Javascript must be enabled to continue!
Modeling and Deploying IoT-Aware Business Process Applications in Sensor Networks
View through CrossRef
The concept of the Internet of Things (IoT) is an important part of the next generation of information. Wireless sensor networks are composed of independent distributed smart sensor nodes and gateways. These discrete sensors constantly gather external physical information, such as temperature, sound, and vibration. Owing to the diversity of sensor devices and the complexity of the sensor sensing environment, the direct modeling of an IoT-aware business process application is particularly difficult. In addition, how to effectively deploy those designed applications to discrete servers in the heterogeneous sensor networks is also a pressing problem. In this paper, we propose a resource-oriented modeling approach and a dynamic consistent hashing (DCH)-based deploying algorithm to solve the above problems. Initially, we extended the graphic and machine-readable model of Business Process Model Notation (BPMN) 2.0 specification, making it able to support the direct modeling of an IoT-aware business process application. Furthermore, we proposed the DCH-based deploying algorithm to solve the problem of dynamic load balancing and access efficiency in the distributed execution environment. Finally, we designed an actual extended BPMN plugin in Eclipse. The approach presented in this paper has been validated to be effective.
Title: Modeling and Deploying IoT-Aware Business Process Applications in Sensor Networks
Description:
The concept of the Internet of Things (IoT) is an important part of the next generation of information.
Wireless sensor networks are composed of independent distributed smart sensor nodes and gateways.
These discrete sensors constantly gather external physical information, such as temperature, sound, and vibration.
Owing to the diversity of sensor devices and the complexity of the sensor sensing environment, the direct modeling of an IoT-aware business process application is particularly difficult.
In addition, how to effectively deploy those designed applications to discrete servers in the heterogeneous sensor networks is also a pressing problem.
In this paper, we propose a resource-oriented modeling approach and a dynamic consistent hashing (DCH)-based deploying algorithm to solve the above problems.
Initially, we extended the graphic and machine-readable model of Business Process Model Notation (BPMN) 2.
0 specification, making it able to support the direct modeling of an IoT-aware business process application.
Furthermore, we proposed the DCH-based deploying algorithm to solve the problem of dynamic load balancing and access efficiency in the distributed execution environment.
Finally, we designed an actual extended BPMN plugin in Eclipse.
The approach presented in this paper has been validated to be effective.
Related Results
Access mechanisms for massive Internet of Things in 5G and beyond networks
Access mechanisms for massive Internet of Things in 5G and beyond networks
(English) The Massive Internet of Things (MIoT) characterizes a communication scenario where a massive number of battery-operated devices perform infrequent, primarily uplink-orien...
Dynamic stochastic modeling for inertial sensors
Dynamic stochastic modeling for inertial sensors
Es ampliamente conocido que los modelos de error para sensores inerciales tienen dos componentes: El primero es un componente determinista que normalmente es calibrado por el fabri...
Pelatihan Internet of Things (IoT) dalam peningkatan kompetensi siswa multimedia di SMK Perguruan Buddhi
Pelatihan Internet of Things (IoT) dalam peningkatan kompetensi siswa multimedia di SMK Perguruan Buddhi
Pelatihan Internet of Things (IoT) menjadi bagian penting dalam pengembangan kompetensi siswa jurusan multimedia di SMK Perguruan Buddhi. Era digital menuntut adanya pemahaman mend...
Impact and Innovations of Azure IoT: Current Applications, Services, and Future Directions
Impact and Innovations of Azure IoT: Current Applications, Services, and Future Directions
Azure IoT, developed by Microsoft, is a leading platform in the realm of Internet of Things (IoT), revolutionizing industries through enhanced connectivity, robust data management,...
Implementation of Faulty Sensor Detection Mechanism using Data Correlation of Multivariate Sensor Readings in Smart Agriculture
Implementation of Faulty Sensor Detection Mechanism using Data Correlation of Multivariate Sensor Readings in Smart Agriculture
Through sensor networks, agriculture can be connected to the IoT, which allows us to create connections among agronomists, farmers, and crops regardless of their geographical diffe...
Energy efficient cooperative node management for wireless multimedia sensor networks
Energy efficient cooperative node management for wireless multimedia sensor networks
In Wireless Multimedia Sensor Networks (WMSNs) the lifetime of battery operated visual nodes is limited by their energy consumption, which is proportional to the energy required fo...
ACM SIGCOMM computer communication review
ACM SIGCOMM computer communication review
At some point in the future, how far out we do not exactly know, wireless access to the Internet will outstrip all other forms of access bringing the freedom of mobility to the way...
IoT-Flock: An Open-source Framework for IoT Traffic Generation
IoT-Flock: An Open-source Framework for IoT Traffic Generation
Abstract
Network traffic generation is one of the primary techniques that is used to design and analyze the performance of network security systems. However, due to the div...

