MsM: A microservice middleware for smart WSN-based IoT application

Benayache, Ayoub; Bilami, Azeddine; Barkat, Sami; Lorenz, Pascal; Taleb, Hafnaoui

doi:10.1016/j.jnca.2019.06.015

Cited by 34 publications

(15 citation statements)

References 17 publications

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“…4. In conclusion, to guarantee the versatility and robustness of the architecture, three aspects are important to take into account: (i) scalability, microservices can be scaled individually when running a heavy workload just by replicating them on several containers without and not replicating the others underutilized (maximize the performance with minimal cost) [19], [74]; (ii) communication in a microservice, is important establishing simple communication protocol like http, httprest "request/response" (synchronous protocol) or mqtt "publish/subscribe" (asynchronous protocol), depending on needs [67]; (iii) fine-grained microservices, it is fundamental to decompose each service focused on a specific function and of limited influence, according to the established requirements [75]; otherwise, this architecture suffers from a high level of abstraction and coordination among the teams [67], [76].…”

Section: Discussionmentioning

confidence: 99%

“…• Performed post-production: Additional tests (spike tests) are run to ensure that the new version works properly in the production container [16], [59], [62]. • Azure Kubernetes service (AKS) -Kubernetes is used for container orchestration [38], [67], as it allows for initialisation, scaling of container-based jobs, service exposure, and rescheduling of failed jobs and longrunning services [29]. We chose Kubernetes rather than other orchestrators (e.g.…”

Section: Figure 2 Framework For the Automation And Continuous Deploymentioning

confidence: 99%

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Telemonitoring System for Infectious Disease Prediction in Elderly People Based on a Novel Microservice Architecture

et al. 2020

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This article describes the design, development and implementation of a set of microservices based on an architecture that enables detection and assisted clinical diagnosis within the field of infectious diseases of elderly patients, via a telemonitoring system. The proposed system is designed to continuously update a medical database fed with vital signs from biosensor kits applied by nurses to elderly people on a daily basis. The database is hosted in the cloud and is managed by a flexible microservices software architecture. The computational paradigms of the edge and the cloud were used in the implementation of a hybrid cloud architecture in order to support versatile high-performance applications under the microservices pattern for the pre-diagnosis of infectious diseases in elderly patients. The results of an analysis of the usability of the equipment, the performance of the architecture and the service concept show that the proposed e-health system is feasible and innovative. The system components are also selected to give a cost-effective implementation for people living in disadvantaged areas. The proposed e-health system is also suitable for distributed computing, big data and NoSQL structures, thus allowing the immediate application of machine learning and AI algorithms to discover knowledge patterns from the overall population.

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Section: Discussionmentioning

confidence: 99%

Section: Figure 2 Framework For the Automation And Continuous Deploymentioning

confidence: 99%

Telemonitoring System for Infectious Disease Prediction in Elderly People Based on a Novel Microservice Architecture

et al. 2020

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“…With the increasing scale of the IoT systems, development of IoT application to be flexibility, lightweight and loose coupling is important to enable extensibility and maintainability, and the microservice architecture is a key to meet the demand [55]- [59]. Benayache et al [60] proposed a middleware in IoT networks for enabling service interconnectivity and availability over heterogeneous networks based on accessing different APIs and communication protocols. Fernandez et al [61] proposed an orchestration of IoT slices through providing microservices from edge and cloud environment.…”

Section: Related Workmentioning

confidence: 99%

Secure Edge Computing Management Based on Independent Microservices Providers for Gateway-Centric IoT Networks

Jin

You

et al. 2020

IEEE Access

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Edge computing is an emerging computing paradigm that distributes the computational capability to the edge of networks for enabling the computation near to the environment where the sensors and actuators are deployed. Therefore, from the network edge, heterogeneous solutions can be provided to the Internet based on sufficient computing ability. Nevertheless, computing and networking resources are constrained for devices in the network edge. Providing secure services from edge computing is a challenge based on constrained resources. In this paper, we propose a secure edge computing to provide management of device, data, user and additional services based on deploying independent microservices providers with a security gateway on an edge gateway. The edge gateway is the hub of a local network where multiple IoT devices are deployed to interact with the physical environment for sensing and actuating. The gateway provides the management functionalities through microservices based on multiple independent server modules. Each gateway-centric local network has a standalone management service based on the gateway. For providing secure edge computing services through the edge gateway, a security gateway is deployed on the proposed edge gateway to provide Representational State Transfer Application Programming Interfaces to expose the security services to the Internet instead of microservices from management modules. Moreover, a client support gateway is deployed in the edge gateway to provide services of User Interface and access forwarding based on web sessions to support user authentication and authorization with the security gateway. Based on the proposed edge gateway including client support and security gateway, IoT clients and IoT devices are enabled to communicate for providing secure edge services of access and visualization to users.

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“…According to authors [21] this paper is the first that deals with the integration of WSNs in the IoT using microservice approach through neural network, together with the cloud computing approach. The proposed model allows the design and the development of an extensible, distributed, and adaptable middleware system for lightweight WSN device integration.…”

Section: Microservice Based Applications In Iot and Wsn Systemsmentioning

confidence: 99%

Approach in the development of lightweight microservice architecture for small data center monitoring system

Malić¹,

Dobrilovic²,

Malić³

et al. 2020

IJEEC

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In the past decade there is a significant trend of implementing IoT technologies and standards in different industries. This trend brings cost reductions to the companies and other benefits as well. One of the main benefits is real-time and uniform data collection. The data are transferred using diverse communication protocols, from the sensor nodes to the centralized application. So far, current approaches in developing applications are not proved itself to be efficient enough in scenarios when a significant amount of data needs to be stored and analyzed. The focus of this paper is on development of software architecture suitable for usage in Internet of Things (IoT) systems where the larger amount of data can be processed in real-time. The software architecture is developed in order to support the sensor network for monitoring the small data center and it is based on microservices. Besides the system and its architecture, this paper presents the method of analysis of system performances in real-time environment. The proposal for lightweight microservice architecture, presented in this paper, is developed with .NET Core and RabbitMQ, with the utilization of MongoDB and SQLite databases systems for storing data collected with IoT devices. In this paper, the system evaluation and research results in different stress scenarios are also presented. Because of its complexity, only the most significant segments of architecture will be presented in this paper. The proposed solution showed that proposed lightweight architecture based on microservices could deal with the larger amount of sensor data in the case of using MongoDB. On the other hand, the usage of SQLite database is not recommended due to the lower performances and test results.

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MsM: A microservice middleware for smart WSN-based IoT application

Cited by 34 publications

References 17 publications

Telemonitoring System for Infectious Disease Prediction in Elderly People Based on a Novel Microservice Architecture

Telemonitoring System for Infectious Disease Prediction in Elderly People Based on a Novel Microservice Architecture

Secure Edge Computing Management Based on Independent Microservices Providers for Gateway-Centric IoT Networks

Approach in the development of lightweight microservice architecture for small data center monitoring system

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