An alarm management framework for automated network fault identification

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.

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QoS Management in Distributed Real-Time Databases

In many distributed real-time systems, certain critical data need to be replicated to achieve fault-tolerance and improved performance. Schedulers for such distributed real-time systems must satisfy timing constraints of transactions and preserve data consistency. In this paper we presents a replication control algorithm, which integrates real-time scheduling and replication control to achieve the desired level of fault-tolerance. The algorithm adopts a majority consensus scheme for replication control and employs epsilon-serializability, a correctness criterion which is less stringent than conventional one-copy serializability. The performance of the algorithm is compared with that of a real-time token-based algorithm.

Replication control for fault-tolerance in distributed real-time database systems

The online automatic monitoring is a hot topic in the real-time application. Generally, the real-time data could come from different sources with different formats, resulting in difficulty in data parsing. To solve this problem, this paper proposes a Universal Heterogeneous Data Integration Standard (UHDIS) associated with a Parsing Algorithm to data of UHDIS in real time. The UHDIS could reduce the redundant information, leading high compression ability and transmission efficiency. For the parsing algorithm, we propose to parse data by utilizing template, which could map the integrated data of UHDIS to the desired tables in database. Based on this structure, our parsing algorithm could be adapted to different kinds of integrated real time data by adding new templates instead of changing the algorithm, thus has a good universality. We conduct experiments on data from the on-line environment monitoring system. As the experiments show, our approach has a good performance.

A Universal Heterogeneous Data Integration Standard and Parse Algorithm in Real-Time Database

Many real time database systems are now being used in safety critical applications, in which human lives or expensive machinery may be at stake. Transactions in real time databases should be scheduled considering both data consistency and timing constraints. In addition, a real time database must adapt to changes in the operating environment and guarantee the completion of critical tasks. The effects of scheduling decisions and concurrency control mechanisms for real time database systems have typically been demonstrated in a simulated environment. We present a functional real time database server called DRDB, which provides an operational platform for research in distributed real time database issues.

R.C. Beckinger

Papers

DRDB: a distributed real-time database server for high-assurance time-critical applications