We measure the energy emitted by extensive air showers in the form of\ud
radio emission in the frequency range from 30 to 80 MHz. Exploiting the\ud
accurate energy scale of the Pierre Auger Observatory, we obtain a\ud
radiation energy of 15.8 +/- 0.7 (stat) +/- 6.7 (syst) MeV for cosmic\ud
rays with an energy of 1 EeV arriving perpendicularly to a geomagnetic\ud
field of 0.24 G, scaling quadratically with the cosmic-ray energy. A\ud
comparison with predictions from state-of-the-art first-principles\ud
calculations shows agreement with our measurement. The radiation energy\ud
provides direct access to the calorimetric energy in th
The Auger Engineering Radio Array (AERA) is part of the Pierre Auger Observatory and is used to detect the radio emission of cosmic-ray air showers. These observations are compared to the data of the surface detector stations of the Observatory, which provide well-calibrated information on the cosmic-ray energies and arrival directions. The response of the radio stations in the 30 to 80 MHz regime has been thoroughly calibrated to enable the reconstruction of the incoming electric field. For the latter, the energy deposit per area is determined from the radio pulses at each observer position and is interpolated using a two dimensional function that takes into account signal asymmetries due to interference between the geomagnetic and charge excess emission components. The spatial integral over the signal distribution gives a direct measurement of the energy transferred from the primary cosmic ray into radio emission in the AERA frequency range. We measure 15.8 MeV of 4 radiation energy for a 1 EeV air shower arriving perpendicularly to the geomagnetic field. This radiation energy -corrected for geometrical effects -is used as a cosmic-ray energy estimator. Performing an absolute energy calibration against the surface-detector information, we observe that this radio-energy estimator scales quadratically with the cosmic-ray energy as expected for coherent emission. We find an energy resolution of the radio reconstruction of 22% for the data set and 17% for a high-quality subset containing only events with at least five radio stations with signal. PACS numbers: 96.50.sd, 96.50.sb, 95.85.Bh, 95.55.Vj
Localization is one of the most challenging and important issues in wireless sensor networks (WSNs), especially if cost-effective approaches are demanded. In this paper, we present intensively discuss and analyze approaches relying on the received signal strength indicator (RSSI). The advantage of employing the RSSI values is that no extra hardware (e.g. ultrasonic or infra-red) is needed for network-centric localization. We studied different factors that affect the measured RSSI values. Finally, we evaluate two methods to estimate the distance; the first approach is based on statistical methods. For the second one, we use an artificial neural network to estimate the distance.
We present the Virtual Cord Protocol (VCP), which exploits virtual coordinates to provide efficient and failure tolerant routing and data management in sensor networks. VCP maintains a virtual cord interconnecting all the nodes in the network and which, operating similar to a Distributed Hash Table (DHT), provides means for inserting data fragments into sensor nodes and retrieving them. Furthermore, it supports service discovery using indirections. VCP uses two mechanisms for finding paths to nodes and associated data items: First, it relies on the virtual cord that always provides a path toward the destination. Second, locally available neighborhood information is exploited for greedy routing. Our simulation results show that VCP is able to find paths close to the shortest path (achieving a stretch ratio of less than 125 percent) with very low overhead. We also extended VCP with data replication mechanisms to improve failure handling. The routing performance of VCP, which clearly outperforms other ad hoc routing protocols such as Dynamic MANET On Demand (DYMO), is similar to other virtual addressing schemes, e.g., Virtual Ring Routing (VRR). However, we improved VCP to handle frequent node failures in an optimized way. The presented results outline the capabilities of VCP to handle such cases more efficiently compared to other protocols. We also compared the capabilities to reliably store and retrieve data in the network to Geographic Hash Tables (GHTs). VCP, in the worst case, performs similar to GHTs, but outperforms this protocol in most cases, especially when complex routing is involved.
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