ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3/W5, 243-248, 2015
https://doi.org/10.5194/isprsannals-II-3-W5-243-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
19 Aug 2015
QOS MANAGEMENT IN REAL-TIME SPATIAL BIG DATA USING FEEDBACK CONTROL SCHEDULING
S. Hamdi1, E. Bouazizi2, and S. Faiz3 1Tunisia Polytechnic School, BP 2078 La Marsa, University of Carthage, Tunisia
2MIRACL Laboratory, Higher Institute of Computer Science and Multimedia, Sfax University, Tunisia
3LTSIRS Laboratory, BP 37 Le Belvedere 1002, Tunis, Tunisia
Keywords: Geographic Information System, Real-Time Spatial Big Data, Heterogeneous Real-Time Geospatial Data, Transaction, Feedback Control Scheduling, Quality of Service Abstract. Geographic Information System (GIS) is a computer system designed to capture, store, manipulate, analyze, manage, and present all types of spatial data. Spatial data, whether captured through remote sensors or large scale simulations has always been big and heterogenous. The issue of real-time and heterogeneity have been extremely important for taking effective decision. Thus, heterogeneous real-time spatial data management has become a very active research domain. Existing research has principally focused on querying of real-time spatial data and their updates. But the unpredictability of access to data maintain the behavior of the real-time GIS unstable. In this paper, we propose the use of the real-time Spatial Big Data and we define a new architecture called FCSA-RTSBD (Feedback Control Scheduling Architecture for Real-Time Spatial Big Data). 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 unpredictable workloads and finally satisfy the requirements of users by the improving of the quality of service (QoS).
Conference paper (PDF, 814 KB)


Citation: Hamdi, S., Bouazizi, E., and Faiz, S.: QOS MANAGEMENT IN REAL-TIME SPATIAL BIG DATA USING FEEDBACK CONTROL SCHEDULING, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3/W5, 243-248, https://doi.org/10.5194/isprsannals-II-3-W5-243-2015, 2015.

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