Toward a General Distributed Messaging Framework for Online Transaction Processing Applications

Liao, Jianwei; Zhuang, Xinhua; Fan, Renyi; Peng, Xiaoning

doi:10.1109/access.2017.2717930

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…Spark and Hadoop can be better to integrate a variety of data sources after recent development in Spark [6]. Kafka and other distribution messaging technology made real-time data integration possible [12] [13]. Depending on the needs, data can be processed in batch, or real-time using big data tools.…”

Section: Big Data Integrationmentioning

confidence: 99%

Bridging Data Silos Using Big Data Integration

Patel¹

2019

IJDMS

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With cloud computing, cheap storage and technology advancements, an enterprise uses multiple applications to operate business functions. Applications are not limited to just transactions, customer service, sales, finance but they also include security, application logs, marketing, engineering, operations, HR and many more. Each business vertical uses multiple applications which generate a huge amount of data. On top of that, social media, IoT sensors, SaaS solutions, and mobile applications record exponential growth in data volume. In almost all enterprises, data silos exist through these applications. These applications can produce structured, semi-structured, or unstructured data at different velocity and in different volume. Having all data sources integrated and generating timely insights helps in overall decision making. With recent development in Big Data Integration, data silos can be managed better and it can generate tremendous value for enterprises. Big data integration offers flexibility, speed and scalability for integrating large data sources. It also offers tools to generate analytical insights which can help stakeholders to make effective decisions. This paper presents the overview on data silos, challenges with data silos and how big data integration can help to stun them.

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Section: Big Data Integrationmentioning

confidence: 99%

Bridging Data Silos Using Big Data Integration

Patel¹

2019

IJDMS

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“…Data processing is close to the source of the data so that network traffic and the stress of the application server can be reduced. The middleware mainly is wireless sensor network (WSN) middleware such as TinyDB [8] [9] and MetaQ [10] . The main advantages of embedded middleware are that sensor nodes bear data processing capacity and reduce the stress on networks and servers.…”

Section: Related Workmentioning

confidence: 99%

An Architecture of IoT Application Support System in Launch Site

Xiao¹,

Li²,

Xiao³

2018

Proceedings of the 2018 2nd International Conference on Artificial Intelligence: Technologies and Applications (ICAITA 2018)

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Abstract-Internet of Things (IoT) application support system is key infrastructures and common software platform for various IoT applications at launch sites. The research studies the progress of IoT middleware related to academia and industry. On the basis of hybrid architecture, the paper proposes the architecture of the IoT application support system for the launch site. The architecture combines software with hardware and includes design and implementation scheme. It contributes to solving the problems of IoT application support system about the heterogeneity of embedded sensor devices and mobile terminals, mobility and network transformation, communication and data exchange, a fusion of different middleware systems, and implementing middleware support environment in launch site. In the domestic operating system and database environment, the personnel positioning application is realized by graphical programming and application deployment. The actual example verifies the availability of the architecture and presents the developing process of the IoT application support system in the launch site.

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Architecture and Implementation of IoT Middleware for Ground Support Systems in Launch Site

Xiao

et al. 2020

2020 International Conference on Sensing, Measurement &Amp; Data Analytics in the Era of Artificial Intelligence (ICSMD)

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Toward a General Distributed Messaging Framework for Online Transaction Processing Applications

Cited by 3 publications

References 14 publications

Bridging Data Silos Using Big Data Integration

Bridging Data Silos Using Big Data Integration

An Architecture of IoT Application Support System in Launch Site

Architecture and Implementation of IoT Middleware for Ground Support Systems in Launch Site

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