Abstract:

The demand of real-time spatial data has been increasing recently. Nowadays, we are talking about a real-time spatial Big Data that process a large amount of heterogeneous data. In these applications, it is desirable to execute transactions within their deadlines using a real-time spatial data. But the realtime spatial Big Data can be overloaded and many transactions may miss their deadlines, or real-time spatial data can be violated. To address these problems, we proposed a new architecture called FCSA-RTSBD [8]. The main objectives of this architecture are the following: take in account the heterogeneity of data, guarantee the data freshness, enhance the deadline miss ratio even in the presence of conflicts and finally satisfy the requirements of users by the improving of the quality of service (QoS). In this paper, a simulation study is shown to prove that our architecture can achieve a significant performance improvement, in terms of deadline miss ratio and data freshness, compared to other architectures.