A Novel Protocol For Barrier K-Coverage In Wireless Sensor Networks

One of major problems in the wireless sensor networks is the barrier coverage problem. This problem deals with the ability to minimizing the probability of undetected penetration through the barrier (sensor network). The reliability and fault tolerance problems are very important for long strip barrier coverage sensor networks. Also, another design challenge in sensor networks is to save limited energy resources to prolong the lifetime of wireless sensor network. In this paper we propose the fault tolerant k-barrier coverage protocol, called APBC. The proposed protocol maintains a good balance in using nodes energy, in order to prolong the network lifetime. The proposed protocol presents a proper way to provide the k-barrier coverage at nodes fails without reexecuting the algorithm. The simulation results show that this method prolongs the lifetime of the network in comparison with RIS method

Finding and Mending Barrier Gaps in Wireless Sensor Networks

Constructing sensing barriers using wireless sensor networks has important applications in military operations and homeland security. The goal of forming a sensing barrier is to detect intruders attempting to cross the network. Early studies often assume that sensors remain static once deployed. We note that barrier gaps may occur at deployment if sensors are deployed at random. Barrier gaps may also occur in an existing barrier if some sensors used to form the barrier start malfunctioning or run out of power. We present an efficient solution to solve this problem. In particular, we devise an efficient algorithm to find sensing gaps and relocate mobile sensors to form a new barrier while balancing the energy consumption among mobile sensors. We also investigate the related design issues and performance tradeoffs. Simulation results show that our algorithms can effectively improve the barrier coverage of a wireless sensor network under a wide range of deployment parameters. These results provide insights and guidelines to the deployment, design, and performance of mobile wireless sensor networks for barrier coverage

Deployment, Coverage And Network Optimization In Wireless Video Sensor Networks For 3D Indoor Monitoring

As a result of extensive research over the past decade or so, wireless sensor networks (wsns) have evolved into a well established technology for industry, environmental and medical applications. However, traditional wsns employ such sensors as thermal or photo light resistors that are often modeled with simple omni-directional sensing ranges, which focus only on scalar data within the sensing environment. In contrast, the sensing range of a wireless video sensor is directional and capable of providing more detailed video information about the sensing field. Additionally, with the introduction of modern features in non-fixed focus cameras such as the pan, tilt and zoom (ptz), the sensing range of a video sensor can be further regarded as a fan-shape in 2d and pyramid-shape in 3d. Such uniqueness attributed to wireless video sensors and the challenges associated with deployment restrictions of indoor monitoring make the traditional sensor coverage, deployment and networked solutions in 2d sensing model environments for wsns ineffective and inapplicable in solving the wireless video sensor network (wvsn) issues for 3d indoor space, thus calling for novel solutions. In this dissertation, we propose optimization techniques and develop solutions that will address the coverage, deployment and network issues associated within wireless video sensor networks for a 3d indoor environment. We first model the general problem in a continuous 3d space to minimize the total number of required video sensors to monitor a given 3d indoor region. We then convert it into a discrete version problem by incorporating 3d grids, which can achieve arbitrary approximation precision by adjusting the grid granularity. Due in part to the uniqueness of the visual sensor directional sensing range, we propose to exploit the directional feature to determine the optimal angular-coverage of each deployed visual sensor. Thus, we propose to deploy the visual sensors from divergent directional angles and further extend k-coverage to ``k-angular-coverage\u27\u27, while ensuring connectivity within the network. We then propose a series of mechanisms to handle obstacles in the 3d environment. We develop efficient greedy heuristic solutions that integrate all these aforementioned considerations one by one and can yield high quality results. Based on this, we also propose enhanced depth first search (dfs) algorithms that can not only further improve the solution quality, but also return optimal results if given enough time. Our extensive simulations demonstrate the superiority of both our greedy heuristic and enhanced dfs solutions. Finally, this dissertation discusses some future research directions such as in-network traffic routing and scheduling issues

Quantum Communication Systems: Vision, Protocols, Applications, and Challenges

The growth of modern technological sectors have risen to such a spectacular level that the blessings of technology have spread to every corner of the world, even to remote corners. At present, technological development finds its basis in the theoretical foundation of classical physics in every field of scientific research, such as wireless communication, visible light communication, machine learning, and computing. The performance of the conventional communication systems is becoming almost saturated due to the usage of bits. The usage of quantum bits in communication technology has already surpassed the limits of existing technologies and revealed to us a new path in developing technological sectors. Implementation of quantum technology over existing system infrastructure not only provides better performance but also keeps the system secure and reliable. This technology is very promising for future communication systems. This review article describes the fundamentals of quantum communication, vision, design goals, information processing, and protocols. Besides, quantum communication architecture is also proposed here. This research included and explained the prospective applications of quantum technology over existing technological systems, along with the potential challenges of obtaining the goal.Comment: 23 pages, 11 Figure

