QoS management in real-time spatial big data using a feedback control scheduling. (2018)

• Record Type: Journal Article
• Authors: Hamdi, Sana; Bouazizi, Emna; Faiz, Sami
• Is Part Of: International journal of intelligent information and database systems. Volume 11:Number 4(2018)
• Page Start: 266
• Page End: 295
• Publication Date: 2018
• Subjects: heterogeneous real-time geospatial data -- update transaction -- user transaction -- feedback control scheduling -- nested transaction -- speculative concurrency control -- imprecise computation -- quality of service -- QoS -- simulation; Database management -- Computer programs -- Periodicals; Information retrieval -- Computer programs -- Periodicals; Information storage and retrieval systems -- Computer programs -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligent agents (Computer software) -- Periodicals; 006.33
• Languages: English
• ISSNs: 1751-5858

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.