Authors: Richard K. Lomotey; Harsha Guttikonda; Ralph Deters
Addresses: Department of Information Sciences and Technology (IST), Pennsylvania State University, Beaver Campus, Monaca, PA 15061, USA ' Department of Information Sciences and Technology (IST), Pennsylvania State University, Beaver Campus, Monaca, PA 15061, USA ' Department of Computer Science, University of Saskatchewan, Saskatoon, SK, S7N 5C9, Canada
Abstract: One of the enterprises that has heavily adopted mobile technology today is the agriculture sector. Farmers and agro specialists can use their smartphones and tablets to easily communicate, advertise goods and services, as well as access agronomic data in soft-real time. The palpable barrier however is the mode of communication of these mobile devices, which is the use of wireless channels orthodoxly. As a result, agronomic mobile applications can experience bandwidth fluctuations and inefficient propagation of data in mobile cloud computing architectures. To address this issue, some existing works proposed a P2P synchronisation technique that is based on three algorithms namely: bloom filters, whole state data transfer, and exchange of deltas only. In this paper, we have totally redesigned and replaced the P2P synchronisations with the data-centric publish-subscribe model that improves the efficiency of the agronomic data synchronisation. As part of this research, a real-world agronomic mobile app is developed and tested where empirical evaluations show that the data-centric publish-subscribe approach is better in terms of latency optimisation in agronomic data management. The well-researched app is called FlagThis and it is available in the App store for free download by farmers and agro-experts.
Keywords: mobile devices; middleware; publish-subscribe; agro-data; data synchronisation; P2P; peer-to-peer; cloud computing; agronomic data; data management; crop fields; agriculture; smartphones; tablets; farming; mobile apps; mobile applications; latency optimisation.
International Journal of Sustainable Agricultural Management and Informatics, 2017 Vol.3 No.1, pp.65 - 90
Received: 29 Aug 2016
Accepted: 13 Nov 2016
Published online: 15 Mar 2017 *