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Peer-to-Peer Networking and Applications

, Volume 12, Issue 1, pp 13–31 | Cite as

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

  • Paulo Henrique Cazarotto
  • Cristiano André da CostaEmail author
  • Rodrigo da Rosa Righi
  • Jorge Luis Victória Barbosa
Article
  • 114 Downloads

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.

Keywords

Mobile commerce Mobile computing Context awareness P2P Dynamic adaptation Matching 

Notes

Acknowledgments

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

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  1. 1.Applied Computing Graduate Program, Universidade do Vale do Rio dos SinosSão LeopoldoBrazil

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