Performance evaluation of edge cloud computing system for big data applications

Cloud computing is a convenient model to easily access large amounts of computing resources in order to implement platforms for data intensive applications. These platforms, such as Hadoop, are designed to run on large clusters. When the amount of computing and networking resources are limited, such as in the emergent paradigm of edge computing, maximizing their utilization is of paramount importance. In this paper we investigate the performance of a benchmark suite for Hadoop, running on both physical and virtual infrastructure in a testbed representative of an edge computing deployment. Experimental results show that in spite of a predictable performance loss in virtualized environments with respect to the native one, it is still convenient to execute Hadoop in a small cloud. This could be useful to pre-process data coming from sensors and/or mobile devices before sending them to a central cloud for further analysis.