Reliable data delivery in low energy ad hoc sensor networks

Reliable delivery of data is a classical design goal for reliability-oriented collection routing protocols for ad hoc wireless sensor networks (WSNs). Guaranteed packet delivery performance can be ensured by careful selection of error free links, quick recovery from packet losses, and avoidance of overloaded relay sensor nodes. Due to limited resources of individual senor nodes, there is usually a trade-off between energy spending for packets transmissions and the appropriate level of reliability. Since link failures and packet losses are unavoidable, sensor networks may tolerate a certain level of reliability without significantly affecting packets delivery performance and data aggregation accuracy in favor of efficient energy consumption. However a certain degree of reliability is needed, especially when hop count increases between source sensor nodes and the base station as a single lost packet may result in loss of a large amount of aggregated data along longer hops. An effective solution is to jointly make a trade-off between energy, reliability, cost, and agility while improving packet delivery, maintaining low packet error ratio, minimizing unnecessary packets transmissions, and adaptively reducing control traffic in favor of high success reception ratios of representative data packets. Based on this approach, the proposed routing protocol can achieve moderate energy consumption and high packet delivery ratio even with high link failure rates. The proposed routing protocol was experimentally investigated on a testbed of Crossbow's TelosB motes and proven to be more robust and energy efficient than the current implementation of TinyOS2.x MultihopLQI

Traffic eavesdropping based scheme to deliver time-sensitive data in sensor networks

Due to the broadcast nature of wireless channels, neighbouring sensor nodes may overhear packets transmissions from each other even if they are not the intended recipients of these transmissions. This redundant packet reception leads to unnecessary expenditure of battery energy of the recipients. Particularly in highly dense sensor networks, overhearing or eavesdropping overheads can constitute a significant fraction of the total energy consumption. Since overhearing of wireless traffic is unavoidable and sometimes essential, a new distributed energy efficient scheme is proposed in this paper. This new scheme exploits the inevitable overhearing effect as an effective approach in order to collect the required information to perform energy efficient delivery for data aggregation. Based on this approach, the proposed scheme achieves moderate energy consumption and high packet delivery rate notwithstanding the occurrence of high link failure rates. The performance of the proposed scheme is experimentally investigated a testbed of TelosB motes in addition to ns-2 simulations to validate the performed experiments on large-scale network

HUGO:The Hawaii Undersea Geo-Observatory

The Hawaii Undersea Geo-Observatory, HUGO, was installed with the intent of supplying infrastructure for researchers interested in studies of undersea volcanism and associated phenomena at Loihi, the newest volcano of the Hawaiian chain. Much like an astronomical observatory, HUGO is a facility where scientists can perform experiments while sharing resources with others. The main components of HUGO are the shore station, supplying power to the observatory and recording data; the main cable-an electro-optical cable connecting the shore station to the summit of Loihi; the Junction box-the power distribution and data collection center on Loihi; multiplexing (mux) nodes-secondary distribution points; and experiments supplied by scientists. HUGO can potentially supply electrical power, command capability and real-time data service to more than 100 instruments connected and removed on the ocean floor by submersible or ROV. HUGO was installed on October 11, 1997, but the main cable developed an electrical short circuit to sea water on April 26, 1998, and a new cable must be obtained and installed before routine operations can continue. Despite the failure, several important tasks have been accomplished, including: 1) the successful small-ship lay of the 47-km electro-optical cable from the Island of Hawaii to the summit of Loihi submarine volcano; 2) installation and servicing of the Junction box; 3) successful operation of electro-optical connectors on the ocean floor by submersible; 4) installation and removal of experiments on the ocean floor; 5) transmission of power and commands from shore to experiments installed at HUGO; 6) transmission of high-rate, high-fidelity data from the summit of Loihi to shore in real time; and 7) recording of volcanic, earthquake, biological, ocean wave and ship noises for a period of three months. This paper provides a general description of the HUGO system and its history of operation

Dynamics of Outgassing and Plume Transport Revealed by Proximal Unmanned Aerial System (UAS) Measurements at Volcán Villarrica, Chile

