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Xiaofan Wu

dblp:20/522 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2014
0000-0003-2176-5961ORCID · corroborated

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

Systems, architecture and hardware · 2Software engineering, systems software and programming languages · 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
1 paper
Internet of things and sensor networks · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Embedded and real-time systems · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Internet of things and sensor networks › wireless sensor network › sensor network programming
reprogramming
0.112010
Elon: enabling efficient and long-term reprogramming for wireless sensor networks · SIGMETRICS 2010
Internet of things and sensor networks
wireless sensor network
0.112010
Elon: enabling efficient and long-term reprogramming for wireless sensor networks · SIGMETRICS 2010
Embedded and real-time systems › wireless communication
wireless sensor networks
0.112010
Elon: enabling efficient and long-term reprogramming for wireless sensor networks · SIGMETRICS 2010

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

software reboot · 0.2replaceable component · 0.2
YearPublicationVenuePosition
2014 Elon: Enabling efficient and long-term reprogramming for wireless sensor networks
abstract
We present a new mechanism called Elon for enabling efficient and long-term reprogramming in wireless sensor networks. Elon reduces the transferred code size significantly by introducing the concept of replaceable component. It avoids the cost of hardware reboot with a novel software reboot mechanism. Moreover, it significantly prolongs the reprogrammable lifetime (i.e., the time period during which the sensor nodes can be reprogrammed) by avoiding flash writes for TelosB nodes. Experimental results show that Elon transfers up to 120--389 times less information than Deluge, and 18--42 times less information than Stream. The software reboot mechanism that Elon applies reduces the rebooting cost by 50.4%--53.87% in terms of beacon packets, and 56.83% in terms of unsynchronized nodes. In addition, Elon prolongs the reprogrammable lifetime by a factor of 3.3.
Wei Dong 0001, Yunhao Liu 0001, Chun Chen 0001, Lin Gu 0001, Xiaofan Wu
ACM Trans. Embed. Comput. Syst.5
2010 Elon: enabling efficient and long-term reprogramming for wireless sensor networks
abstract
We present a new mechanism called Elon for enabling efficient and long-term reprogramming in wireless sensor networks. Elon reduces the transferred code size significantly by introducing the concept of replaceable component. It avoids the cost of hardware reboot with a novel software reboot mechanism. Moreover, it significantly prolongs the reprogramming lifetime by avoiding flash writes for TelosB nodes. Experimental results show that Elon transfers up to 120--389 times less information than Deluge, and 18-42 times less information than Stream. The software reboot mechanism that Elon applies reduces the rebooting cost by 50.4%-53.87% in terms of beacon packets, and 56.83% in terms of unsynchronized nodes. In addition, Elon prolongs the reprogramming lifetime by a factor of 2.3.
Wei Dong 0001, Yunhao Liu 0001, Xiaofan Wu, Lin Gu 0001, Chun Chen 0001
SIGMETRICS3