Title: QoS management in real-time spatial big data using a feedback control scheduling

Authors: Sana Hamdi; Emna Bouazizi; Sami Faiz

Addresses: Tunisia Polytechnic School, University of Carthage, BP 2078 La Marsa, Tunisia ' MIRACL Laboratory, University of Sfax, BP 1088 Sfax 3018, Tunisia ' LTSIRS Laboratory, BP 37 Le Belvedere 1002, Tunis, Tunisia

Abstract: Heterogeneous real-time spatial data management is a very active research domain nowadays. We are talking about a real-time spatial big data that process a large amount of heterogeneous data accessed simultaneously by two types of transactions update transactions and user transactions. In these applications, it is desirable to execute transactions within their deadlines using a real-time spatial data. But the real-time 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, as a first contribution, a new architecture called feedback control scheduling architecture for real-time spatial big data (FCSA-RTSBD) (Hamdi et al., 2015). Then, we propose, as a second contribution, two-shadow speculative concurrency control (SCC-2S) with priority and imprecise computation (SCC-2S-P-IC). Finally, a simulation study is shown to prove that our contributions can achieve a significant performance improvement using the TPC-DS (TPC, 2014) benchmark.

Keywords: heterogeneous real-time geospatial data; update transaction; user transaction; feedback control scheduling; nested transaction; speculative concurrency control; imprecise computation; quality of service; QoS; simulation.

DOI: 10.1504/IJIIDS.2018.096590

International Journal of Intelligent Information and Database Systems, 2018 Vol.11 No.4, pp.266 - 295

Received: 25 Jul 2017
Accepted: 09 Feb 2018
Published online: 06 Dec 2018 *

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