Volcanic gas emissions are intimately linked to the dynamics of magma ascent and outgassing, and, on geological timescales, constitute an important source of volatiles to the Earth’s atmosphere. Measurements of gas composition and flux are therefore critical to both volcano monitoring and to determining the contribution of volcanoes to global geochemical cycles. However, significant gaps remain in our global inventories of volcanic emissions, (particularly for CO2, which requires proximal sampling of a concentrated plume) for those volcanoes where the near-vent region is hazardous or inaccessible. Unmanned Aerial Systems (UAS) provide a robust and effective solution to proximal sampling of dense volcanic plumes in extreme volcanic environments. Here, we present gas compositional data acquired using a gas sensor payload aboard a UAS flown at Volcán Villarrica, Chile. We compare UAS-derived gas timeseries to simultaneous crater rim multi-GAS data and UV camera imagery to investigate early plume evolution. SO2 concentrations measured in the young proximal plume exhibit periodic variations that are well-correlated with the concentrations of other species. By combining molar gas ratios (CO2/SO2 = 1.48–1.68, H2O/SO2 = 67–75 and H2O/CO2 = 45–51) with the SO2 flux (142 ± 17 t/day) from UV camera images, we derive CO2 and H2O fluxes of ~150 t/day and ~2850 t/day, respectively. We observe good agreement between time-averaged molar gas ratios obtained from simultaneous UAS- and ground-based Multi-GAS acquisitions. However, the UAS measurements made in the young, less diluted plume reveal additional short-term periodic structure that reflects active degassing through discrete, audible gas exhalations.Alfred P. Sloan Foundation; Leverhulme Trus

Politecast - a new communication primitive for wireless sensor networks

Wireless sensor networks have the potential for becoming a huge market. Ericsson predicts 50 billion devices interconnected to the Internet by the year 2020. Before that, the devices must be made to be able to withstand years of usage without having to change power source as that would be too costly. These devices are typically small, inexpensive and severally resource constrained. Communication is mainly wireless, and the wireless transceiver on the node is typically the most power hungry component. Therefore, reducing the usage of radio is key to long lifetime. In this thesis I identify four problems with the conventional broadcast primitive. Based on those problems, I implement a new communication primitive. This primitive is called Politecast. I evaluate politecast in three case studies: the Steal the Light toy example, a Neighbor Discovery simulation and a full two-month deployment of the Lega system in the art gallery Liljevalchs. With the evaluations, Politecast is shown to be able to massively reduce the amount of traffic being transmitted and thus reducing congestion and increasing application performance. It also prolongs node lifetime by reducing the overhearing by waking up neighbors

Volcanology from space: applications of infrared remote sensing

Remote sensing techniques are being used increasingly to address volcanological problems. This thesis is concerned with the interpretation of multispectral infrared data of volcanic thermal features. Data from the two short wavelength infrared (SWIR) bands of the Landsat Thematic Mapper (TM) are used to constrain sizes and temperatures of subpixel resolution hot spots. Analysis of a 1989 TM scene of Lonquimay volcano suggests a cooling from 250 to 170°C of the crust of an active lava flow down 1.5 km of its length. Estimates of the summed radiative and convective heat losses from the flow top fall from 6 to 3 MW per 30 x 30 m pixel downflow. Thermal data were collected at volcanoes in Chile, Nicaragua and Italy to test assumptions explicit in such calculations. These surveys suggest that SWIR emission from fumarole fields is dominated by that from the interior walls of vents, and that surface temperatures around fumarole vents are lower than those of typical active lava bodies. The relative response of the two SWIR sensors of the TM is sensitive to such differences and therefore provides a basis for the interpretation of thennal anomalies known only from satellite data. Comparison of measurements in the two SWIR bands is petfonned with fourteen TM scenes recorded between 1984 and 1991, of a persistent hot spot at Lascar volcano, Chile. Evolution of the thennal source is charted by comparing the summed spectral radiance in each of the SWIR bands. Thus it appears that Lascar has experienced at least two periods of lava dome growth punctuated by the explosive eruptions of 1986 and 1990. Infrared sensors to be deployed on forthcoming remote sensing platfonns, including the Japanese Earth Resources Satellite and NASA's Earth Observing System, promise to constrain thennal emissions from volcanoes more effectively than possible with existing orbital systems. These investigations will improve understanding of the physical processes that influence the emplacement of lavas, as well as the potential for detecting eruption precursors and evaluating volcanic hazards

Decentralized Convex Optimization for Wireless Sensor Networks

Many real-world applications arising in domains such as large-scale machine learning, wired and wireless networks can be formulated as distributed linear least-squares over a large network. These problems often have their data naturally distributed. For instance applications such as seismic imaging, smart grid have the sensors geographically distributed and the current algorithms to analyze these data rely on centralized approach. The data is either gathered manually, or relayed by expensive broadband stations, and then processed at a base station. This approach is time-consuming (weeks to months) and hazardous as the task involves manual data gathering in extreme conditions. To obtain the solution in real-time, we require decentralized algorithms that do not rely on a fusion center, cluster heads, or multi-hop communication. In this thesis, we propose several decentralized least squares optimization algorithm that are suitable for performing real-time seismic imaging in a sensor network. The algorithms are evaluated and tested using both synthetic and real-data traces. The results validate that our distributed algorithm is able to obtain a satisfactory image similar to centralized computation under constraints of network resources, while distributing the computational burden to sensor nodes