Scalable distributed datastore for real-time cloud computing

Abstract

Recent prognoses about the future of Cloud Computing, Internet of Things and Internet Services show growing demand for an efficient processing of huge amounts of data within strict time limits. First of all, a real-time data store is necessary to fulfill that requirement. One of the most promising architecture that is able to efficiently store large volumes of data in distributed environment is SDDS (Scalable Distributed Data Structure). In this paper we present SDDS LHRT, an architecture that is suitable for real-time cloud applications. We assume that deadlines, defining the data validity, are associated with real time requests. In the data store a real-time scheduling strategy is applied to determine the order of processing the requests. Experimental results shows that our approach significantly improves the storage Quality-of-service in a real-time cloud environment.