tippenhauer,NO ; Cattuto,C ; Troncoso,C ; Payer,M ; Hubaux,JP ; Salathé,M ; Larus,JR ; Bugnion,E ; Lueks,W ; Stadler,T ; Pyrgelis,A ; Antonioli,D ; Barman,L ; Chatel,S ; Paterson,KG ; Capkun,S ; 5602 ; 5604 ; 5594
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    Toward a Practical and Timely Diagnosis of Application's I/O Behavior
    ( 2023) Ricardo Gonçalves Macedo ; Tânia Conceição Araújo ; Rui Carlos Oliveira ; João Tiago Paulo ; 6941 ; 7401 ; 5594 ; 5621
    We present DIO, a generic tool for observing inefficient and erroneous I/O interactions between applications and in-kernel storage backends that lead to performance, dependability, and correctness issues. DIO eases the analysis and enables near real-time visualization of complex I/O patterns for data-intensive applications generating millions of storage requests. This is achieved by non-intrusively intercepting system calls, enriching collected data with relevant context, and providing timely analysis and visualization for traced events. We demonstrate its usefulness by analyzing four production-level applications. Results show that DIO enables diagnosing inefficient I/O patterns that lead to poor application performance, unexpected and redundant I/O calls caused by high-level libraries, resource contention in multithreaded I/O that leads to high tail latency, and erroneous file accesses that cause data loss. Moreover, through a detailed evaluation, we show that, when comparing DIO's inline diagnosis pipeline with a similar state-of-the-art solution, our system captures up to 28x more events while keeping tracing performance overhead between 14% and 51%.