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A. B. M. Musa

dblp:18/10521 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Wireless sensing and localization › tracking
GPS tracking
0.212016
Trading Off Accuracy, Timeliness, and Uplink Usage in Online GPS Tracking · IEEE Trans. Mob. Comput. 2016
Wireless sensing and localization › tracking
device tracking
0.112012
Tracking unmodified smartphones using wi-fi monitors · SenSys 2012
Smart cities and intelligent transportation › traffic estimation
travel time estimation
0.112011
WiFlow: real time travel time estimation using wi-fi monitors · SenSys 2011
Cellular and mobile networks › mobility management › location management
location tracking
0.112016
Trading Off Accuracy, Timeliness, and Uplink Usage in Online GPS Tracking · IEEE Trans. Mob. Comput. 2016
Smart cities and intelligent transportation
traffic monitoring
0.012012
Tracking unmodified smartphones using wi-fi monitors · SenSys 2012
Wireless networking › WLAN
wi-fi monitoring
0.012011
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
YearPublicationVenuePosition
2016 Trading Off Accuracy, Timeliness, and Uplink Usage in Online GPS Tracking
abstract
In 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 usage
abstract
A 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/GIS2
2012 Tracking unmodified smartphones using wi-fi monitors
abstract
Smartphones 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
SenSys1
2011 WiFlow: real time travel time estimation using wi-fi monitors
abstract
A 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
SenSys1