This paper presents the Fault-Tolerant Real-Time Cloud (FTRTC) project that aims to design cloud computing infrastructures capable of hosting highly reliable and real-time applications. These applications are characterized by strict timing and reliability constraints, as well as critical failure scenarios. For instance, such requirements are commonly found in the context of Industry 4.0. We present a formalization of the problem of designing real-time cloud applications supporting an adjustable level of fault tolerance throughout their distributed execution in a cloud infrastructure. The contributions presented in this paper indicate important research directions when building cloud infrastructures able to supporting ultra-reliable real-time applications.
In recent years, the demand for cloud-based high-performance computing applications and services has grown in order to sustain the computational and statistical challenges of big-data analytics scenarios. In this context, there is a growing need for reliable large-scale NoSQL data stores capable of eciently serving mixed high-performance and interactive cloud workloads. This paper deals with the problem of designing such NoSQL database service: to this purpose, a set of modications to the popular MongoDB software are presented. The modied MongoDB lets clients submit individual requests or even carry out whole sessions at dierent priority levels, so that the higher-priority requests are served with shorter response times that exhibit less variance, with respect to lower-priority requests. Experimental results carried out on two big multi-core servers using synthetic workload scenarios demonstrate the eectiveness of the proposed approach in providing dierentiated performance levels, highlighting what trade-os are available between maximum achievable throughput for the platform, and the response-time reduction for higher-priority requests.
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