TY - GEN
T1 - A Reliable IoT Data Economic System Based on Edge Computing
AU - Chuang, I. Hsun
AU - Weng, Tzu Chun
AU - Tsai, Jen Sheng
AU - Horng, Mong Fong
AU - Kuo, Yau Hwang
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/12/18
Y1 - 2018/12/18
N2 - IoT data economy is an emerging concept since sensing data are widely applied in various IoT services. To maintain the stability of data economic system, this paper proposes the Reliable IoT Data Economic System (RIDES) to provide IoT data a reliable, automatic, and intelligent trading environment. Applying the smart contract technique, IoT data in RIDES can be automatically traded without human intervention. As the trading procedure is performed based on blockchain, all transactions can be protected against tampering. Also, the RIDES provides the Smart Decision Making Module for users to develop practical pricing strategies. Thus, a seller can derive a price with the highest expected revenue for its data and a buyer can purchase its desired data referring to cost-performance ratio or data owner's trustworthiness. Even if malicious sellers cheat buyers, the latter can invoke trade dispute procedure to refund their payment, which makes the trading environment more reliable. As the blockchain-based operations usually cost much, the RIDES adopts the edge computing architecture to alleviate the burdens of IoT devices. Finally, the RIDES is implemented in IoT environments. The case study demonstrates that the transactions on IoT data can be performed correctly by RIDES.
AB - IoT data economy is an emerging concept since sensing data are widely applied in various IoT services. To maintain the stability of data economic system, this paper proposes the Reliable IoT Data Economic System (RIDES) to provide IoT data a reliable, automatic, and intelligent trading environment. Applying the smart contract technique, IoT data in RIDES can be automatically traded without human intervention. As the trading procedure is performed based on blockchain, all transactions can be protected against tampering. Also, the RIDES provides the Smart Decision Making Module for users to develop practical pricing strategies. Thus, a seller can derive a price with the highest expected revenue for its data and a buyer can purchase its desired data referring to cost-performance ratio or data owner's trustworthiness. Even if malicious sellers cheat buyers, the latter can invoke trade dispute procedure to refund their payment, which makes the trading environment more reliable. As the blockchain-based operations usually cost much, the RIDES adopts the edge computing architecture to alleviate the burdens of IoT devices. Finally, the RIDES is implemented in IoT environments. The case study demonstrates that the transactions on IoT data can be performed correctly by RIDES.
UR - http://www.scopus.com/inward/record.url?scp=85060538321&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85060538321&partnerID=8YFLogxK
U2 - 10.1109/PIMRC.2018.8580742
DO - 10.1109/PIMRC.2018.8580742
M3 - Conference contribution
AN - SCOPUS:85060538321
T3 - IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
BT - 2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 29th IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2018
Y2 - 9 September 2018 through 12 September 2018
ER -