<tex> $K$</tex>-Means Clustering-Based Data Compression Scheme for Wireless Imaging Sensor Networks

Paek, Jeongyeup,Ko, JeongGil IEEE 2017 IEEE systems journal Vol.11 No.4

<P>Image-based embedded wireless sensor networks (WSNs) can be a useful tool in various environmental monitoring applications to unobtrusively observe biological phenomena. Our prior deployments of an embedded wireless imaging system at the James Reserve have already shown its feasibility and usefulness. However, we argue that data compression schemes employed in prior systems can be improved to provide higher image transfer rates per node, or lower the energy costs of wireless communication. In this paper, we develop an image compression scheme using <TEX>$K$</TEX>-means clustering on low-power embedded devices for image-based WSNs. Specifically, we use the similarity of pixel colors to group pixels and compress the original image. Using 100 000 images collected from our pilot deployments at the James Reserve, we study the applicability and impact of the proposed <TEX>$K$</TEX>-means clustering-based compression algorithm. Our results suggest that the cost of running <TEX>$K$</TEX>-means learning on a wireless sensor node may outweigh the benefit of data compression, but offloading the learning step and only performing the compression can provide significant energy gains. Specifically, our evaluations with real-world data sets show that our proposed scheme reduces power usage by ∼49%, when sending image updates from a bird nest periodically every 15 min.</P>

Automatic Task Classification via Support Vector Machine and Crowdsourcing

Shin, Hyungsik,Paek, Jeongyeup Hindawi Limited 2018 Mobile information systems Vol.2018 No.-

<P>Automatic task classification is a core part of personal assistant systems that are widely used in mobile devices such as smartphones and tablets. Even though many industry leaders are providing their own personal assistant services, their proprietary internals and implementations are not well known to the public. In this work, we show through real implementation and evaluation that automatic task classification can be implemented for mobile devices by using the support vector machine algorithm and crowdsourcing. To train our task classifier, we collected our training data set via crowdsourcing using the Amazon Mechanical Turk platform. Our classifier can classify a short English sentence into one of the thirty-two predefined tasks that are frequently requested while using personal mobile devices. Evaluation results show high prediction accuracy of our classifier ranging from 82% to 99%. By using large amount of crowdsourced data, we also illustrate the relationship between training data size and the prediction accuracy of our task classifier.</P>

Semi-analytic texturing algorithm for polygon computer-generated holograms.

Lee, Wooyoung,Im, Dajeong,Paek, Jeongyeup,Hahn, Joonku,Kim, Hwi Optical Society of America 2014 Optics express Vol.22 No.25

<P>A texturing method for the semi-analytic polygon computer-generated hologram synthesis algorithm is studied. Through this, the full-potential and development direction of the semi-analytic polygon computer-generated holograms are discussed and compared to that of the conventional numerical algorithm of polygon computer-generated hologram generation based on the fast Fourier transform and bilinear interpolation. The theoretical hurdle of the semi-analytic texturing algorithm is manifested and an approach to resolve this problen. A key mathematical approximation in the angular spectrum computer-generated hologram computation, as well as the trade-offs between texturing effects and computational efficiencies are analyzed through numerical simulation. In this fundamental study, theoretical potential of the semi-analytic polygon computer-generated hologram algorithm is revealed and the ultimate goal of research into the algorithm clarified.</P>

Deep-Fading Hole Avoidance for Secure Region Detection using Channel State Information

Suh, Jihwan,YOO, YONGJAE,Paek, Jeongyeup,박세웅 한국통신학회 2022 Journal of communications and networks Vol.24 No.6

One of the critical challenges in many wirelesssystems is the deep fading hole problem where signals interferedestructively to create an abrupt change in signal amplitude dueto multipath fading. In this work, we tackle this challenge in thecontext of secure region detection (SRD) problem. Specifically, wepropose SHARD, a novel hole avoidance technique that analyzeschannel state information (CSI) to significantly improve theaccuracy of CSI-based SRD. SHARD identifies potential fadingholes in CSI amplitude, and removes an unreliable portion of datawhile utilizing the remaining unaffected part. To compensate forthe loss of information, we define phase-distance for reliable useof time-varying CSI phase, and neighboring reference points areutilized for accurate matching. Our real-world experiments showthat SHARD can achieve a near-perfect 99.96% true-negativeratio (successfully rejecting devices not in the secure region)and an excellent true-positive of 98.01% for practical usage,significantly better than state-of-the-art prior work. We believeour ideas can be generalized to many RF-based localizationsystems to mitigate the deep fading hole problem and improvetheir accuracy.

RPLIE: RPL for Indoor Environments under Midterm Link Fluctuations

Hyung-Sin Kim,Jeongyeup Paek,Saewoong Bahk 한국통신학회 2021 Journal of communications and networks Vol.23 No.3

Link dynamics due to environmental change is a criti cal challenge for wireless networking, and handling it is essentialfor wireless protocols, especially for low-power and lossy multihopwireless networks (LLNs). Prior work have only studied methodsto detect and cope with short-term and long-term link dynamicsin LLN. In this work, we tackle the midterm dynamics due to theopening and closing of doors and windows that can happen in atime scale of a few minutes to hours in an indoor LLN. Specifi cally, we study how midterm link fluctuations impact the perfor mance of standard IPv6 routing protocol for LLN (RPL), and de sign ‘RPLIE,’ a novel and backward-compatible lightweight en hancement to RPL that detects and overcomes the negative impactof such dynamics. We define ‘opportunistic links’ and propose anovel routing metric, expected breakage cost (EBC), which rep resents the expected number of link transmissions required froma link breakage to a routing parent change. We implement RPLIEon real embedded devices, and evaluate its performance against thestandard RPL via experiments on a 31-node testbed to show thatRPLIE achieves significantly better packet delivery performancewhile using less overhead.

