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A Model to Calculate Amazon EC2 Instance
Performance in Frost Prediction Applications
Lucas Iacono
1
,
2
, José Luis Vázquez-Poletti
3
, Carlos García Garino
1
,
4
,
and Ignacio Martín Llorente
3
1
ITIC, Universidad Nacional de Cuyo. Mendoza, Argentina
2
Instituto de Microelectrónica. Facultad de Ingeniería, Universidad de Mendoza
Mendoza, Argentina
lucas.iacono@um.edu.ar
3
Departamento de Arquitectura de Computadores y Automática, Facultad de
Informática, Universidad Complutense de Madrid, Madrid, Spain
jlvazquez@fdi.ucm.es
,
llorente@dacya.ucm.es
4
Facultad de Ingeniería, Universidad Nacional de Cuyo. Mendoza, Argentina
cgarcia@itu.uncu.edu.ar
Abstract. Frosts are one of the main causes of economic losses in the
Province of Mendoza, Argentina. Although it is a phenomenon that hap-
pens every year, frosts can be predicted using Agricultural Monitoring
Systems (AMS). AMS provide information to start and stop frosts de-
fense systems and thus reduce economic losses. In recent years, the emer-
gence of infrastructures called Sensor Clouds improved AMS in several
aspects such as scalability, reliability, fault tolerance, etc. Sensor Clouds
use Wireless Sensor Networks (WSN) to collect data in the field and
Cloud Computing to store and process these data. Currently, Cloud
providers like Amazon offer different instances to store and process data
in a profitable way. Moreover, due to the variety of offered instances
arises the need for tools to determine which is the most appropriate in-
stance type, in terms of execution time and economic costs, for running
agro-meteorological applications. In this paper we present a model tar-
geted to estimate the execution time and economic cost of Amazon EC2
instances for frosts prediction applications.
1
Introduction
Frost is an agro-meteorological event which causes both damage in crops and
important economic losses. The impact of frost damages in the Province of Men-
doza, region of Cuyo, Argentina (which affected up to 80% of crops in 2013)
resulted in economic emergency in all the region. Due to frosts happen every
year, there are different defense methods (such as surface irrigation, heaters and
others) that can be used to minimize damage.
Defense systems should be activated based on information provided by Agri-
cultural Monitoring Systems (AMS). AMS perform in-field data acquisition and
data management. Moreover, AMS ensure production quality and guarantee
crops traceability.
