Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Nivedita Sritharan

dblp:202/2116 · DBLP profile ↗
← Back
1ranked-venue papers
1as first author
0since 2021 · last 2019
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Memory systems · 61% Embedded and real-time systems · 39%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Memory systems
cache coherence
0.412019
Enabling Predictable, Simultaneous and Coherent Data Sharing in Mixed Criticality Systems · RTSS 2019
Memory systems › cache coherence
cache coherence protocol
0.412019
Enabling Predictable, Simultaneous and Coherent Data Sharing in Mixed Criticality Systems · RTSS 2019
Embedded and real-time systems › real-time scheduling › mixed-criticality scheduling
mixed-criticality systems
0.412019
Enabling Predictable, Simultaneous and Coherent Data Sharing in Mixed Criticality Systems · RTSS 2019
Embedded and real-time systems
real-time scheduling
0.112019
Enabling Predictable, Simultaneous and Coherent Data Sharing in Mixed Criticality Systems · RTSS 2019

Methods — techniques the papers use, named apart from their topics

time-based cache coherence · 0.4
YearPublicationVenuePosition
2019 Enabling Predictable, Simultaneous and Coherent Data Sharing in Mixed Criticality Systems
abstract
Emerging embedded systems deployed in the automotive and avionics domains execute applications with different criticalities, comprising what is known as Mixed Criticality Systems (MCS). Applications in MCS often share data between tasks (coming from sensors for instance). Data sharing is challenging because it can lead to increased response times or even unpredictable behaviors if not carefully addressed. Therefore, several prior works in MCS either assumed that tasks do not share data or disallowed it by design. Recent solutions attempt to mitigate the effects of data sharing, albeit by introducing new restrictions on the system either by prohibiting applications from caching shared data or prohibiting the operating system from running tasks with shared data in parallel. We find these solutions also to have limited applicability as they deteriorate system schedulability and prohibit simultaneous access to shared data. In this paper, we propose PENDULUM: a time-based cache coherence protocol to enable simultaneous and predictable access to shared data in MCS. Our evaluation shows that PENDULUM, achieves flexibility and better performance compared to existing solutions, while maintaining system predictability.
Nivedita Sritharan, Anirudh M. Kaushik, Mohamed Hassan 0002, Hiren D. Patel
RTSS1