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Wireless sensor networks have recently found their way into a wide range of applications among which environmental monitoring system has attracted increasing interests of researchers. Such monitoring applications, in general, don way into a wide range of applications among which environmental monitoring system has attracted increasing interests of researc latency requirements regarding to the energy efficiency. Also a challenge of this application is the network topology as the application should be able to be deployed in very large scale. Nevertheless low power consumption of the devices making up the network must be on focus in order to maximize the lifetime of the whole system. These devices are usually battery-powered and spend most of their energy budget on radio transceiver module. A so-called Wake-On-Radio (WoR) technology can be used to achieve a reasonable balance among power consumption, range, complexity and response time. In this paper, some designs for integration of WOR into IEEE 802.1.5.4 are to be discussed, providing an overview of trade-offs in energy consumption while deploying the WoR schemes in a monitoring system.
6LoWPAN (IPv6 over Low Power Wireless Personal Area Networks) is gaining more and more attraction for the seamless connectivity of embedded devices for the Internet of Things. It can be observed that most of the available solutions are following an open source approach, which significantly leads to a fast development of technologies and of markets. Although the currently available implementations are in a pretty good shape, all of them come with some significant drawbacks. It was therefore decided to start the development of an own implementation, which takes the advantages from the existing solutions, but tries to avoid the drawbacks. This paper discussed the reasoning behind this decision, describes the implementation and its characteristics, as well as the testing results. The given implementation is available as open-source project under [15].
6LoWPAN (IPv6 over Low Power Wireless Personal Area Networks) is gaining more and more attraction for the seamless connectivity of embedded devices for the Internet of Things (IoT). Whereas the lower layers (IEEE802.15.4 and 6LoWPAN) are already well defined and consolidated with regard to frame formats, header compression, routing protocols and commissioning procedures, there is still an abundant choice of possibilities on the application layer. Currently, various groups are working towards standardization of the application layer, i.e. the ETSI Technical Committee on M2M, the IP for Smart Objects (IPSO) Alliance, Lightweight M2M (LWM2M) protocol of the Open Mobile Alliance (OMA), and OneM2M. This multitude of approaches leaves the system developer with the agony of choice. This paper selects, presents and explains one of the promising solutions, discusses its strengths and weaknesses, and demonstrates its implementation.
Extended Performance Measurements of Scalable 6LoWPAN Networks in an Automated Physical Testbed
(2015)
IPv6 over Low power Wireless Personal Area Networks, also known as 6LoWPAN, is becoming more and more a de facto standard for such communications for the Internet of Things, be it in the field of home and building automation, of industrial and process automation, or of smart metering and environmental monitoring. For all of these applications, scalability is a major precondition, as the complexity of the networks continuously increase. To maintain this growing amount of connected nodes a various 6LoWPAN implementations are available. One of the mentioned was developed by the authors' team and was tested on an Automated Physical Testbed for Wireless Systems at the Laboratory Embedded Systems and Communication Electronics of Offenburg University of Applied Sciences, which allows the flexible setup and full control of arbitrary topologies. It also supports time-varying topologies and thus helps to measure performance of the RPL implementation. The results of the measurements prove an excellent stability and a very good short and long-term performance also under dynamic conditions. In all measurements, there is an advantage of minimum 10% with regard to the average times, like global repair time; but the advantage with reagr to average values can reach up to 30%. Moreover, it can be proven that the performance predictions from other papers are consistent with the executed real-life implementations.