Demo Data from EDBT 2026 / reviewers in the wild / expert
Mohammadali Khodabandehlou
dblp:404/0184
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2025
0009-0005-5791-5337ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 1 · 1 first-author · 1 since 2021
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 networks
1 paper |
Internet of things and sensor networks · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Parallel and multicore computing · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Parallel and multicore computing
parallel scheduling |
0.3 | 1 | 2025 | Poster Abstract: Scheduling Dynamic IoT Task Graphs · SenSys 2025 |
Parallel and multicore computing › task scheduling
task graph scheduling |
0.3 | 1 | 2025 | Poster Abstract: Scheduling Dynamic IoT Task Graphs · SenSys 2025 |
Methods — techniques the papers use, named apart from their topics
residual scheduling · 1.7cumulative scheduling · 1.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Poster Abstract: Scheduling Dynamic IoT Task GraphsabstractScheduling a given graph of tasks on a processing network has been a topic of interest and has been extensively studied, including for IoT applications. However, scheduling a series of task graphs that arrive at different time instances is still under-explored. We discuss this problem and introduce two approaches for it: Residual and Cumulative. We demonstrate using two subtle examples that both approaches face performance challenges. Mohammadali Khodabandehlou, Jared Coleman, Bhaskar Krishnamachari |
SenSys | 1 |