Determination of RF source power in WPSN using modulated backscattering

A wireless sensor network (WSN) is a wireless network consisting of spatially distributed autonomous devices using sensors to cooperatively monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants, at different locations. During RF transmission energy consumed by critically energy-constrained sensor nodes in a WSN is related to the life time system, but the life time of the system is inversely proportional to the energy consumed by sensor nodes. In that regard, modulated backscattering (MB) is a promising design choice, in which sensor nodes send their data just by switching their antenna impedance and reflecting the incident signal coming from an RF source. Hence wireless passive sensor networks (WPSN) designed to operate using MB do not have the lifetime constraints. In this we are going to investigate the system analytically. To obtain interference-free communication connectivity with the WPSN nodes number of RF sources is determined and analyzed in terms of output power and the transmission frequency of RF sources, network size, RF source and WPSN node characteristics. The results of this paper reveal that communication coverage and RF Source Power can be practically maintained in WPSN through careful selection of design parametersComment: 10 pages; International Journal on Soft Computing (IJSC) Vol.3, No.1 (2012). arXiv admin note: text overlap with arXiv:1001.5339 by other author

Wireless communication, identification and sensing technologies enabling integrated logistics: a study in the harbor environment

In the last decade, integrated logistics has become an important challenge in the development of wireless communication, identification and sensing technology, due to the growing complexity of logistics processes and the increasing demand for adapting systems to new requirements. The advancement of wireless technology provides a wide range of options for the maritime container terminals. Electronic devices employed in container terminals reduce the manual effort, facilitating timely information flow and enhancing control and quality of service and decision made. In this paper, we examine the technology that can be used to support integration in harbor's logistics. In the literature, most systems have been developed to address specific needs of particular harbors, but a systematic study is missing. The purpose is to provide an overview to the reader about which technology of integrated logistics can be implemented and what remains to be addressed in the future

Distributed Coverage Area Reporting for Wireless Sensor Networks

In order to efficiently deal with subscriptions or other location dependent information, it is key that the wireless sensor network informs the gateways what geographical area is serviced by which gateway. The gateways are then able to e.g. efficiently route subscriptions which are only valid in particular regions of the deployment. \ud \ud In our distributed approach of establishing a description of WSN coverage area per gateway, we let nodes keep track of the convex hull of the coverage area. In this way, gateways are efficiently informed of the service areas, while we limit the amount of information each node needs to store, transmit and receive

Combined Coverage Area Reporting and Geographical Routing in Wireless Sensor-Actuator Networks for Cooperating with Unmanned Aerial Vehicles

In wireless sensor network (WSN) applications with multiple gateways, it is key to route location dependent subscriptions efficiently at two levels in the system. At the gateway level, data sinks must not waste the energy of the WSN by injecting subscriptions that are not relevant for the nodes in their coverage area and at WSN level, energy-efficient delivery of subscriptions to target areas is required. In this paper, we propose a mechanism in which (1) the WSN provides an accurate and up-to-date coverage area description to gateways and (2) the wireless sensor network re-uses the collected coverage area information to enable efficient geographical routing of location dependent subscriptions and other messages. The latter has a focus on routing of messages injected from sink nodes to nodes in the region of interest. Our proposed mechanisms are evaluated in simulation

MH-REACH-Mote: supporting multi-hop passive radio wake-up for wireless sensor network

A passive wake-up radio in a wireless sensor network (WSN) has the advantage of increasing network lifetime by using a wake-up radio receiver (WuRx) to eliminate unnecessary idle listening. A sensor node equipped with a WuRx can operate in an ultra-low-power sleep mode, waiting for a trigger signal sent by the wake-up radio transmitter (WuTx). The passive WuRx is entirely powered by the energy harvested from radio transmissions sent by the WuTx. Therefore, it has the advantage of not consuming any energy locally, which would drain the sensor node's battery. Even so, the high amount of energy required to wake up a passive WuRx by a WuTx makes it difficult to build a multi-hop passive wake-up sensor network. In this paper, we describe and discuss our implementation of a battery-powered sensor node with multi-hop wake-up capability using passive WuRxs, called MH-REACH-Mote (Multi-hop-Range EnhAnCing energy Harvester-Mote). The MH-REACH-Mote is kept in an ultra-low-power sleep mode until it receives a wake-up trigger signal. Upon receipt, it wakes up and transmits a new trigger signal to power other passive WuRxs. We evaluate the wake-up range and power consumption of an MH-REACH-Mote through a series of field tests. Results show that the MH-REACH-Mote enables multi-hop wake-up capabilities for passive WuRxs with a wake-up range of 9.4m while requiring a reasonable power consumption for WuTx functionality. We also simulate WSN data collection scenarios with MH-REACH-Motes and compare the results with those of active wake-up sensor nodes as well as a low power listening approach. The results show that the MH-REACH-Mote enables a longer overall lifetime than the other two approaches when data is collected infrequently.Peer ReviewedPostprint (author's final draft