Wireless Sensor Networks for Underwater Localization: A Survey

Autonomous Underwater Vehicles (AUVs) have widely deployed in marine investigation and ocean exploration in recent years. As the fundamental information, their position information is not only for data validity but also for many real-world applications. Therefore, it is critical for the AUV to have the underwater localization capability. This report is mainly devoted to outline the recent advance- ment of Wireless Sensor Networks (WSN) based underwater localization. Several classic architectures designed for Underwater Acoustic Sensor Network (UASN) are brie y introduced. Acoustic propa- gation and channel models are described and several ranging techniques are then explained. Many state-of-the-art underwater localization algorithms are introduced, followed by the outline of some existing underwater localization systems

Computing Approximate Solutions to the Art Gallery Problem and Watchman Route Problem by Means of Photon Mapping

Wireless sensor networks (WSNs) can be partitioned component sensor nodes (SNs) who are meant to operate and sense information arriving from multiple spectra in their environment. Determining where to place a single SN or multiple SNs such that the amount of information gained is maximized while the number of SNs used to gain that information is minimized is an instance of solving the art gallery problem (AGP). In order to solve the AGP, we present the Sensor Placement Optimization via Queries (SPOQ) algorithm that uses level sets populated by queries to a photon map in order to find observation points that sense as many photons as possible. Since we are using photon mapping as our means of modeling how information is conveyed, SPOQ can then take into account static or dynamic environmental conditions and can use exploratory or precomputed sensing. Unmanned vehicles can be designated more generally as UxVs where “x” indicates the environment they are expected to operate – either in the air, on the ground, underwater or on the water’s surface. Determining how to plan an optimal route by a single UxV or multiple UxVs operating in their environment such that the amount of information gained is maximized while the cost of gaining that information is minimized is an instance of solving the watchman route problem (WRP). In order to solve the WRP, we present the Photon-mapping-Informed active-Contour Route Designator (PICRD) algorithm. PICRD heuristically solves the WRP by utilizing SPOQ’s AGP-solving vertices and connecting them with the high visibility vertices provided by a photon-mapping informed Chan-Vese segmentation mesh using a shortest-route path-finding algorithm. Since we are using photon-mapping as our foundation for determining sensor coverage by the PICRD algorithm, we can then take into account the behavior of photons as they propagate through the various environmental conditions that might be encountered by a single or multiple UxVs

Realization of Underwater Acoustic Networks.

This work contains a study of underwater acoustic networks. The concept of underwater acoustic networks has been presented with its benefits and drawbacks. An overview of the marine research areas oceanography, seismology, waterside security, marine pollution and marine biology has been made and a review of conventional methods and instrumentation committed. The research methods used today have been compared with the potential of underwater acoustic networks as a platform for maritime applications. Underwater acoustic networks were reviewed as feasible within all areas with some restrictions. The fact that respectable data rate is best achieved for nodes deployed in a high density grid give limitations on the coverage area. Battery as an energy source limits the life span of an underwater acoustic network and makes it best suited for missions for short term monitoring, if not a recharging technology is applied. The energy restrictions also put constraint on the amount of sensing done and the temporal solution in measurements. Underwater acoustic networks were found applicable for intrusion detection in waterside security to increase the range of current ultrasonic surveillance systems or realize distributed systems for passive diver detection. In oceanography and pollution monitoring current in situ sensors may enable underwater acoustic networks to do autonomous synoptic sampling of limited areas to measure a number of parameters, e.g. oxygen, turbidity, temperature and salinity. For seismic exploration this technology might save costs for permanent seismic installations in constant monitoring of producing oil fields. It might also aid marine biologists in habitat monitoring

Void Avoiding Opportunistic Routing Protocols for Underwater Wireless Sensor Networks: A Survey

One of the most challenging issues in the routing protocols for underwater wireless sensor networks (UWSNs) is the occurrence of void areas (communication void). That is, when void areas are present, the data packets could be trapped in a sensor node and cannot be sent further to reach the sink(s) due to the features of the UWSNs environment and/or the configuration of the network itself. Opportunistic routing (OR) is an innovative prototype in routing for UWSNs. In routing protocols employing the OR technique, the most suitable sensor node according to the criteria adopted by the protocol rules will be elected as a next-hop forwarder node to forward the data packets first. This routing method takes advantage of the broadcast nature of wireless sensor networks. OR has made a noticeable improvement in the sensor networks’ performance in terms of efficiency, throughput, and reliability. Several routing protocols that utilize OR in UWSNs have been proposed to extend the lifetime of the network and maintain its connectivity by addressing void areas. In addition, a number of survey papers were presented in routing protocols with different points of approach. Our paper focuses on reviewing void avoiding OR protocols. In this paper, we briefly present the basic concept of OR and its building blocks. We also indicate the concept of the void area and list the reasons that could lead to its occurrence, as well as reviewing the state-of-the-art OR protocols proposed for this challenging area and presenting their strengths and weaknesses

