Demo Data from EDBT 2026 / reviewers in the wild / expert
A. B. M. Musa
dblp:18/10521
· DBLP profile ↗
4ranked-venue papers
3as first author
0since 2021 · last 2016
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 3 · 3 first-authorArtificial intelligence and machine learning · 1Databases, data management, data science and information retrieval · 1Applied, interdisciplinary, general and emerging computing · 1
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
3 papers |
Wireless sensing and localization · 78% Cellular and mobile networks · 15% Wireless networking · 7% | |
| Interdisciplinary, comprehensive, and emerging computing
2 papers |
Smart cities and intelligent transportation · 100% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Wireless sensing and localization › tracking
GPS tracking |
0.2 | 1 | 2016 | Trading Off Accuracy, Timeliness, and Uplink Usage in Online GPS Tracking · IEEE Trans. Mob. Comput. 2016 |
Wireless sensing and localization › tracking
device tracking |
0.1 | 1 | 2012 | Tracking unmodified smartphones using wi-fi monitors · SenSys 2012 |
Smart cities and intelligent transportation › traffic estimation
travel time estimation |
0.1 | 1 | 2011 | WiFlow: real time travel time estimation using wi-fi monitors · SenSys 2011 |
Cellular and mobile networks › mobility management › location management
location tracking |
0.1 | 1 | 2016 | Trading Off Accuracy, Timeliness, and Uplink Usage in Online GPS Tracking · IEEE Trans. Mob. Comput. 2016 |
Smart cities and intelligent transportation
traffic monitoring |
0.0 | 1 | 2012 | Tracking unmodified smartphones using wi-fi monitors · SenSys 2012 |
Wireless networking › WLAN
wi-fi monitoring |
0.0 | 1 | 2011 | WiFlow: real time travel time estimation using wi-fi monitors · SenSys 2011 |
Methods — techniques the papers use, named apart from their topics
wi-fi message capture · 0.3road-side monitoring · 0.3wi-fi packet capture · 0.2vehicle re-identification · 0.2optimization · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | Trading Off Accuracy, Timeliness, and Uplink Usage in Online GPS TrackingabstractIn an online GPS tracking system, a fundamental trade-off exists between timeliness, the average time interval between a recorded change in location and a change in the reported location; accuracy, the average error between the actual location and the reported location; and uplink usage, the average amount of data used per second of tracking. While tracking efficiency has been addressed in the literature, our thrifty tracking system presents the first unified view of timeliness, accuracy, and uplink usage, allowing the user to specify desired targets for any two of these objectives, while optimizing the third. We also provide a closed-form characterization of this three-way trade-off, and demonstrate that our system converges to the predicted performance. A. B. M. Musa, James Biagioni, Jakob Eriksson |
IEEE Trans. Mob. Comput. | 1 |
| 2013 | Thrifty tracking: online GPS tracking with low data uplink usageabstractA typical online GPS tracking system uses a cellular uplink to report the location of a device to a central server, and in a study based on 1.6 billion location updates we find at least 90% are sent with a fixed 1--300 second period. Through experiments with the cost of cellular data transmission we also find that every packet sent incurs significant overhead. James Biagioni, A. B. M. Musa, Jakob Eriksson |
SIGSPATIAL/GIS | 2 |
| 2012 | Tracking unmodified smartphones using wi-fi monitorsabstractSmartphones with Wi-Fi enabled periodically transmit Wi-Fi messages, even when not associated to a network. In one 12-hour trial on a busy road (average daily traffic count 37,000 according to the state DOT), 7,000 unique devices were detected by a single road-side monitoring station, or about 1 device for every 5 vehicles. A. B. M. Musa, Jakob Eriksson |
SenSys | 1 |
| 2011 | WiFlow: real time travel time estimation using wi-fi monitorsabstractA real-time travel time estimation system is demonstrated that uses Wi-Fi monitors deployed along surface streets to capture Wi-Fi packets from smartphones in passing vehicles. Travel time is estimated based on observations of the same vehicle by two or more monitors. A. B. M. Musa, Jakob Eriksson |
SenSys | 1 |