Demo Data from VLDB 2026 / reviewers in the wild / expert
Mohamed Salehmohamed
dblp:46/3279
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 1987
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1 · 1 first-authorSoftware engineering, systems software and programming languages · 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 |
Parallel and multicore computing · 53% Distributed systems · 32% Performance modeling and evaluation · 16% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Parallel and multicore computing › parallel algorithms › sorting
parallel sorting |
0.0 | 1 | 1987 | Performance Evaluation of LAN Sorting Algorithms · SIGMETRICS 1987 |
Distributed systems
distributed algorithms |
0.0 | 1 | 1987 | Performance Evaluation of LAN Sorting Algorithms · SIGMETRICS 1987 |
Distributed systems › distributed algorithms
distributed sorting |
0.0 | 1 | 1987 | Performance Evaluation of LAN Sorting Algorithms · SIGMETRICS 1987 |
Methods — techniques the papers use, named apart from their topics
theoretical analysis · 0.0empirical measurement · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1987 | Performance Evaluation of LAN Sorting AlgorithmsabstractWe adapt several parallel sorting algorithms (block sorting algorithms) and distributed sorting algorithms for implementation on an Ethernet network with diskless Sun workstations. We argue that the performance of sorting algorithms on local area networks (LANs) should be analyzed in a manner that is different from the ways that parallel and distributed sorting algorithms are usually analyzed. Consequently, we propose an empirical approach which will provide more insight into the performance of the algorithms. We obtain data on communication time, local processing time, and response time (i.e. total running time) of each algorithm for various file sizes and different numbers of processors. Comparing the performance data with our theoretical analysis, we attempt to provide rationale for the behaviour of the algorithms and project the future behaviour of the algorithms as file size, number of processors, or interprocessor communication facilities change. Mohamed Salehmohamed, Wo-Shun Luk, Joseph G. Peters |
SIGMETRICS | 1 |