A NEW ENERGY EFFICIENT ADAPTIVE HYBRID ERROR CORRECTION TECHNIQUE FOR UNDERWATER WIRELESS SENSORS NETWORKS

Underwater wireless sensors networks find many applications in today's life. However underwater sensors are still relatively expensive. They suffer from short lifetime which is limited by batteries lifetime as it is difficult to recharge or even replace batteries in harsh aquatic medium. When the battery is depleted the sensor is of no use anymore. So designing energy efficient communication protocols is an important issue for underwater sensors networks. Underwater is characterized by variable channel conditions, whereas underwater sensors are mobile due to water currents leading to variable distances between sensors. This variability in channel conditions and distances between sensors leads to inefficiency in energy consumptions when using fixed type of error correction technique. In this thesis, a mathematical energy efficiency derivations for the two main error correction techniques (Automatic Repeat request (ARQ) and Forward Error Correction (FEC)) in underwater environment has been done. The results from those derivations show that one technique is more energy efficient than the other below specific distance, where as the other is more energy efficient after this distance. This specific distance is found to be unfixed and varies with the variation in channel conditions and packet size. So using fixed error correction technique for specific distance is not accurate. Simulation has been done which validate the mathematical derivations. Based on the above derivation results Adaptive Hybrid Error Correction (AHEC) technique which adaptively changes the error correction technique to the technique that gives the highest energy efficiency for the current channel conditions and distances has been proposed. The technique uses an adaptation algorithm which depends on a pre-calculated packet acceptance rate (PAR) ranges look-up table, current PAR, packet length and current error correction technique used. AHEC viii technique has been found to have better energy saving compared with the techniques that depend on pure ARQ or FEC only. This saving ranges from 10 to 70 % in energy saving in ARQ case , and 7 to 10 % in energy saving in FEC case depending on current channel conditions and distance .It has also been compared with the technique that uses variable power supply in adaptation (Adaptive Variable Power Supply (AVPS)) and it achieves between 20 to 60 % in energy saving depending on current channel conditions and distance. It has also been compared with Adaptive Redundancy Reliable Transport Protocol (ARRTP), and it achieves between 10 to 80 % in energy saving depending on the current channel conditions and distance. The adaptation algorithm which depends on PAR has also been applied in adaptation to the ARRTP which originally depends only on inter-node distance in adaptation. PAR take both of distance and channel conditions into consideration. This technique is called PAR-based ARRTP, and the results shows better adaptation than the basic ARRTP in variable channel conditions cases. AHEC technique has also been applied with the bounded distance routing protocol to minimize the effects of variable channel conditions. Bounded distance routing protocol design depends on choosing specific number of relays between sender and receiver that minimize the total energy consumptions. This specific number of relays varies with the variation in channel conditions. The results show a deviation in number of relays from 6 when fixed error correction technique is used to only 2 when AHEC technique is used with it

EFFICIENT DYNAMIC ADDRESSING BASED ROUTING FOR UNDERWATER WIRELESS SENSOR NETWORKS

This thesis presents a study about the problem of data gathering in the inhospitable underwater environment. Besides long propagation delays and high error probability, continuous node movement also makes it difficult to manage the routing information during the process of data forwarding. In order to overcome the problem of large propagation delays and unreliable link quality, many algorithms have been proposed and some of them provide good solutions for these issues, yet continuous node movements still need attention. Considering the node mobility as a challenging task, a distributed routing scheme called Hop-by-Hop Dynamic Addressing Based (H2- DAB) routing protocol is proposed where every node in the network will be assigned a routable address quickly and efficiently without any explicit configuration or any dimensional location information. According to our best knowledge, H2-DAB is first addressing based routing approach for underwater wireless sensor networks (UWSNs) and not only has it helped to choose the routing path faster but also efficiently enables a recovery procedure in case of smooth forwarding failure. The proposed scheme provides an option where nodes is able to communicate without any centralized infrastructure, and a mechanism furthermore is available where nodes can come and leave the network without having any serious effect on the rest of the network. Moreover, another serious issue in UWSNs is that acoustic links are subject to high transmission power with high channel impairments that result in higher error rates and temporary path losses, which accordingly restrict the efficiency of these networks. The limited resources have made it difficult to design a protocol which is capable of maximizing the reliability of these networks. For this purpose, a Two-Hop Acknowledgement (2H-ACK) reliability model where two copies of the same data packet are maintained in the network without extra burden on the available resources is proposed. Simulation results show that H2-DAB can easily manage during the quick routing changes where node movements are very frequent yet it requires little or no overhead to efficiently complete its tasks

A multi-modal smart sensing network for marine environmental monitoring

There is an imperative need for long-term, large-scale marine monitoring systems that will allow decisions to be made based on the analysis of collected data to avoid or limit negative impacts on the ecosystem. Modern marine environmental sensing technologies, such as autonomous wireless sensor networks (WSNs), provide the capability to meet the challenges of high spatial and temporal scales. However, the significant amount of data generated from WSNs is a significant challenge for manual analysis. These multitudinous data need to be automatically processed, indexed and catalogued in a smarter way that can be more easily understood, accessed and managed by operators, scientists and policy makers. Moreover, current research works show that WSNs have their own limitations, for example, reliability issues and the fact that they are passive systems and provide context-less data. Thus, it is becoming increasingly clear that in order to adequately monitor marine environments, they need to be characterised from multiple perspectives. Combining multiple technologies and sensing modalities in environmental monitoring programmes can provide not only advantages of reliability and robustness for sensing systems, but also enhanced understanding of environmental processes. In addition, considerable advances can be made if robust sensing technology can be combined with sophisticated methods of data analysis, classification and cataloguing. The aim of this work is to bridge the gap between current aquatic monitoring systems and futuristic ideal large scale multi-modality smart sensing networks for marine environmental monitoring. To illustrate this, a smart sensing system is proposed and two case studies are used to show data processing from in-situ measurements and from camera based visual sensing data automatically using machine learning techniques. Abnormal events detection results from an in-situ sensor and shipping traffic detection results from visual sensor are combined to illustrate the benefit of coupling multiple sensing modalities