Intelligent Replication for Distributed Active
Real-Time Databases Systems
Rashed Salem1,
Safa'a Saleh2, and Hattem Abdul-Kader1
1Information Systems
Department, Menoufia University, Egypt
2Information Systems Department, Taibah University, KSA
Abstract: Recently,
the demand for real-time database is increasing. Most real-time systems are
inherently distributed in nature and need to handle data in a timely fashion. Obtaining
data from remote sites may take long time making the temporal data invalid.
This results in a large number of tardy transactions with their catastrophic
effect. Replication is one solution of this problem, as it allows transactions
to access temporal data locally. This helps transactions to meet their time
requirements which require predictable resource usage. To improve
predictability, Distributed Active Real-time Database System (DeeDS) prototype is
introduced to avoid the delay which results from disk access, network
communications and distributed commit processing. DeeDS advises to use
In-memory database, fully replication and local transaction committing, but
full replication consumes the system resources causing a scalability problem.
In this work, we introduce Intelligent Replication In DeeDS (IReIDe) as a new
replication protocol that supports the replication for DeeDS and faces the
scalability problem using intelligent clustering technique. The results show
the ability of IReIDe to reduce the consumed system resources and maintain
scalability.
Keyword: Replication, real-time, DRTDBS, DeeDS, clustering.
Received February 17, 2015; accepted October 7, 2015