Container-based microservice architecture for cloud applications

Singh, V.P.; Peddoju, Sateesh K.

doi:10.1109/ccaa.2017.8229914

Cited by 80 publications

(35 citation statements)

References 9 publications

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“…A microservice-based architecture is an architectural style that puts its emphasis on dividing and designing an entire application as a set of loosely coupled, lightweight, independent services [23][24][25]. Each independent service can be independently developed, tested, deployed, monitored, scaled and even implemented in different programming languages [23,24,26]. As the conclusion of [27][28][29], compared to the monolith architecture, a microservice-based architecture addresses the following concerns: Therefore, a microservice-based architecture can be a very convincing architecture style for setting up a workflow environment with the aim of loose coupling independent runnable tasks (e.g., arbitrary execution environments).…”

Section: Microservices-based Architecturementioning

confidence: 99%

Architectural Concept and Evaluation of a Framework for the Efficient Automation of Computational Scientific Workflows: An Energy Systems Analysis Example

et al. 2019

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Scientists and engineers involved in the design of complex system solutions use computational workflows for their evaluations. Along with growing system complexity, the complexity of these workflows also increases. Without integration tools, scientists and engineers are often highly concerned with how to integrate software tools and model sets, which hinders their original research or engineering aims. Therefore, a new framework for streamlining the creation and usage of automated computational workflows is introduced in the present article. It uses state-of-the-art technologies for automation (e.g., container-automation) and coordination (e.g., distributed message oriented middleware), and a microservice-based architecture for novel distributed process execution and coordination. It also supports co-simulations as part of larger workflows including additional auxiliary computational tasks, e.g., forecasting or data transformation. Using Apache NiFi, an easy-to-use web interface is provided to create, run and control workflows without the need to be concerned with the underlying computing infrastructure. Initial framework testing via the implementation of a real-world workflow underpins promising performance in the realms of parallelizability, low overheads and reliable coordination.

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Section: Microservices-based Architecturementioning

confidence: 99%

Architectural Concept and Evaluation of a Framework for the Efficient Automation of Computational Scientific Workflows: An Energy Systems Analysis Example

et al. 2019

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“…In a research that was done by Singh and Peddoju, the performance of a monolithic application is compared to a microservices application that they developed and compared the performance of the two applications, their tests consisted of 2000 threads. Their results exhibited that microservices architecture has a better performance in terms of throughput when it is used for a large number of requests [5].…”

Section: Literature Reviewmentioning

confidence: 99%

A Comparative Review of Microservices and Monolithic Architectures

Al-Debagy

Martinek

2018

2018 IEEE 18th International Symposium on Computational Intelligence and Informatics (CINTI)

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Microservices' architecture is getting attention in the academic community and the industry, and mostly is compared with monolithic architecture. Plenty of the results of these research papers contradict each other regarding the performance of these architectures. Therefore, these two architectures are compared in this paper, and some specific configurations of microservices' applications are evaluated as well in the term of service discovery. Monolithic architecture in concurrency testing showed better performance in throughput by 6% when compared to microservices architecture. The load testing scenario did not present significant difference between the two architectures. Furthermore, a third test comparing microservices applications built with different service discovery technologies such as Consul and Eureka showed that applications with Consul presented better results in terms of throughput.

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“…Similarly, in order to reduce the complexity of typical service‐oriented architectures (SOAs) where considerable amounts of interfaces are necessary to cope with high loads, microservices architectures (MSAs) have been introduced . Microservices architectures add agility and flexibility to traditional SOAs and bring the required speed and efficiency in case of scalability issues …”

Section: Introductionmentioning

confidence: 99%

“…6 Microservices architectures add agility and flexibility to traditional SOAs and bring the required speed and efficiency in case of scalability issues. 7 In such a scenario, edge 8 and fog 9 computing paradigms try to further improve the scalability and reduce the workload on big data processing platforms by using preprocessing applications on edge and fog layers. Conversely, the adoption of MCS introduces a new challenge related to data provenance and information reliability, if compared to traditional wireless sensor networks.…”

mentioning

confidence: 99%

An osmotic computing infrastructure for urban pollution monitoring

2019

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Summary Urban pollution control systems suffer from the presence of fixed stations in a greater number than mobile monitoring devices. Data gathered from such stations provide detailed and reliable information, thanks to equipment quality and effective measuring protocols, but these sampled data are gathered from very limited areas and through discontinuous monitoring campaigns. Fortunately, the spread of technologies for mobility has fostered the development of new approaches like mobile crowdsensing (MCS), increasing the chances of using mobile devices, even personal ones, as suitable sensors for the urban monitoring scenario. Nevertheless, one of the open challenges is the management of integrated heterogeneous data flows, differing in terms of typology, technical specifications (eg, transmission protocols), and semantics. The osmotic computing paradigm aims at creating an abstract level between mobile devices/Internet‐of‐Things devices and a cloud platform, which enables opportunistic filtering and the addition of metadata for improving the data processing flow. This work focuses on the design and development of a middleware that integrates data coming from mobile and Internet‐of‐Things devices specifically deployed in urban contexts using the osmotic computing paradigm. Moreover, a component of the osmotic membrane has been developed for security management.

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Container-based microservice architecture for cloud applications

Cited by 80 publications

References 9 publications

Architectural Concept and Evaluation of a Framework for the Efficient Automation of Computational Scientific Workflows: An Energy Systems Analysis Example

Architectural Concept and Evaluation of a Framework for the Efficient Automation of Computational Scientific Workflows: An Energy Systems Analysis Example

A Comparative Review of Microservices and Monolithic Architectures

An osmotic computing infrastructure for urban pollution monitoring

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