Axis2-based Replication Middleware forWeb Services

Osrael, Johannes; Froihofer, Lorenz; Weghofer, M.; Goeschka, Karl M.

doi:10.1109/icws.2007.57

Cited by 10 publications

(15 citation statements)

References 21 publications

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“…Once all replicas process the requests in the same order, the consistence among them is preserved. The authors of [6] and [7] propose solutions based on passive replication. In these solutions, client requests are sent to a unique primary replica, which propagates the updates to the other replicas.…”

Section: Related Workmentioning

confidence: 99%

Lab4WS: A Testbed for Web Services

Nakai

Madeira

Buzato

2009

2009 2nd International Conference on Computer Science and Its Applications

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Abstract-Web services are increasingly being deployed in clusters located at geographically distributed datacenters linked via the Internet. Ideally, before the actual deployment of such a complex service, engineers would like to have a way to quantitatively analyze aspects such as performance, availability, and the load balancing achieved by the different solutions available. In this paper we present the Lab4WS, a testbed designed to reduce the difficulties associated with the evaluation of LAN and/or WAN deployed web services. The key features of Lab4WS are illustrated by using it to compare four WAN load balancing mechanisms (DNS-based, server-based, dispatcher-based, and client-based).

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Section: Related Workmentioning

confidence: 99%

Lab4WS: A Testbed for Web Services

Nakai

Madeira

Buzato

2009

2009 2nd International Conference on Computer Science and Its Applications

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“…Traditional database replication techniques as provided by both commercial and open source database management system (such as Oracle, IBM DB2, Microsoft SQL Server, PostgreSQL, or MySQL) can be applied [3].…”

Section: Introductionmentioning

confidence: 99%

Replication of Data in Database Systems for Backup and Failover – An Overview

Singh¹,

Sandhu²,

Bhatti³

2013

IJCCE

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Abstract-The production database are transactions intensive transactions can be insert, update on the tables, failover is the replica of the production server, if there is any change we have to implement on the production and it will be automatically implemented on failover or standby database. Now a days the data on the production server is increasing and we need extra storage space on production server to keep data and this is same required on the failover. To generate reports from that data will increase load on the production server and can affect the performance of the server. There are also some threats which can cause loss of data from which we have to protect our database like Hardware failure, loss of machine. Replication is one of the methods for Backup of the running database and its immediate failover during failure. This paper represents some parts for the replication techniques, failover, and transaction states.

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“…Ye and Shen [45] propose a middleware using active replication as well, but it relies on communication history based one the abcast protocol. [31] present a middleware based on a variation of passive replication, which is rather close to active replication. All of the above approaches are either not intend to consider scalability and consistency in replication or are strongly bound to a specific standard (web service), as a result they cannot satisfy consistency requirements at the application level and scalability tends to be limited.…”

Section: Replication and Consistency In Service-oriented Systemsmentioning

confidence: 99%

“…Generally, there are two form of protocols by which consistency can be guaranteed: (1) two-phase protocol [16,39,41] where the first phase runs unordered but with reliable broadcast, out-of-order operations are rolled back when found. (2) Apply atomic broadcast (abcast) protocol over reliable communication [15,17,31,36,45], which prevents inconsistent ordering from happening. In this work, we are specially interested on the later category.…”

Section: Cc1mentioning

confidence: 99%

“…Therefore in most cases requirements for consistency and scalability varies depending on the services needed. Nevertheless, existing service replication approaches and middlewares [16,25,31,36,39,41,45,48] force engineers to choose between a rather restricted consistency management in a cloud environment with the replication of services for scalability. Suppose the business does not require restricted consistency.…”

Section: Introductionmentioning

confidence: 99%

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Scalable service-oriented replication with flexible consistency guarantee in the cloud

Chen

Bahsoon

Tawil

2014

Information Sciences

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a b s t r a c tReplication techniques are widely applied in and for cloud to improve scalability and availability. In such context, the well-understood problem is how to guarantee consistency amongst different replicas and govern the trade-off between consistency and scalability requirements. Such requirements are often related to specific services and can vary considerably in the cloud. However, a major drawback of existing service-oriented replication approaches is that they only allow either restricted consistency or none at all. Consequently, service-oriented systems based on such replication techniques may violate consistency requirements or not scale well. In this paper, we present a Scalable Service Oriented Replication (SSOR) solution, a middleware that is capable of satisfying applications' consistency requirements when replicating cloud-based services. We introduce new formalism for describing services in service-oriented replication. We propose the notion of consistency regions and relevant service oriented requirements policies, by which trading between consistency and scalability requirements can be handled within regions. We solve the associated sub-problem of atomic broadcasting by introducing a Multi-fixed Sequencers Protocol (MSP), which is a requirements aware variation of the traditional fixed sequencer approach. We also present a Region-based Election Protocol (REP) that elastically balances the workload amongst sequencers. Finally, we experimentally evaluate our approach under different loads, to show that the proposed approach achieves better scalability with more flexible consistency constraints when compared with the state-of-the-art replication technique.

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Axis2-based Replication Middleware forWeb Services

Cited by 10 publications

References 21 publications

Lab4WS: A Testbed for Web Services

Lab4WS: A Testbed for Web Services

Replication of Data in Database Systems for Backup and Failover – An Overview

Scalable service-oriented replication with flexible consistency guarantee in the cloud

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