Design support for Wireless Sensor Networks based on the IEEE 802.15.4 standard

Wielens, S.; Galetzka, Michael; Schneider, Peter

doi:10.1109/pimrc.2008.4699594

Cited by 9 publications

(8 citation statements)

References 4 publications

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“…ZigBee both based on IEEE 802.15.1 (Wielens, et al, 2008). These standards have been designed for applications where the transfer speed is not the best but it makes possible for the motes to be powered through batteries.…”

Section: Radio Frequency Identification and Wireless Sensor Network mentioning

confidence: 99%

Integration of BIM and Utility Sensor Data for Facilities Management

Suprabhas¹

2017

Computing in Civil Engineering 2017

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Section: Radio Frequency Identification and Wireless Sensor Network mentioning

confidence: 99%

Integration of BIM and Utility Sensor Data for Facilities Management

Suprabhas¹

2017

Computing in Civil Engineering 2017

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“…Ad hoc networks provide connectivity among M2M devices and from M2M devices and M2M gateways, encompassing such personal area network technologies as ZigBee/other IEEE 802.15.4 [27,28], short-range devices, UWB, M-bus, or wireless M-bus, adopted for the remote reading of gas or electricity meters. Capillary networks enable data transmission from devices unable to independently connect to the operator's network (i.e., IP-unaware devices, not SIM-based devices), facilitating the support of very low-cost and simple devices [29][30][31][32][33][34][35][36][37].…”

Section: M2m Trend Scenariomentioning

confidence: 99%

Dynamic Optical Networks for Future Internet Environments

Matera

2014

Fiber and Integrated Optics

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This article reports an overview on the evolution of the optical network scenario taking into account the exponential growth of connected devices, big data, and cloud computing that is driving a concrete transformation impacting the information and communication technology world. This hyper-connected scenario is deeply affecting relationships between individuals, enterprises, citizens, and public administrations, fostering innovative use cases in practically any environment and market, and introducing new opportunities and new challenges. The successful realization of this hyper-connected scenario depends on different elements of the ecosystem. In particular, it builds on connectivity and functionalities allowed by converged next-generation networks and their capacity to support and integrate with the Internet of Things, machine-to-machine, and cloud computing. This article aims at providing some hints of this scenario to contribute to analyze impacts on optical system and network issues and requirements. In particular, the role of the software-defined network is investigated by taking into account all scenarios regarding data centers, cloud computing, and machine-to-machine and trying to illustrate all the advantages that could be introduced by advanced optical communications.Acronyms 3G, 4G, and 5G third-, fourth-, and fifth-generation 3GPP third-generation partnership project API application programming interface CAPEX capital expenditure CRM customer relationship management DC data center FSO free-space optic FTTB fiber-to-the-building FTTH fiber-to-the-home GMPLS generalized multi-protocol label switching

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“…A ZigBee network is developed to support the communications among sensor nodes. ZigBee works in the license-free and globallyavailable 2.4 GHz bandwidth, based on IEEE 802.15.4 Private Area Network (PAN) standard [6]. To illustrate the application of the developed verification and visualization system, the prototyping WSN in the Intel laboratory of Berkely University is applied as a case study.…”

Section: Architecture Of Integrated Environmentmentioning

confidence: 99%

“…It is essential to provide a modeling and simulation approach, which can be applied in the entire design process of a complex WSN [6]. Many networking simulation tools exist; while some are very good at performing simulation, they may not be good at providing a visualization tool to examine simulation results.…”

Section: Introductionmentioning

confidence: 99%

An integrated environment for visualization of distributed wireless sensor networks

2013

2013 10th IEEE International Conference on Control and Automation (ICCA)

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With the advance of MEMS sensors and wireless communication technologies, wireless sensor networks (WSNs) become ubiquitous. However, design, monitor and control of WSNs are not trivial tasks. To assist the design and monitoring of a WSN, computer aided software tools are essential; both of designers and users need these tools to model and simulate WSNs. Most of existing simulators have been developed for designers; while a few of user-oriented tools are confined to a specific platform or system. In this paper, a modular framework is proposed for modeling and simulation of WSNs, and the aspects of monitoring and visualization are focused. The framework serves for both of designers and users. The programming solutions to some generic functions have been provided. The developed system is open to adapt special modules. To maximize scalability and flexibility of the system, the Eclipse platform and Java have been used for the development. The resulted integrated system accommodates different operating systems such as Windows and Linux. It is capable of integrating other plug-ins developed in various languages such as Java, C, C++ and Matlab. The user-friendly Graphic User Interface (GUI) is developed to create and visualize the acquired real-time data of WSN. The embodied methodologies are capable of predicting the behaviors of objects in network. The integrated visualization system has been illustrated through a case study simulation.

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Design support for Wireless Sensor Networks based on the IEEE 802.15.4 standard

Cited by 9 publications

References 4 publications

Integration of BIM and Utility Sensor Data for Facilities Management

Integration of BIM and Utility Sensor Data for Facilities Management

Dynamic Optical Networks for Future Internet Environments

An integrated environment for visualization of distributed wireless sensor networks

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