Architectural ML Framework for IoT Services Delivery Based on Microservices

Dineva, Kristina; Atanasova, Tatiana

doi:10.1007/978-3-030-66471-8_53

Cited by 7 publications

(3 citation statements)

References 8 publications

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“…A previous study [22] used microservices and cloud paradigms to implement a highly scalable livestock IoT platform. The microservice architecture of a distributed IoT system discussed in detail in [23] consists of a group of microservices that communicate with each other synchronously or asynchronously. Another study [24] involved the design of a sensor network based on a microkernel operating system.…”

Section: Introductionmentioning

confidence: 99%

An Internet of Things-Based Cluster System for Monitoring Lactating Sows’ Feed and Water Intake

He,

Zeng,

Liu

et al. 2024

Agriculture

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Acquiring real-time feeding information for monitoring lactating sows and their feeding requirements is a challenging task. Real-time data represent an important input for numerous tasks, such as disease monitoring, nutritional regulation, and feeding modeling. However, concurrently monitoring large numbers of sows and processing the real-time information for modeling is challenging using existing platforms. In this paper, we describe the design and development of a system that monitors and processes sows’ feed and water consumption in real time. The system was custom-developed using open-source networking technologies. The system consists of three components: an electronic sow feeder connected to a central controller via a CAN network, an MQTT service cluster, and a data processing program. The MQTT service cluster uses Netty to develop a single service node, and it uses Zookeeper and Redis to complete node registration, discovery, and scheduling. The data processing program is based on Spark and Flink. We conducted comparative testing of three common codecs (Java Serializer, Marshalling, and Protostuff) to further speed up data transmission. The results of the experiment show that, with three service nodes, the system can concurrently monitor up to 20,000 sows. Moreover, the system achieves optimal performance when monitoring 10,000 sows at the same time, with a TPS of 6399 pcs/s and an RT of 643 ms.

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Section: Introductionmentioning

confidence: 99%

An Internet of Things-Based Cluster System for Monitoring Lactating Sows’ Feed and Water Intake

He,

Zeng,

Liu

et al. 2024

Agriculture

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“…With the development of mobile Internet and Internet plus, the original SOA architecture has encountered four problems: lack of effective service governance, mixed service assets, and no effective service management and control means; The business support response is slow, and the system is too big to fail, unable to achieve real-time updates and modular release; Poor system availability, unable to achieve 7 × 24 hour uninterrupted service; Innovative business is di cult to support, especially innovative business with Internet characteristics. Based on this, developers propose an SOA architecture based on Microservices with the starting point of architecture optimization [1][2][3][4][5][6]; Its core concept is to decompose complex application systems into multiple services in the form of independent business units, each of which can adopt different implementation technologies and be independently designed, developed, and deployed in a lightweight and more exible mode, running in independent processes to form highly cohesive autonomous units Speci cally, SOA divides the system into different services, uses interfaces for data interaction, and services are interdependent and effectively integrated to achieve the overall function of the system [7][8]. In terms of architecture, the Microservices architecture is an improvement based on SOA architecture, and incorporates the idea of componentization and domain modeling.…”

Section: Introductionmentioning

confidence: 99%

Research on multi-dimensional reconstruction mechanism of cloud native full link in the Metaverse scenario

Sheng

2023

Preprint

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Recently, the Microservices whole link whole life cycle optimization framework has been a research hotspot in the academic and engineering fields, especially how to encapsulate the component security mechanism and conduct high concurrency testing based on the existing active framework. The whole link delay, load, and cost have always been the key optimization goals of Microservices splitting and deployment logic. Based on this, this paper proposes a multi-objective optimization Microservices framework that takes into account the security mechanism, Define the fitness function, define the upper and lower limits, and perform multi-dimensional constraints to filter for global and local optima. At the same time, reconstruct the circuit breaker current limiting mechanism, dynamically detect protocol parameters, and perceive the logical relationship of heartbeat status in real-time. Experimental results have shown that this innovative framework can solve scenarios such as high concurrency, high reliability, and high availability Performance bottleneck, business degradation, especially in financial and securities scenarios.

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“…It has been found that the increase in herd size is driven by economies of scale-the cost of production per unit decreases with increasing herd size [5]. As pointed out in [5], system discussed in detail in [19] consists of a group of microservices that communicate with each other synchronously or asynchronously.…”

Section: Introductionmentioning

confidence: 99%

Design of Scalable IoT Architecture Based on AWS for Smart Livestock

Dineva

Atanasova

2021

Animals

Self Cite

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In the ecological future of the planet, intelligent agriculture relies on CPS and IoT to free up human resources and increase production efficiency. Due to the growing number of connected IoT devices, the maximum scalability capacity, and available computing power of the existing architectural frameworks will be reached. This necessitates finding a solution that meets the continuously growing demands in smart farming. Cloud-based IoT solutions are achieving increasingly high popularity. The aim of this study was to design a scalable cloud-based architecture for a smart livestock monitoring system following Agile methodology and featuring environmental monitoring, health, growth, behaviour, reproduction, emotional state, and stress levels of animals. The AWS services used, and their specific tasks related to the proposed architecture are explained in detail. A stress test was performed to prove the data ingesting and processing capability of the proposed architecture. Experimental results proved that the proposed architecture using AWS automated scaling mechanisms and IoT devices are fully capable of processing the growing amount of data, which in turn allow for meeting the required needs of the constantly expanding number of CPS systems.

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Architectural ML Framework for IoT Services Delivery Based on Microservices

Cited by 7 publications

References 8 publications

An Internet of Things-Based Cluster System for Monitoring Lactating Sows’ Feed and Water Intake

An Internet of Things-Based Cluster System for Monitoring Lactating Sows’ Feed and Water Intake

Research on multi-dimensional reconstruction mechanism of cloud native full link in the Metaverse scenario

Design of Scalable IoT Architecture Based on AWS for Smart Livestock

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