Replication in Distributed Systems and its Improvements

2011

The necessity of ever-increasing use of distributed data in computer networks is obvious for all. One technique that is performed on the distributed data for increasing of efficiency and reliablity is data rplication. In this paper, after introducing this technique and its advantages, we will examine some dynamic data replication. We will examine their characteristies for some overus scenario and the we will propose some suggestion for their improvement.

Database and Expert Systems …, 1996

In this paper we investigate the performance issues of data replication in a loosely coupled distributed database system, where a set of database servers are connected via a network. A database replication scheme, Replication with Divergence, which allows some degree of divergence between the primary and the secondary copies of the same data object, is compared to other two schemes that, respectively, disallows replication and maintains all replicated copies consistent at all times. The impact of some tunable factors, such as cache size and the update propagation probability, on the performance of Replication with Divergence is also investigated. These results shed light on the performance issues that were not addressed in previous studies on replication of distributed database systems.

Proceedings of the sixteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems - PODS '97, 1997

The issue of data replication is considered in the context of a restricted system model motivated by certain distributed data-warehousing applications. A new replica management protocol is defined for this model in which gIobaI serializability is ensured, while message overhead and deadlock frequency are less than in previously published work. The advantages of the protocol arise from its use of a lazy approach to update of secondary copies of replicated data and the use of a new concept, virtual sites, to reduce the potential for conflict among global transactions.

Proceedings 20th IEEE International Conference on Distributed Computing Systems, 2000

Replication is an area of interest to both distributed systems and databases. The solutions developed from these two perspectives are conceptually similar but differ in many aspects: model, assumptions, mechanisms, guarantees provided, and implementation. In this paper, we provide an abstract and "neutral" framework to compare replication techniques from both communities in spite of the many subtle differences. The framework has been designed to emphasize the role played by different mechanisms and to facilitate comparisons. With this, it is possible to get a functional comparison of many ideas that is valuable for both didactic and practical purposes. The paper describes the replication techniques used in both communities, compares them, and points out ways in which they can be integrated to arrive to better, more robust replication protocols.

Data grid is a distributed collection of storage and computational resources that are not bounded within a geophysical location. It is a fast growing area of research and providing efficient data access and maximum data availability is a challenging task. To achieve this task, data is replicated to different sites. A number of data replication techniques have been presented for data grids. All replication techniques address some attributes like fault tolerance, scalability, improved bandwidth consumption, performance, storage consumption, data access time etc. In this paper, different issues involved in data replication are identified and different replication techniques are studied to find out which attributes are addressed in a given technique and which are ignored. A tabular representation of all those parameters is presented to facilitate the future comparison of dynamic replication techniques. The paper also includes some discussion about future work in this direction by identifying some open research problems. .pk (A. Daud).

2002

Replication maintains replicas (copies) of critical data on multiple computers and allows access to any one of them. It is the critical enabling technology of distributed services, improving both their performance and availability. Availability is improved by allowing access to the data, even when some of the replicas or network links are unavailable. Performance is improved in two ways. First, users can access nearby replicas and avoid expensive remote network access and reduce latency.

Ensuring data consistency during replication is a critical research issue in a distributed system. Guaranteeing that data replicacontinues to maintain its original status and its consistency while being copied into the distributed system is still an emerging challenge. As a result of this there is an increase in risk operational disruptions in distributed databases, financial losses in database distribution, legal issues in data consistency, passivity penalties and reputational damages to the database. Maintaining the accuracy and consistency of data over its entire life-cycle is another challenge in a distributed computing environment, this prompts intruders to temper and modify data in an invisible manner without permission of its true user thereby leading to data breach and inconsistency. The new model uses Hadoop model in connection with database to create large space memory location that handles all the bulk of unstructured data in the distributed computing environment. The evaluation parameter was taken based on the efficiency of the processing speed, data consistency, memory space and data integrity. The efficiency was recorded in percentages (%).It was observed that the proposed model performed better and achieved more data consistency in the distributed database environment as the efficiency level generateda75 % accuracy.

2006

High availability of information in medium and large-sized enterprises may naturally benefit from a wide-area replication of data. We feature and discuss an ongoing development of replication architecture innovations. They boost the availability of business data in distributed information systems.

2006

The availability of information systems benefits from distributed replication. Different applications and users require different degrees of data availability, consistency and integrity. The latter are perceived as competing objectives that need to be reconciled by appropriate replication strategies. We outline work in progress on a replication architecture for distributed information systems. It simultaneously maintains several protocols, so that it can be re-configured on the fly to the actual needs of availability, consistency and integrity of possibly simultaneous applications and users

The distribution of information systems on multiple nodes ensures maximum availability of resources and business continuity in case of disasters by using data replication. There are two basic parameters to select when designing a replication strategy: "where" and "when" the updates are propagated. In this paper I presented the advantages and disadvantages of data replication. In addition, we analyze the available methods and strategies of data replication depending on needs, for improving performance and increasing data availability.