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Abstract-In today's increasingly interconnected world, the deployment of an Intrusion Detection System (IDS) is becoming very important for securing embedded systems from viruses, worms, attacks, etc. But IDSs face many challenges like computational resources and ubiquitous threats. Many of these challenges can be resolved by running the IDS in a cluster to allow tasks to be parallelly executed. In this paper, we propose to secure embedded systems by using a cluster of embedded cards that can run multiple instances of an IDS in a parallel way. This proposition is now possible with the availability of new lowpower single-board computers (Raspberry Pi, BeagleBoard, Cubieboard, Galileo, etc.). To test the feasibility of our proposed architecture, we run two instances of the Bro IDS on two Raspberry Pi. The results show that we can effectively run multiple instances of an IDS in a parallel way on a cluster of new low-power single-board computers to secure embedded systems.

Abstract-Recently, HPC (High Performance Computing) systems have gone from supercomputers to clusters. The clusters are used in all tasks that require very high computing power such as weather forecasting, climate research, molecular modeling, physical simulations, cryptanalysis, etc. The use of clusters is increasingly important in the scientific community, where the need for high performance computing (HPC) is still growing. In this paper, we propose an improvement of a mobile robots system control by using an MPI (Message Passing Interface) cluster. This cluster will launch, manipulate and process data from multiple robots simultaneously.