MarketNet: An Asymmetric Transmission Power-based Wireless System for Managing e-Price Tags in Markets
- Authors
- Kim, Hyung-Sin; Cho, Hosoo; Lee, Myung-Sup; Paek, Jeongyeup; Ko, JeongGil; Bahk, Saewoong
- Issue Date
- Nov-2015
- Publisher
- ASSOC COMPUTING MACHINERY
- Keywords
- Wireless sensor networks; network architecture; routing protocol; low-power lossy network; RPL
- Citation
- SENSYS'15: PROCEEDINGS OF THE 13TH ACM CONFERENCE ON EMBEDDED NETWORKED SENSOR SYSTEMS, pp 281 - 294
- Pages
- 14
- Journal Title
- SENSYS'15: PROCEEDINGS OF THE 13TH ACM CONFERENCE ON EMBEDDED NETWORKED SENSOR SYSTEMS
- Start Page
- 281
- End Page
- 294
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/48530
- DOI
- 10.1145/2809695.2809717
- ISSN
- 0000-0000
- Abstract
- Updating price tags in a large-scale market is a recurrent task, still performed manually in most markets. Given that human-errors can easily lead to customer complaints and accounting inaccuracies, the ability to autonomously reconfigure price tags can be of significant benefit. With the introduction of low-power display techniques such as electronicink, applications of enabling electronic, wirelessly reconfigurable price tags show potential for future deployment. In this work, we examine networking architectures that can be applied in such scenarios. Through a series of preliminary pilot studies in an actual supermarket, we show that the performance of existing protocols are not ready to overcome the unique challenges of busy market environments. We identify underlying technical challenges and propose MarketNet, an asymmetric transmission power-based system designed for densely populated, obstacle-rich, downwards traffic-oriented environments. We evaluate MarketNet in a large indoor market visited by 5000+ customers per day. Our results show that MarketNet addresses the challenges of the target application and environment, while achieving higher packet delivery performance with noticeably lower radio duty-cycles than existing protocols such as RPL and SHDP.
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Collections - College of Software > School of Computer Science and Engineering > 1. Journal Articles
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