Typically, a real-time system consists of a a controlling system and a controlled system. In an automated factory, the controlled system is the factory floor with its robots, assembling stations, and the assembled parts, while the controlling system is the computer and human interfaces that manage and coordinate the activities on the factory

There is a growing need for real-time data services in distributed environments. Providing quality-of-service guarantees for data services in a distributed environment is a challenging task. The presence of multiple sites in distributed environments raises issues that are not present in centralized systems. The transaction workloads in distributed real-time databases may not be balanced and the transaction access patterns may be time-varying and skewed. Data replication is an effective method to help database systems meet the stringent temporal requirements of real-time applications. We have designed an algorithm that provides quality-of-service guarantees for data services in distributed real-time databases with full replication of temporal data. The algorithm consists of heuristic feedback-based local controllers and global load balancers (GLB) working at each site. The local controller controls the admission process of incoming transactions. The global load balancers collect the performance data from other nodes and balance the system-wide workload. The simulation results show that the new algorithm successfully balances the workloads in distributed real-time databases and provides tight transaction miss ratio guarantees under various transaction workloads. Index Terms Quality of Service, real-time databases, replication, distributed real-time systems, feedback control, load balance I.

1 Introduction Since the past decade, browsers have become the access point to complex transactional applications. Following the approach widely adopted in the industrial world, these applications are typically supported by multi-tier systems, e.g. three-tier systems, where middle-tier Web/application servers have

Many real-time applications need data services in distributed environments. However, providing such data services is a challenging task due to long remote data accessing delays and stringent time requirements of real-time transactions. Replication can help distributed real-time database systems meet the stringent time requirements of application transactions. In this paper, we present two dynamic replication control algorithms designed for medium and large scale distributed realtime database systems. With the data needs information from incoming transactions, our algorithms dynamically determine where and how often the replicas are replicated. In our algorithms, the data replicas are dynamically created upon the requests by the incoming transactions and their update frequencies are determined by the data freshness requirements of these transactions. A detailed simulation study shows that our algorithms can greatly improve the system performance compared to the systems without replication or systems with simple replication strategies such as full replication.