標題: A Wi-Fi Union Mechanism for Internet Advertising Reciprocal Platform in Microenterprises
作者: Thi Thanh An Nguyen
Chang, Che-Pin
Yuan, Shyan-Ming
資訊工程學系
電機學院碩士在職專班
Department of Computer Science
Degree Program of Electrical and Computer Engineering
關鍵字: internet advertising;mobile advertising;Wi-Fi advertising;fog computing;QR code
公開日期: 1-七月-2017
摘要: With the evolution of the Internet and smartphone devices, Internet advertising has become one of the most important methods for delivering promotional marketing messages to customers. However, the efficiency of Internet advertising for microenterprise is not very high, since Wi-Fi advertisingwhich is limited by a small router coverage areais mainly used. Moreover, because of the lack of money, microenterprises have been using low-cost methods to promote their products. Thus, enhancing the effectiveness of Wi-Fi advertising, and solving the problem of cost and the range of the views are now an essential investigation in this study. In this paper, we propose a reciprocal model with Wi-Fi union mechanism for Internet advertising based on fog computing architecture to enhance the efficiency of advertisement, reduce the cost, and increase the range of the views for microenterprise by using the Internet. In particular, the system was built in advertisers', publishers', and consumers' sides. In our system, we use contribution point (CP) as an exchange value among the participants. Advertisers and publishers can get CP by helping the others in the system to promote their advertisements, increasing their CP by one unit. Similarly, advertisers and publishers can use their CP to ask for assistance from the others, decreasing their CP by one unit. The result shows that the system in a Wi-Fi union is easy to use, and advertisements can be seen by all customers who are using free Wi-Fi from the stores of the union. This method can solve the problem of cost and fixed consumer groups.
URI: http://dx.doi.org/10.3390/s17071617
http://hdl.handle.net/11536/145906
ISSN: 1424-8220
DOI: 10.3390/s17071617
期刊: SENSORS
Volume: 17
Issue: 7
起始頁: 0
結束頁: 0
顯示於類別:期刊論文


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