Data collection, storage, and retrieval with an underwater sensor network

Underwater Sensor Networks (UWSNs) are significantly different from terrestrial sensor networks in the following aspects: low bandwidth, high latency, node mobility, high error probability, and 3-dimensional space. These new features bring many challenges to the network protocol design of UWSNs. The communication range of underwater wireless sensor networks (UWSNs) is limited, and the nodes are equipped with limited power battery whose replacement is expensive due to underwater harsh environment. Moreover, the networks including small number of nodes have communication problems for long ranges. In this paper, we evaluate the performance of three classical location-based routing protocols (namely, VBF, HH-VBF, and VBVA) for underwater wireless sensor networks in terms of three critical performance metrics for dynamic network topology. Our comparison includes energy consumption, end-to-end delay, and packet delivery ratio.

Selection and navigation of mobile sensor nodes using a sensor network

Unknown target search, in an unknown environment, is a complex problem in Wireless Sensor Network (WSN). It does not have a linear solution when target’s location and searching space is unknown. For the past few years, many researchers have invented novel techniques for finding a target using either Static Sensor Node (SSN) or Mobile Sensor Node (MSN) in WSN i.e. Hybrid WSN. But there is a lack of research to find a solution using hybrid WSN. In the current research, the problem has been addressed mostly using non-biological techniques. Due to its complexity and having a non-linear solution, Bio-inspired techniques are most suited to solve the problem. This paper proposes a solution for searching of randomly moving target in unknown area using only Mobile sensor nodes and combination of both Static and Mobile sensor nodes. In proposed technique coverage area is determined and compared. To perform the work, novel algorithms like MSNs Movement Prediction Algorithm (MMPA), Leader Selection Algorithm (LSA), Leader’s Movement Prediction Algorithm (LMPA) and follower algorithm are implemented. Simulation results validate the effectiveness of proposed work. Through the result, it is shown that proposed hybrid WSN approach with less number of sensor nodes (combination of Static and Mobile sensor nodes) finds target faster than only MSN approach.

Study Framework: The system of geographical information (GIS) is a computerized method for collecting, storing, disseminating, querying, updating, processing and analyzing geographic data. (GIS) enables the collection of diverse spatial data from various sources and transforms it into an information board for multiple users to boost productivity. Intelligent techniques, remote sensing, and underwater Wireless sensor networks are applied to improve GIS dramatically. Remote sensing data sources for GIS come from underwater sensor networks, The implementation of effective sensing devices, intelligent mobile nodes, and a multi-hop routing system can facilitate the efficient and optimal routing of traffic towards the basin or base station. They have been using GIS, which has revolutionized response scenarios with its ability to collect, analyze and manipulate spatial points. The objective of the study: The aim of this research is to differentiate the significant routing protocol issues that are relevant to underwater sensor networks. These networks serve as key transceivers that have established mechanisms for seamless and efficient data transmission. The mechanisms: The article presented a performance evaluation simulation based on a comparison of five different routing protocols that perform to promote GIS execution. A rigorous comparison of the outcomes varied by five routing protocols, where it evaluated with random mobility UnderWater sensor model based on the varied network parameters, was performed to validate this work. The continued to improve results: The suggested study in this manuscript contains spatial-information services universal to routing protocols to aid a group of navigators in harsh circumstances. According to the findings of the study, the CTP-ABS-SEEC routing protocol demonstrated superior performance compared to the other four routing protocols (CTP-SEEC, SEEC, EEDBR, and DBR) in the specified network configuration.

Hybrid sensor network (HSN) is composed of a set of static and mobile sensor nodes. Besides the capabilities of sensing, computing and communicating like static nodes, mobile nodes have locomotion capability particularly. Area coverage is one of the most fundamental metrics for hybrid sensor network because it is crucial to the quality of monitoring. In order to improve the network coverage, we employ the mobility of mobile nodes to compensate for the uneven deployment of static sensors. In this paper we propose a 3-phase algorithm based on Hamilton Circuit. Conducted simulation shows that the algorithm can improve coverage performance with less energy conservation. Experimental results verify the feasibility and validity of the algorithm proposed.

Hybrid sensor networks consisting of both static and mobile sensor nodes attract more research interests with their enhanced capability. As mobile nodes generally have more power than static nodes, they are preferable to be used as cluster heads. In this paper, we study the mobile node deployment problem with the objective of maximizing the number of static nodes covered by the mobile nodes with minimized moving distance. We prove that this problem is NP-complete and propose a distributed deployment protocol to solve it. In the proposed protocol, different policies of selecting the moving nodes are considered to cover more static nodes with less moving distance. Simulation results show that the proposed protocol achieves high coverage ratio with acceptable moving distance.

Underwater sensor networks are physical networks containing acoustic,magnetic,and static electric field.It has got widely application in ocean data acquisition,pollution forecasting,ocean exploitation,and ocean supervision.And in future it will show its advantages in the battlefield.The state-of-the-art underwater wireless sensor networks are overviewed,and several typical structures of underwater wireless sensor networks are also described.Taking account of the requirements of underwater applications several fundamental key aspects in the design of underwater sensor networks,such as node localization,energy,source localization and other challenges are investigated.Finally open issues in underwater sensor networks are discussed.

