DOCKERANALYZER : Towards Fine Grained Resource Elasticity for Microservices-Based Applications Deployed with Docker

Fourati, Mohamed Hedi; Marzouk, Soumaya; Drira, Khalil; Jmaïel, Mohamed

doi:10.1109/pdcat46702.2019.00049

Cited by 6 publications

(2 citation statements)

References 9 publications

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“…The recent developments in artificial intelligence and machine learning contribute to building general-purpose autoscalers [Imdoukh et al 2020]. Machine learning techniques are most commonly related to proactive scaling strategy, but they are also employed in the reactive strategy scope as highlighted in [Fourati et al 2019] that propose the adoption of an anomaly detection system to support scaling decisions for both vertical and horizontal scenarios.…”

Section: Adoption Of Machine Learningmentioning

confidence: 99%

State of the Art on Microservices Autoscaling: An Overview

Nunes¹,

Bianchi²,

Iwasaki³

et al. 2021

Anais Do XLVIII Seminário Integrado De Software E Hardware (SEMISH 2021)

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The adoption of microservices architecture has taken on great pro-portions due to its benefits and popularization of containers driven tools, such as Kubernetes and Docker. Besides, the development of microservice-based applications is a complex task, specially because they can be composed of multiple heterogeneous parts. In particular, one of the main challenges is how to conduct the microservices autoscaling (i.e., adding or removing resources on demand), while still avoiding resource waste, such as CPU and memory. This paper presents the state of the art of approaches to solve the problem of micro services autoscaling, the main characteristics to be considered as well as the important future directions that need to be still investigated.

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Section: Adoption Of Machine Learningmentioning

confidence: 99%

State of the Art on Microservices Autoscaling: An Overview

Nunes¹,

Bianchi²,

Iwasaki³

et al. 2021

Anais Do XLVIII Seminário Integrado De Software E Hardware (SEMISH 2021)

View full text Add to dashboard Cite

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“…Today, loT applications are often deployed on the Cloud to utilize the advantage of this environment such as ondemand measurement services, wide-area network capability as well as radically supported resource elasticity. Many solutions, including DOCKERANALYZER [20], Proliot [21], BDAaaS [22] and ACD [23] have attempted to provide scalability for components of IoT applications. However, only a few elasticity solutions for MQTT brokers have been proposed, including Broker [24], E-SilboPS [25].…”

Section: Elastic Mqtt Brokermentioning

confidence: 99%

Elasticity for MQTT Brokers in IoT Applications

Pham

2021

MIC ICT Research Journal

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Many domains of human life are more and moreimpacted by applications of the Internet of Things (i.e., IoT).The embedded devices produce masses of data day after dayrequiring a strong network infrastructure. The inclusion ofmessaging protocols like MQTT is important to ensure as fewerrors as possible in sending millions of IoT messages. Thisprotocol is a great component of the IoT universe due to itslightweight design and low power consumption. DistributedMQTT systems are typically needed in actual applicationenvironments because centralized MQTT methods cannotaccommodate a massive volume of data. Although beingscalable decentralized MQTT systems, they are not suited totraffic workload variability. IoT service providers may incurexpense because the computing resources are overestimated.This points to the need for a new approach to adapt workloadfluctuation. Through proposing a modular MQTT framework,this article provides such an elasticity approach. In order toguarantee elasticity of MQTT server cluster while maintainingintact IoT implementation, the MQTT framework used offthe-shelf components. The elasticity feature of our frameworkis verified by various experiments.

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Multi-level just-enough elasticity for MQTT brokers of Internet of Things applications

Pham

Nguyen

2022

Cluster Comput

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DOCKERANALYZER : Towards Fine Grained Resource Elasticity for Microservices-Based Applications Deployed with Docker

Cited by 6 publications

References 9 publications

State of the Art on Microservices Autoscaling: An Overview

State of the Art on Microservices Autoscaling: An Overview

Elasticity for MQTT Brokers in IoT Applications

Multi-level just-enough elasticity for MQTT brokers of Internet of Things applications

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