A Novel Deployment Scheme Based on Three-Dimensional Coverage Model for Wireless Sensor Networks

Coverage pattern and deployment strategy are directly related to the optimum allocation of limited resources for wireless sensor networks, such as energy of nodes, communication bandwidth, and computing power, and quality improvement is largely determined by these for wireless sensor networks. A three-dimensional coverage pattern and deployment scheme are proposed in this paper. Firstly, by analyzing the regular polyhedron models in three-dimensional scene, a coverage pattern based on cuboids is proposed, and then relationship between coverage and sensor nodes’ radius is deduced; also the minimum number of sensor nodes to maintain network area’s full coverage is calculated. At last, sensor nodes are deployed according to the coverage pattern after the monitor area is subdivided into finite 3D grid. Experimental results show that, compared with traditional random method, sensor nodes number is reduced effectively while coverage rate of monitor area is ensured using our coverage pattern and deterministic deployment scheme

E2MR:Energy Efficient Multipath Routing Protocol for Underwater Wireless Sensor Networks

Exploration of underwater resources, oceanographic data collection, tactical surveillance and natural disaster prevention are some of the areas of Underwater Wireless Sensor Network(UWSN) applications. UWSN is different from traditional wireless sensor network. The later uses radio waves for communication between sensors while the former uses acoustic waves for data transmission. Communication through UWSN is more challenging because of the many challenges associated with acoustic channels such as low bandwidth, high transmission delay, usual path loss and intermittent connectivity. In UWSN, some algorithms were introduced to enhance the lifetime of networks, by using a smaller battery and other for critical data transmission. However, data packets flooding, path loss and low network lifetime are few challenges with immediate attention. This study proposes a novel routing scheme referred to as the energy-efficient multipath routing (E2MR) for UWSN, which is basically designed for long-term monitoring with higher energy efficiency and delivery ratio. The E2MR establishes a priority table, and the forward nodes are selected based on that priority table. Different experiments are carried out by simulating E2MR and compared with Depth-Based Routing (DBR), EEDBR and H2-DAB with respect to the number of live nodes, end-to-end delay, packet delivery ratio and total energy consumption

An enhanced evolutionary algorithm for requested coverage in wireless sensor networks

Wireless sensor nodes with specific and new sensing capabilities and application requirements have affected the behaviour of wireless sensor networks and created problems. Placement of the nodes in an application area is a wellknown problem in the field. In addition, high per-node cost as well as need to produce a requested coverage and guaranteed connectivity features is a must in some applications. Conventional deployments and methods of modelling the behaviour of coverage and connectivity cannot satisfy the application needs and increase the network lifetime. Thus, the research designed and developed an effective node deployment evaluation parameter, produced a more efficient node deployment algorithm to reduce cost, and proposed an evolutionary algorithm to increase network lifetime while optimising deployment cost in relation to the requested coverage scheme. This research presents Accumulative Path Reception Rate (APRR) as a new method to evaluate node connectivity in a network. APRR, a node deployment evaluation parameter was used as the quality of routing path from a sensing node to sink node to evaluate the quality of a network deployment strategy. Simulation results showed that the behaviour of the network is close to the prediction of the APRR. Besides that, a discrete imperialist competitive algorithm, an extension of the Imperialist Competitive Algorithm (ICA) evolutionary algorithm was used to produce a network deployment plan according to the requested event detection probability with a more efficient APRR. It was used to reduce deployment cost in comparison to the use of Multi-Objective Evolutionary Algorithm (MOEA) and Multi-Objective Deployment Algorithm (MODA) algorithms. Finally, a Repulsion Force and Bottleneck Handling (RFBH) evolutionary-based algorithm was proposed to prepare a higher APRR and increase network lifetime as well as reduce deployment cost. Experimental results from simulations showed that the lifetime and communication quality of the output network strategies have proven the accuracy of the RFBH algorithm performance

W-GUN: Whale Optimization for Energy and Delay centric Green Underwater Networks

Underwater Sensor Networks (UWSNs) has witnessed significant R&D attention in both academia and industries due to its growing application domain such as border security, freight via sea or river, natural petroleum production, etc. Considering the deep underwater oriented access constraints, energy centric communication for lifetime maximization of tiny sensor nodes in UWSNs is one of the key research themes in this domain. Existing literature on green UWSNs are majorly adapted from the existing techniques in traditional wireless sensor network without giving much attention to the realistic impact of underwater network environments resulting in degraded performance. Towards this end, this paper presents an adapted whale optimization algorithm-based energy and delay centric green UWSNs framework (W-GUN). It focuses on exploiting dynamic underwater network characteristics by effectively utilizing underwater whale centric optimization in relay node selection. Firstly, an underwater relay- node optimization model is mathematically derived focusing on whale and wolf optimization algorithms for incorporating realistic underwater characteristics. Secondly, the optimization model is used to develop an adapted whale and grey wolf optimization algorithm. Thirdly, a complete work-flow of the W-GUN framework is presented with the optimization flowchart. The comparative performance evaluation attests the benefits of the proposed framework as compared to the state-of-the-art techniques considering various metrics related to underwater network environments