In hybrid wireless sensor networks composed of both static and mobile sensor nodes, the random deployment of stationary nodes may cause coverage holes in the sensing field. Hence, mobile sensor nodes are added after the initial deployment to overcome the coverage holes problem. To achieve optimal coverage, an efficient algorithm should be employed to find the best positions of the additional mobile nodes. This paper presents a genetic algorithm that searches for an optimal or near optimal solution to the coverage holes problem. The proposed algorithm determines the minimum number and the best locations of the mobile nodes that need to be added after the initial deployment of the stationary nodes. The performance of the genetic algorithm was evaluated using several metrics, and the simulation results demonstrated that the proposed algorithm can optimize the network coverage in terms of the overall coverage ratio and the number of additional mobile nodes.

Monitoring of the sub-sea environment requires advanced sensor networks with both stationary and mobile nodes on the surface and underwater, each node playing a different role. The combination of mobile and stationary nodes, the loss of nodes due to harsh conditions, the difficult conditions for wireless sub-sea communication and the need for nodes to collaborate are all factors that require new approaches to software architectures for such nodes and systems. This articles presents work in progress that sets out to address these issues by adapting approaches from software engineering solutions to ubiquitous computing.

Water covers more than 70 % of the entire planet, contains much of its natural resources. With the increasing use of underwater sensors for the exploitation and monitoring of vast underwater resources, underwater wireless sensor network (UWSN), mostly based on acoustic transmission technologies, have been developing steadily in terms of operation range and data throughput. In an energy-constrained underwater system environment it is very important to find ways to improve the life expectancy of the sensors. Compared to the sensors of a terrestrial Ad Hoc Wireless Sensor Network (WSN), underwater sensors cannot use solar energy to recharge the batteries, and it is difficult to replace the batteries in the sensors. This paper reviews the research progress made to date in the area of energy consumption in underwater sensor networks (UWSN) and concentrates on developing routing algorithms that support energy efficiency. These algorithms are designed to carry out data communication while prolonging the operation time of WSNs.

Data collection is a fundamental and important issue in wireless sensor networks (WSNs). Recent research has shown that using mobile nodes to collect and carry data in WSNs has many advantages over static multi-hop routing. In this paper, we focus on the problem of data collection in WSNs with the minimum mobile nodes. A mobile node can pick up the data cached in a sensor node via one-hop wireless communications when it passes by a point that R meters away from this stationary sensor node. Since the storage capability of sensor node is limited, each mobile node must visit the sensor nodes, that assigned to it, every t seconds to avoid the overflow of sensor data. In order to reduce the cost of mobile nodes, we try to minimize the number of mobile nodes. We formally prove that the problem of minimizing the number of mobile nodes required by periodical data collection in WSNs is NP hard. We propose a path planning algorithm to minimize the number of mobile nodes. Our simulation results show that our approach can notably reduce the number of required mobile nodes as much as 55.6%.

A testbed for coverage control using mixed wireless sensor networks

Aiming at improving the localization accuracy, reducing network cost, and energy loss in the 3-D environment, this paper proposes a mobile node localization algorithm based on compressive sensing for underwater acoustic sensor networks (UASNs). By dividing the cubic module of the underwater monitoring area and using the energy between the mobile anchor node and the unknown nodes, the sparse localization problem based on the cubic module is transformed into the nodes localization problem based on compressive sensing. Since the energy localization between nodes based on cubic modularization is adopted, the path of the mobile node does not need to be specially designed, as long as the mobile beacon node traverses the entire cubic module. Considering the distance problem of the moving path, the mobile node path is based on the random waypoint (RWP) and the LAYERED-SCAN model. The simulation results show that the proposed algorithm can be applied to the node localization problem of UASNs. It can reduce network cost and node energy loss while obtaining higher localization accuracy.

This paper explores energy-efficient ways of retrieving data from underwater sensor fields using autonomous underwater vehicles (AUVs). Since AUVs are battery-powered and therefore energy-constrained, their energy consumption is a critical consideration in designing underwater wireless sensor networks. The energy consumed by an AUV depends on the hydrodynamic design, speed, on-board payload and its trajectory. In this paper, we optimise the trajectory taken by the AUV deployed from a floating ship to collect data from every cluster head in an underwater sensor network and return to the ship to offload the data. The trajectory optimisation algorithm models the trajectory selection as a stochastic shortest path problem and uses reinforcement learning to select the minimum cost path, taking into account that banked turns consume more energy than straight movement. We also investigate the impact of AUV speed on its energy consumption. The results show that our algorithm improves AUV energy consumption by up to 50% compared with the Nearest Neighbour algorithm for sparse deployments.

Owing to the rapid development of underwater applications, the research on underwater wireless sensor networks (UWSNs) is becoming more and more significant. Low bandwidth, high latency, limited energy and node float mobility are basic challenges for underwater sensor networks. Most of the theories for terrestrial sensor networks can not be applied to underwater sensor networks. In this paper, we focus on the localization and routing issues for dynamic UWSNs. Location based routing protocols can suit the dynamic situation of UWSNs well. However, most research assumes that the nodes know their locations, which may be not appropriate for some applications. This paper combines these two aspects together to design a localization based routing protocol for dynamic UWSNs. The simulation results show our method can effectively route data from the source nodes to the sink nodes in a dynamic environment.