## 3 MiniGrid Infrastructures  
Grid computing is an emerging technology where a set of heterogeneously networked resources distributed in geographically dispersed locations are coordinated to provide transparent, dependable, pervasive, and consistent computing support to diverse types of applications [48]. There are different levels of integration that range from the use of computing resources of two or more organizations to the extensive use of all grid resources [49].  
There are several approaches to build and configure grid environments, and there are many efforts to define general schemes for grid resources exploitation. First, grid environments using Globus, Condor, or gLite are considered high-throughput grids or service grids. These grids manage the resource set (machines or clusters) and distribute the processes among these resources. The service grid's goal is to provide an abstraction level for the users so that they can use all the grid's resources while maintaining an adequate security level. Service grids can implement either sequential or parallel applications. On the other hand, the use of a VPN to cluster integration in grid environments avoids the need for specialized packages such as Globus or gLite [50]. A VPN-based grid can be considered a high-performance grid since it can run parallel applications using the resources of several clusters connected in the grid. A VPN creates an encrypted communication channel between groups to ensure secure data exchange.  
In this work, the MiniGrid is composed of two clusters with homogeneous machines (Table 3), each belonging to a different organization, geographically distant (14.37 km), as is shown in Figure 3. One cluster is in the Autonomous University of Morelos State (UAEM), in Cuernavaca city, and the other in the Polytechnic University of Morelos State (UPEMOR), in Jiutepec city, both in the Mexican state of Morelos. In this case, OpenVPN is used to integrate the clusters in a grid environment. Communication between clusters is via a wireless WAN link between institutions (UAEM-UPEMOR) implemented via a point-to-point microwave link with ISM frequency bands with a bandwidth of 30 Mbs [51]. Message passing interface (MPI) is used to exchange data, and to reduce the communication rate between MiniGrid clusters. MPI has been used to develop applications with both Globus-based grids [52] and VPN-based environments [29; 53; 54].  
\begin{table}
\begin{tabular}{c c} \hline \hline \multicolumn{3}{c}{**Software MiniGrid**} \\ \hline
**Centos Linux 5.5, 64 bits, Compiler gcc 4.1.2, OpenMPI1.8 MPICH2, Intel compiler MPI 12.0, Ganglia 3.1.7,** \\
**NFS-utils 1.0.9, OpenVPN, Torque+Maui** \\ \hline Hardware for the UAEM cluster & Hardware for the UPEMOR cluster \\ (cluster.cuexcomate.edu.mx) & (cluster.texcal.edu.mx) \\ \hline Switch 3 COM 24/10/100/1000 & Switch 3 COM 24/10/100/1000 \\ Switch InfiniBand Mellanox, 18 ports, 40 Gb/s QDR & Switch InfiniBand Mellanox, 18 ports, 40 Gb/s QDR \\ \hline Master Node Motherboard: Two Intel Xeon, Six Core & Master Node Motherboard: Two Intel Xeon, Six Core \\
3.06 GHz (12 cores, Total), 12 MB cache, 6 HD 7200 & 3.06 GHz (12 cores, Total), 12 MB cache, 6 HD 7200 \\ RPM, 12 TB, 24 GB RAM, InfiniBand card 40 Gb/s & RPM, 12 TB, 24 GB RAM, InfiniBand card 40 Gb/s \\ \hline
4 slave nodes, Node Motherboard: Two Intel Xeon Six core 3.06 GHz, 12 MB cache, 1 HD 7200 RPM, 500 GB, 24 GB RAM, InfiniBand card 40 Gb/s (Total 4 slaves: 48 cores, 96 GB RAM, 2 TB HD) & 4 slave nodes, Node Motherboard: Two Intel Xeon Six core 3.