Evidence map›Paper›PMID 34577317›Full record

ArticleSensors (Basel, Switzerland)2021

Low-Power Scan Correlation-Aware Scan Cluster Reordering for Wireless Sensor Networks.

Sangjun Lee, Kyunghwan Cho, Jihye Kim, Jongho Park, Inhwan Lee, Sungho Kang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Sangjun LeeElectrical and Electronic Engineering Department, Yonsei University, Seoul 03722, Korea.
Kyunghwan ChoElectrical and Electronic Engineering Department, Yonsei University, Seoul 03722, Korea.
Jihye KimElectrical and Electronic Engineering Department, Yonsei University, Seoul 03722, Korea.
Jongho ParkElectrical and Electronic Engineering Department, Yonsei University, Seoul 03722, Korea.
Inhwan LeeElectrical and Electronic Engineering Department, Yonsei University, Seoul 03722, Korea.
Sungho KangElectrical and Electronic Engineering Department, Yonsei University, Seoul 03722, Korea.ORCID 0000-0002-7093-2095

Funding

MOTIE and KEIT 20012010, Design for Test of Intelligent Processors
6 · The paper itself

Abstract

Cryptographic circuits generally are used for applications of wireless sensor networks to ensure security and must be tested in a manufacturing process to guarantee their quality. Therefore, a scan architecture is widely used for testing the circuits in the manufacturing test to improve testability. However, during scan testing, test-power consumption becomes more serious as the number of transistors and the complexity of chips increase. Hence, the scan chain reordering method is widely applied in a low-power architecture because of its ability to achieve high power reduction with a simple architecture. However, achieving a significant power reduction without excessive computational time remains challenging. In this paper, a novel scan correlation-aware scan cluster reordering is proposed to solve this problem. The proposed method uses a new scan correlation-aware clustering in order to place highly correlated scan cells adjacent to each other. The experimental results demonstrate that the proposed method achieves a significant power reduction with a relatively fast computational time compared with previous methods. Therefore, by improving the reliability of cryptography circuits in wireless sensor networks (WSNs) through significant test-power reduction, the proposed method can ensure the security and integrity of information in WSNs.

Indexed as

cryptographydesign for testability (DFT)low-power testingscan chain reorderingwireless sensor networks

Identifiers

PMID34577317
PMCPMC8472869

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.