Load Balancing Under Heavy Traffic in RPL Routing Protocol for Low Power and Lossy Networks

Kim, Hyung-Sin,Kim, Hongchan,Paek, Jeongyeup,Bahk, Saewoong IEEE Computer Society 2017 IEEE TRANSACTIONS ON MOBILE COMPUTING Vol.16 No.4

<P>RPL is an IPv6 routing protocol for low-power and lossy networks (LLNs) designed to meet the requirements of a wide range of LLN applications including smart grid AMIs, industrial and environmental monitoring, and wireless sensor networks. RPL allows bidirectional end-to-end IPv6 communication on resource constrained LLN devices, leading to the concept of the Internet of Things (IoT) with thousands and millions of devices interconnected through multihop mesh networks. In this article, we investigate the load balancing and congestion problem of RPL. Specifically, we show that most of the packet losses under heavy traffic are due to congestion, and a serious load balancing problem appears in RPL in terms of routing parent selection. To overcome this problem, this article proposes a simple yet effective queue utilization based RPL (QU-RPL) that achieves load balancing and significantly improves the end-to-end packet delivery performance compared to the standard RPL. QU-RPL is designed for each node to select its parent node considering the queue utilization of its neighbor nodes as well as their hop distances to an LLN border router (LBR). Owing to its load balancing capability, QURPL is very effective in lowering queue losses and increasing the packet delivery ratio. We implement QU-RPL on a low-power embedded platform, and verify all of our findings through experimental measurements on a real testbed of a multihop LLN over IEEE 802.15.4. We present the impact of each design element of QU-RPL on performance in detail, and also show that QU-RPL reduces the queue loss by up to 84 percent and improves the packet delivery ratio by up to 147 percent compared to the standard RPL.</P>

RPL Objective Function for Multihop PLC Network

Park, Mingyu,Jeong, Gunmo,Gnawali, Omprakash,Paek, Jeongyeup 한국통신학회 2023 Journal of communications and networks Vol.25 No.1

The increasing number of devices in the Internetof things (IoT) is beginning to exhaust the wireless channel. As an alternative, power line communication (PLC) appearspromising and has the potential of providing easy deploymentat low cost. On one hand, PLC resembles wireless low-powerand lossy networks (LLN). Its performance is time-varying andsensitive to noise, interference, and asymmetry owing to co-existing electronic appliances. However, when running the stan-dard IPv6 routing protocol for LLN (RPL) on PLC, the networksuffers significant reliability loss because RPL does not reflectthe unique characteristics of PLC. To address this problem,we propose PLC-OF, an objective function (OF) for RPL overPLC. PLC-OF exploits PLC’s physical layer (PHY) diversity asa routing metric distinct from other approaches in wireless. PLC-OF finds the most suitable path to prepare for suddeninterference or congestion in power lines. Evaluation results fromreal testbed experiments show that PLC-OF better tolerates noisymedium compared to existing objective functions. Particularly,PLC-OF has better reliability (≈10%) and robustness with lesschannel usage (≈30%) than that of ETX-based MRHOF in highlycongested environments.

Mitigating stealthy jamming attacks in low-power and lossy wireless networks

Heo, Jeongyoon,Kim, Jung-Jun,Paek, Jeongyeup,Bahk, Saewoong Editorial Department of Journal of Communications 2018 Journal of communications and networks Vol.20 No.2

<P>Jamming in wireless networks has advanced to be more stealthy and long-lasting with limited energy. Stealthy attackers transmit short jamming signals to become less detectable with less energy, and yet powerful enough to ruin entire packet transmission procedures. In this article, we deal with three types of stealthy attacks: ‘Reactive jamming’, ‘Jamming ACK’, and ‘Fake ACK’ attacks. These attacks are fatal to low-power and lossy wireless network (LLN) applications because they not only interfere with communication, but also cause LLN devices to quickly drain their batteries. To counter these attacks, we present Dodge-Jam, a lightweight anti-jamming technique suitable for LLN environments to address the stealthy jamming attacks. It protects ACK packet by switching the ACK exchange channel to a channel calculated based on the content of a data packet. Moreover, by partitioning a packet into multiple blocks and performing logical shifts of the blocks when retransmitting the packet, it helps the receiver recover the original packet from received multiple erroneous packets. We implement Dodge-Jam on practical embedded devices, and evaluate its performance through mathematical analysis and experiments on a multi-hop LLN testbed. Our results show that Dodge-Jam successfully avoids many stealthy jamming attacks, recovers jammed packets, and significantly improves packet delivery performance of single-hop and multi-hop networks with small overhead.1</P>

V2X 네트워크에서 자원할당을 위한 기계학습 기반 최적화 기법 연구동향 조사

최남건(Namgeon Choi),조성래(Sungrae Cho),백정엽(Jeongyeup Paek) 한국통신학회 2024 한국통신학회 학술대회논문집 Vol.2024 No.6

분산 의미론적 통신 시스템에 대한 동향 연구

원동욱(Dongwook Won),홍성훈(Seonghun Hong),신용구(Yonggoo Shin),백정엽(Jeongyeup Paek),조성래(Sungrae Cho) 한국통신학회 2024 한국통신학회 학술대회논문집 Vol.2024 No.1