Evaluation of a Group Communication Middleware for Clustered J2EE Application Servers

Abdellatif, Takoua; Cecchet, Emmanuel; Lachaize, Renaud

doi:10.1007/978-3-540-30469-2_46

Cited by 16 publications

(10 citation statements)

References 8 publications

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“…Work focused on JGroups [1] has shown that the performance the TCP-based configuration is superior to the UDP-based configuration. This is attributed to poor performance of the network switch with multicast.…”

Section: Discussionmentioning

confidence: 99%

Evaluating Throughput Stability of Protocols for Distributed Middleware

Carvalho

Oliveira

Pereira

2009

On the Move to Meaningful Internet Systems: OTM 2009

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Communication of large data volumes is a core functionality of distributed systems middleware, namely, for interconnecting components, for distributed computation and for fault tolerance. This common functionality is however achieved in different middleware platforms with various combinations of operating system and application level protocols, both standardized and ad hoc, and including implementations on managed runtime environments such as Java. In this paper, in contrast with most previous work that focus on performance, we point out that architectural and implementation decisions have an impact in throughput stability when the system is heavily loaded, precisely when such stability is most important. In detail, we present an experimental evaluation of several communication protocol components under stress conditions and conclude on the relative merits of several architectural options.

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Section: Discussionmentioning

confidence: 99%

Evaluating Throughput Stability of Protocols for Distributed Middleware

Carvalho

Oliveira

Pereira

2009

On the Move to Meaningful Internet Systems: OTM 2009

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“…Network latency and unreliability of long distance links are big hurdles in the extension of multi-master replication to WAN [130]. The bandwidth availability is increasing, but the physical constraints on latency over worldwide links limits the evolution of latency.…”

Section: Conclusion Open Research Issues and Future Directionsmentioning

confidence: 99%

Performance analysis of data intensive cloud systems based on data management and replication: a survey

Malik

Khan

Ewen

et al. 2015

Distrib Parallel Databases

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As we delve deeper into the 'Digital Age', we witness an explosive growth in the volume, velocity, and variety of the data available on the Internet. For example, in 2012 about 2.5 quintillion bytes of data was created on a daily basis that originated from myriad of sources and applications including mobiledevices, sensors, individual 123 Distrib Parallel Databases archives, social networks, Internet of Things, enterprises, cameras, software logs, etc. Such 'Data Explosions' has led to one of the most challenging research issues of the current Information and Communication Technology era: how to optimally manage (e.g., store, replicated, filter, and the like) such large amount of data and identify new ways to analyze large amounts of data for unlocking information. It is clear that such large data streams cannot be managed by setting up on-premises enterprise database systems as it leads to a large up-front cost in buying and administering the hardware and software systems. Therefore, next generation data management systems must be deployed on cloud. The cloud computing paradigm provides scalable and elastic resources, such as data and services accessible over the Internet Every Cloud Service 123 Distrib Parallel Databases (data replication and management) to provide different QoS attributes is deliberated. Furthermore, the performance advantages and disadvantages of data replication and management approaches in the cloud computing environments are analyzed. Open issues and future challenges related to data consistency, scalability, load balancing, processing and placement are also reported.

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“…Recently emerged strategies, such as satellite databases [29], offer a migration path for such cases. In the case of an e-commerce application, the main legacy database is 1 By middleware we mean the software layer that lies between an application and the database replicas.…”

Section: Improving Performance Via Replicationmentioning

confidence: 99%

“…Motivated by these findings, we draft possible agendas for academic and industrial research. This paper concentrates exclusively on middleware-based 1 replication for OLTP workloads. The prevalent architecture is shared-nothing, where cluster nodes use local disks to store data.…”

Section: Introductionmentioning

confidence: 99%

Middleware-based database replication

Cecchet

Candea²,

Ailamaki³

2008

Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data

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The need for high availability and performance in data management systems has been fueling a long running interest in database replication from both academia and industry. However, academic groups often attack replication problems in isolation, overlooking the need for completeness in their solutions, while commercial teams take a holistic approach that often misses opportunities for fundamental innovation. This has created over time a gap between academic research and industrial practice. This paper aims to characterize the gap along three axes: performance, availability, and administration. We build on our own experience developing and deploying replication systems in commercial and academic settings, as well as on a large body of prior related work. We sift through representative examples from the last decade of open-source, academic, and commercial database replication systems and combine this material with case studies from real systems deployed at Fortune 500 customers. We propose two agendas, one for academic research and one for industrial R&D, which we believe can bridge the gap within 5-10 years. This way, we hope to both motivate and help researchers in making the theory and practice of middleware-based database replication more relevant to each other.

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Evaluation of a Group Communication Middleware for Clustered J2EE Application Servers

Cited by 16 publications

References 8 publications

Evaluating Throughput Stability of Protocols for Distributed Middleware

Evaluating Throughput Stability of Protocols for Distributed Middleware

Performance analysis of data intensive cloud systems based on data management and replication: a survey

Middleware-based database replication

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