Continental shelf seafloor mapping, benthic habitat surveys, and reef fish assessments in the eastern Gulf of Mexico

In April 2010, The Deepwater Horizon (DWH) oil spill originated in the deep sea 1,500 m below the ocean surface at the edge of the continental shelf off Louisiana. Surface and sub-surface dispersal of the oil eventually encompassed an area of over 200,000 km2. Impacts of DWH on biota of the Gulf of Mexico were severe, wide-spread, and are ongoing even a decade after the spill. Because of its offshore origin, the spill caused injury to many resources on the continental shelf, including important reef fish species (e.g., snappers and groupers, etc.) and protected species including sea turtles. Habitats which these species occupy were oiled which resulted in the loss of key supporting plant and animal species. Because so little of the offshore habitat of reef fish species and sea turtles was mapped and characterized prior to the spill, restoration efforts aimed at improving degraded habitats and strengthening species populations proved difficult. This project was specifically developed to discover additional, high conservation value, habitats of reef fishes and sea turtles on the continental shelf of the Gulf of Mexico off Florida (the West Florida Shelf, WFS). The goal of the project was to map such habitats and quantify the density and biodiversity of species occupying them, and to facilitate additional conservation management decisions to enhance their long-term sustainability. The project resulted in mapping and classifying and characterizing 2,350 km2 of heretofore unmapped habitats, the development of new methods to extrapolate habitat types from a sub-sample from video surveys, and new technologies to automate the counting and identification of fish species and habitat features using artificial intelligence. Project personnel have presented these materials to the competent management authorities responsible for fish and sea turtle management. Here we provide technical detail on the methods, procedures and findings from this project.Funded by the National Fish and Wildlife Foundation (NFWF) Gulf Environmental Benefit Fund (2015 - 2020

Sounding the reef: comparative acoustemologies of underwater noise pollution / Pejling af revet: komparativ akustemologi af undersøisk støjforurening

Matthew Buttacavoli studied the development and detection of the category of underwater noise pollution in the Great Barrier Reef. He examined the phenomenon using a multi-species ethnographic approach. He found that bodily affordances and species’ boundaries that make sensing underwater noise difficult, can be overcome through technology and skilled practice. [Extract from Danish abstract] Denne afhandling vælger en etnografisk strategi til at undersøge, hvordan interesserede lyttere forsøger at opfatte og rekonstruere det akustiske havmiljø. Observation og interviews af deltagere sættes sammen med optagelse og kreative metoder for at kortlægge de (ufuldkomne) måder, hvorpå lyttere (herunder forfatteren) forsøger at forstå havskabningers lydverdener. I fokus er de lyttemetoder, der blev udviklet af dykkere, havforskere, akustikere og interesseorganisationer

Drivers and barriers for implementation radical and incremental innovation in subsea complex in Russia

Master i Energy Management - Nord universitet, 2017Sperret til 2020-10-0

Cooperative Navigation for Low-bandwidth Mobile Acoustic Networks.

This thesis reports on the design and validation of estimation and planning algorithms for underwater vehicle cooperative localization. While attitude and depth are easily instrumented with bounded-error, autonomous underwater vehicles (AUVs) have no internal sensor that directly observes XY position. The global positioning system (GPS) and other radio-based navigation techniques are not available because of the strong attenuation of electromagnetic signals in seawater. The navigation algorithms presented herein fuse local body-frame rate and attitude measurements with range observations between vehicles within a decentralized architecture. The acoustic communication channel is both unreliable and low bandwidth, precluding many state-of-the-art terrestrial cooperative navigation algorithms. We exploit the underlying structure of a post-process centralized estimator in order to derive two real-time decentralized estimation frameworks. First, the origin state method enables a client vehicle to exactly reproduce the corresponding centralized estimate within a server-to-client vehicle network. Second, a graph-based navigation framework produces an approximate reconstruction of the centralized estimate onboard each vehicle. Finally, we present a method to plan a locally optimal server path to localize a client vehicle along a desired nominal trajectory. The planning algorithm introduces a probabilistic channel model into prior Gaussian belief space planning frameworks. In summary, cooperative localization reduces XY position error growth within underwater vehicle networks. Moreover, these methods remove the reliance on static beacon networks, which do not scale to large vehicle networks and limit the range of operations. Each proposed localization algorithm was validated in full-scale AUV field trials. The planning framework was evaluated through numerical simulation.PhDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113428/1/jmwalls_1.pd