Lightweight Service Mashup Middleware With REST Style Architecture for IoT Applications

Cheng, Bo; Zhao, Shuai; Qian, Junyan; Zhai, Zhongyi; Chen, Junliang

doi:10.1109/tnsm.2018.2827933

Cited by 40 publications

(15 citation statements)

References 26 publications

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“…Recent research on light-weight service mashup middleware for IoT applications that allow the physical things seamless integration into the Web. This help the easy development and deployment of IoT-based smart city applications [41]. In these applications, discovering behavioral patterns can significantly improve services such as transportation, energy consumption and security.…”

Section: Smart City Servicesmentioning

confidence: 99%

A Survey on Behavioral Pattern Mining From Sensor Data in Internet of Things

et al. 2020

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The deployment of large-scale wireless sensor networks (WSNs) for the Internet of Things (IoT) applications is increasing day-by-day, especially with the emergence of smart city services. The sensor data streams generated from these applications are largely dynamic, heterogeneous, and often geographically distributed over large areas. For high-value use in business, industry and services, these data streams must be mined to extract insightful knowledge, such as about monitoring (e.g., discovering certain behaviors over a deployed area) or network diagnostics (e.g., predicting faulty sensor nodes). However, due to the inherent constraints of sensor networks and application requirements, traditional data mining techniques cannot be directly used to mine IoT data streams efficiently and accurately in real-time. In the last decade, a number of works have been reported in the literature proposing behavioral pattern mining algorithms for sensor networks. This paper presents the technical challenges that need to be considered for mining sensor data. It then provides a thorough review of the mining techniques proposed in the recent literature to mine behavioral patterns from sensor data in IoT, and their characteristics and differences are highlighted and compared. We also propose a behavioral pattern mining framework for IoT and discuss possible future research directions in this area. INDEX TERMS Association rules, behavioral patterns, data mining, frequent pattern, Internet of Things, knowledge discovery, wireless sensor networks.

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Section: Smart City Servicesmentioning

confidence: 99%

A Survey on Behavioral Pattern Mining From Sensor Data in Internet of Things

et al. 2020

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“…To address these issues, several solutions are proposed to improve traditional development environments [32]. Visual designer, a graphical drag-and-drop tool or plugin, has been widely used in multiple mobile development environments to facilitate designing the GUI process.…”

Section: B Visual Development Environmentmentioning

confidence: 99%

Enabling Ordinary Users Mobile Development With Web Components

2020

Self Cite

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The rapid progress of the mobile internet has been promoting the popularity of mobile devices, and mobile application development is getting more pervasive. However, the state of the art development environments has a high learning barrier for users' lack of programming experience. In this paper, instead of traditional programming environments, we take consideration of ordinary users' requirements and propose a WYSIWYG cross-platform web-component-based mobile application creation environment for ordinary users. This environment has a visual editor with a drag-and-drop web component. A web component library model is proposed to standardize customized libraries. A cross-platform application model based on web components is implemented to build applications rapidly. It helps ordinary users generate installing packages within simple operations for multiple platforms. A native plugin model is proposed to assist web components to invoke native functionalities. The experiment result shows that ordinary users could quickly start to create mobile applications in our environment.

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“…A great deal of effort has been devoted to clarify requirements for IoT middleware , including network protocol bridging [9,10], device and network management [11], resource searching [12], REST (representational state transfer) API [13], semantics [14,15], security [16], and support for cloud and fog computing [17,18,19,20]. Cruz et al proposed an application layer gateway (called MiddleBridge) running on Java virtual machine, which translate widely used message protocols including constrained application layer protocol (CoAP), message queuing telemetry transport protocol (MQTT), data distribution service (DDS), and WebSocket to hypertext transfer protocol (HTTP) [9].…”

Section: Related Workmentioning

confidence: 99%

Implementation of Sensing and Actuation Capabilities for IoT Devices Using oneM2M Platforms

Yun

Ahn

Song

et al. 2019

Sensors

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In this paper, we present an implementation work of sensing and actuation capabilities for IoT devices using the oneM2M standard-based platforms. We mainly focus on the heterogeneity of the hardware interfaces employed in IoT devices. For IoT devices (i.e., Internet-connected embedded systems) to perform sensing and actuation capabilities in a standardized manner, a well-designed middleware solution will be a crucial part of IoT platform. Accordingly, we propose an oneM2M standard-based IoT platform (called nCube) incorporated with a set of tiny middleware programs (called TAS) responsible for translating sensing values and actuation commands into oneM2M-defined resources accessible in Web-based applications. All the source codes for the oneM2M middleware platform and smartphone application are available for free in the GitHub repositories. The full details on the implementation work and open-source contributions are described.

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Lightweight Service Mashup Middleware With REST Style Architecture for IoT Applications

Cited by 40 publications

References 26 publications

A Survey on Behavioral Pattern Mining From Sensor Data in Internet of Things

A Survey on Behavioral Pattern Mining From Sensor Data in Internet of Things

Enabling Ordinary Users Mobile Development With Web Components

Implementation of Sensing and Actuation Capabilities for IoT Devices Using oneM2M Platforms

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