THREE DIMENSIONAL REAL-TIME GEOGRAPHICAL ROUTING PROTOCOLS FOR WIRELESS SENSOR NETWORKS

One of the most important concerns in the operation of Wireless Sensor Network(WSN) is the real-time data delivery. This dissertation addresses the problem of real-time data delivery and void node problem in three dimensional WSN, which has a signicant impact on the network performance. In order to provide an accurate route calculation for reliable data delivery the third coordinate of the location sensor nodes is considered in this dissertation. Additionally, two dierent heuristic solutions for void node problem in three dimensional space have been provided to elevate the eect of long route and spares regions on assurance of real-time data delivery. In order to provide a wide applicable soft real-time routing protocol two decentralized geographical routings are proposed: Three Dimensional Real-Time Geographical Routing Protocol (3DRTGP) and Energy-Aware Real-Time Routing Protocol for Wireless Sensor Networks (EART). 3DRTGP and EART are designed to t with WSNs that are deployed in 3D space. Both protocols benet from utilizing the third coordinate of nodes\u27 locations to achieve less packet end to end (E2E) delay and packet miss ratio.In 3DRTGP, void node problem in 3D space was solved based on adaptive packet forwarding (PFR) region. 3D-VNP solution solely was done locally and without any messaging overhead. In EART, 3D-VNP was solved based on an adaptive spherical forwarding wedge (SFW)

Real-time measurement of wide-area near-surface ocean current

Of all of the physical parameters of the ocean realm, the speed and direction of the movement of ocean water, otherwise referred to as ocean “current,” is one of the most problematic to characterize. Currents influence the global climate, used for producing power, are crucial in determining the oil spill trajectories and ocean contaminant control, can either work against or with the movement of ships at sea and govern the movements of icebergs. Icebergs are a threat to offshore industries and marine transportations, particularly in places like the Northwest Atlantic, because of damages they can cause once they strike the oil platforms or ship hulls. They are steered by the near-surface current and not the surface current. Therefore, measurment of the real-time ocean currents at desired depths is valuable for the industries or researchers who are dealing with or studying the oceanographic data. Ocean current measurment methods that are currently being employed for ocean monitorings, are not able to measure the real-time current at certain desired depths over a larg area of the ocean. Thus, the existing current measurement methods need improvements. Limitations of the existing methods are as follows. Acoustic dopler current profilers (ADCP), are one of the most popular methods employed by most of the industries dealing with the oceanograghy. ADCPs are capable of measuring the current at any desired depth; however, their measurement method is of a point nature and they cannot measure an area averaged current data. Other techniques such as high frequency radio detecting and ranging systems (HF-RADAR) are also used to measure the surface currents (down to 15 m). These shore-based current meters with radio antenna, follow the same premise of the ADCP. In other words their measurement is dependant on the Doppler effect to determine the direction and velocity of the currents; however, they are capable of evaluating only the surface currents and not the near-surface currents (70-100 meter of depth is considered in this thesis as this is the depth oil structures are deployed in the Northwest Atlantic Ocean). Another group of instruments used for current measurement are floats and drifters which report their data to a centre device which is usually a satelite. The current data obtained with these instruments are fed into modeling systems, e.g. in (Chassignet, Hurlburt et al. 2006), for the ocean forcasting. The problems that exist with the available real-time current data from the satelite is that it is the very shallow current data (down to 15m that can be called surface). The data from other devices like floats is very sparse to include the horizontal information. Hence, Chassignet et al. use data assimilation of the past knowledge and ocean dynamics in order to predict the ocean features. Therefore, it is important to develop a method by which adequate data could be provided for the ocean prediction and modeling system. Thus, the focus of this thesis is on designing a method which is real-time and measures the near-surface current. On the other hand, energy suplies to the instruments in open water is limited as they work mainly rely on batteries and it is difficult to access the instruments in harsh condition to replace the batteries. Moreover, in cold regions the solar power is very limitted and thus using solar cells is not practical. Therefore, in order to measure the ocean current in real time, a novel method along with a sustainable architechture design is being proposed in this dissertation. The new method is based on transit time with the difference that in transit time method waves need to travel in both directions; up- and down-stream. But with a modification in the newly designed architecture; which is adding an extra node in the center of the network’s cells, sound waves need to travel on only one direction. This helps with saving a great amount of energy and covering a larger area in comparison with the networks which are developed using transit time method. Experimental results as well as simulations verify that the new proposed method is both efficient and practical

Decentralized Collision-Free Control of Multiple Robots in 2D and 3D Spaces

Decentralized control of robots has attracted huge research interests. However, some of the research used unrealistic assumptions without collision avoidance. This report focuses on the collision-free control for multiple robots in both complete coverage and search tasks in 2D and 3D areas which are arbitrary unknown. All algorithms are decentralized as robots have limited abilities and they are mathematically proved. The report starts with the grid selection in the two tasks. Grid patterns simplify the representation of the area and robots only need to move straightly between neighbor vertices. For the 100% complete 2D coverage, the equilateral triangular grid is proposed. For the complete coverage ignoring the boundary effect, the grid with the fewest vertices is calculated in every situation for both 2D and 3D areas. The second part is for the complete coverage in 2D and 3D areas. A decentralized collision-free algorithm with the above selected grid is presented driving robots to sections which are furthest from the reference point. The area can be static or expanding, and the algorithm is simulated in MATLAB. Thirdly, three grid-based decentralized random algorithms with collision avoidance are provided to search targets in 2D or 3D areas. The number of targets can be known or unknown. In the first algorithm, robots choose vacant neighbors randomly with priorities on unvisited ones while the second one adds the repulsive force to disperse robots if they are close. In the third algorithm, if surrounded by visited vertices, the robot will use the breadth-first search algorithm to go to one of the nearest unvisited vertices via the grid. The second search algorithm is verified on Pioneer 3-DX robots. The general way to generate the formula to estimate the search time is demonstrated. Algorithms are compared with five other algorithms in MATLAB to show their effectiveness