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GTTracker: Location-aware hierarchical model for identifying M-commerce business opportunities

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Abstract

The increased adoption of electronic commerce for selling products and services creates a new channel between consumers and vendors. Commonly, e-commerce platforms are assembled as proprietary and centralized solutions. This method has a high financial cost and slows the entry of both middle and small-sized companies into this communication channel. In this context, this article proposes GTTracker - a hierarchically distributed mobile commerce model for publishing offer and demand requests, which allows the identification of business opportunities based on a user’s location. This model organizes the collection of servers in geographic regions following an extensible approach, where new subregions can be mapped in real time in accordance with the load of requests over a specific region. So, the combination of extensibility, plugin-based matching mechanism, loosely-coupled and location-aware infrastructure and, low cost keywords represents the GTTracker’s contribution. The experiments demonstrated which strategies reduce the resource consumption in the system. Furthermore, the evaluation showed that managers could deploy this application gradually, initially using a low-cost platform. Thus, GTTracker provides infrastructure support and a feasible communication channel for users seeking to buy or sell products efficiently at any time and place.

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Notes

  1. 1 https://dev.mysql.com/doc/refman/5.7/en/fulltext-search.html

  2. 2 http://www.json.org/

  3. 3 http://www.wireshark.org/docs/man-pages/tshark.html

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Acknowledgments

This work was partially supported by the following Brazilian Agencies: FAPERGS, CAPES and CNPq.

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Authors and Affiliations

  1. Applied Computing Graduate Program, Universidade do Vale do Rio dos Sinos, São Leopoldo, RS, Brazil

    Paulo Henrique Cazarotto, Cristiano André da Costa, Rodrigo da Rosa Righi & Jorge Luis Victória Barbosa

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  1. Paulo Henrique Cazarotto
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  2. Cristiano André da Costa
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  3. Rodrigo da Rosa Righi
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  4. Jorge Luis Victória Barbosa
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Correspondence to Cristiano André da Costa.

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Cazarotto, P.H., da Costa, C.A., da Rosa Righi, R. et al. GTTracker: Location-aware hierarchical model for identifying M-commerce business opportunities. Peer-to-Peer Netw. Appl. 12, 13–31 (2019). https://doi.org/10.1007/s12083-017-0621-1

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