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Henko Aantjes

dblp:182/2526 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2019
—ORCID · none

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

Computer networks · 2 · 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 networks
2 papers
Internet of things and sensor networks · 73% Physical-layer communications · 22% Wireless networking · 5%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Energy-efficient computing · 50% Embedded and real-time systems · 50%

Topics — the 6 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Internet of things and sensor networks › RFID systems
computational RFID
0.722019
On the Synchronization of Computational RFIDs · IEEE Trans. Mob. Comput. 2019
Fast downstream to many (computational) RFIDs · INFOCOM 2017
Physical-layer communications
synchronization
0.412019
On the Synchronization of Computational RFIDs · IEEE Trans. Mob. Comput. 2019
Energy-efficient computing
energy harvesting
0.412019
On the Synchronization of Computational RFIDs · IEEE Trans. Mob. Comput. 2019
Embedded and real-time systems
intermittent computing
0.412019
On the Synchronization of Computational RFIDs · IEEE Trans. Mob. Comput. 2019
Internet of things and sensor networks › RFID systems
EPC Gen2 protocol
0.312017
Fast downstream to many (computational) RFIDs · INFOCOM 2017
Internet of things and sensor networks
RFID systems
0.312017
Fast downstream to many (computational) RFIDs · INFOCOM 2017

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

proportional-integral control · 0.8multi-tag transfer · 0.3fast feedback verification · 0.3compressed data streams · 0.3
YearPublicationVenuePosition
2019 On the Synchronization of Computational RFIDs
abstract
Battery-free computational RFID platforms, such as WISP (Wireless Identification and Sensing Platform), are intermittently-powered devices designed for replacing existing sensor networks. Accordingly, synchronization appears as one of the crucial building blocks for collaborative and coordinated actions in these platforms. However, intermittent power leads to frequent loss of computational state and short-term clock frequency instability that makes synchronization challenging. In this article, we introduce the WISP-Sync protocol that provides synchronization among WISP tags in the communication range of an RFID reader. WISP-Sync overcomes the aforementioned challenges by employing a Proportional-Integral (PI) controller-inspired algorithm which (i) is adaptive-reactive to short-term clock instabilities; (ii) requires only a few computation steps-suitable for limited harvested energy; and (iii) keeps a few variables to hold the synchronization state-minimum overhead to recover from power interrupts. Evaluations in our testbed showed that WISP-Sync ensured an average synchronization error of approximately 1 ms among the tags with an average energy overhead of 1.85 μJ per synchronization round.
Kasim Sinan Yildirim, Henko Aantjes, Przemyslaw Pawelczak, Amjad Yousef Majid
IEEE Trans. Mob. Comput.2
2017 Fast downstream to many (computational) RFIDs
abstract
We present Stork - an extension of the EPC C1G2 protocol allowing streaming of data to multiple Computational Radio Frequency IDentification tags (CRFIDs) simultaneously at up to 20 times faster than the prior state of the art. Stork introduces downstream attributes never before seen in (C)RFIDs: (i) fast feedback for CRFID downstream verification based on the internal EPC C1G2 memory check command - which we analytically and experimentally show to be the best possible downstream verification process based on EPC C1G2; (ii) ability to perform multi-CRFID transfer - which in our experiments speeds up downstream by more than two times compared to sequential transmission; and (iii) the use of compressed data streams - which improves firmware reprogramming times by up to 10% at large reader-to-CRFID distances.
Henko Aantjes, Amjad Yousef Majid, Przemyslaw Pawelczak, Jethro Tan, Aaron N. Parks, Joshua R. Smith 0001
INFOCOM1