Adaptive Fuzzy Game-Based Energy-Efficient Localization in 3D Underwater Sensor Networks

The characteristics of mobile underwater sensor networks (UWSNs), such as low communication bandwidth, large propagation delay, and sparse deployment, pose challenging issues for successful localization of sensor nodes. In addition, sensor nodes in UWSNs are usually powered by batteries whose replacements introduce high cost and complexity. Thus, the critical problem in UWSNs is to enable each sensor node to find enough anchor nodes in order to localize itself, with minimum energy costs. In this paper, an energy-efficient localization algorithm (EELA) is proposed to analyze the decentralized interactions among sensor nodes and anchor nodes. A single-leader-multi-follower Stackelberg game is utilized to formulate the topology control problem of sensor nodes and anchor nodes by exploiting their available communication opportunities. In this game, the sensor node acts as a leader taking into account factors such as “two-hop” anchor nodes and energy consumption, while anchor nodes act as multiple followers, considering their ability to localize sensor nodes and their energy consumption. We prove that both players select best responses and reach a socially optimal Stackelberg-Nash Equilibrium. Simulation results demonstrate that the proposed EELA improves the performance of localization in UWSNs significantly, and in particular, the energy cost of sensor nodes. Compared to the baseline schemes, the energy consumption per node is about 48% lower in EELA, while providing a desirable localization coverage, under reasonable error, and delay.

A mobicast, or called as mobile geocast, problem in three-dimensional (3D) underwater sensor networks (USNs) is investigated in this paper, which aims to overcome the hole problem and minimizes the energy consumption of the sensor nodes while maximizing the data collection. In this work, all underwater sensor nodes are randomly distributed in a 3D underwater environment in the sea to form a 3D USN. Considered a mobile sink or an AUV (autonomous underwater vehicle), all possible sensor nodes near to the AUV form a 3D geographic zone (called as 3D zone of reference or 3D ZOR). The AUV travels a user-defined route and continuously collects data form sensor nodes within a series of 3D ZORs at different time. The main problem is how to efficiently collect data from sensor nodes within a 3D ZOR while those sensor nodes are usually in sleep mode for a long period of time. The routing protocol relies on two phases; the first phase is to collect data form sensor nodes within a 3D ZOR, and the second phase is to wake up those sensor nodes in the next 3D ZOR to be queried while trying to avoid topology holes. To save power, only sensor nodes in a 3D ZOR are notified to enter the active mode in order to deliver sensed results to the AUV. To consider the characteristics of USNs, a new mobicast routing protocol is developed in 3D USNs. The key design challenge is to develop a power-saving mobicast protocol in 3D USNs to overcome the unpredictable 3D hole problem. An ”apple slice” technique is used to build multiple segments to surround a hole and to assure routing path continuity. Finally, performance analysis is derived and simulation results illustrate the performance improvement in successful delivery rate and power consumption.

The problem of localization in under water sensor nodes has led to proposal of many techniques over the past few decades that depend primarily on Time of Arrival and Time Difference of Arrival. While these techniques are intuitively very appealing and easy to deploy, accurate node localization in dynamic under water environment has remained elusive. Sensor nodes deployed underwater tend to move from their original positions due to water currents and hence their exact positions at a given moment of time are not known with precision. Due to inherent drawbacks of radio signal propagation in underwater environment, localization of sensor nodes depends on acoustic signals. In this paper, we propose a Doppler shift based localization followed by a genetic algorithm based optimization technique that improves accuracy in localizing unknown nodes in underwater sensor networks. The proposed technique envisages sink nodes playing a pivotal role in taking over a bulk of the computational load on account of being comparatively more accessible and serviceable as compared to any other nodes in the network that are deployed underwater. The algorithm relies on observed frequency shifts (Doppler shift) of sound waves compared to actual, that happen when source and observer are mobile as they do in a marine environment. While Doppler shift determines the approximate location of an unknown sensor node, genetic algorithm minimizes the error in localization. Our proposed methodology has much lower localization error as compared to existing protocols.

Localization and correction of location information for nodes in UWSN-LCLI

Underwater sensor networks (UWSN) transpires as a powerful technique in marine monitoring that includes various applications such as oceanographic data collection, marine surveillance and pollution detection. Localization in UWSN is very challenging as the sensor nodes are in a 3D space and are always in passive movement. Thus providing scalable and efficient energy aware routing services and localization schemes has always been provocative. Depth based routing (DBR) is one of the routing protocols that has been in use to attend to the existing constraints of UWSN. Unlike most of the routing protocols that require full dimensional location information of the sensor nodes, DBR needs only the depth information for routing. Also an energy-efficient game theoretic model based on Single-leader-multi-follower Stackelberg game that follows a socially optimal Stackleberg-Nash-Cournot Equilibrium has been in use for topology control of unlocalized and localized sensor nodes that are closed to the surface. A cross layer UWSN architecture for marine environment monitoring is proposed that uses the adaptive neuro fuzzy based interference system to determine the depth of the sensor nodes and the game theoretic model for localization of the sensor nodes at the upper hull of the sea. Using the depth DBR protocol reports the events to the localized sensor nodes that are close to the sea surface which in turn forwards the reported events to the sink. This cross layer UWSN architecture proves to be energy efficient and apt for marine environment monitoring. The architecture is structured and simulated in Aqua-Sim.

SummaryThe issue of underwater sensor network (UWSN) localization has led to the aim of techniques presented in recent years. In this paper, we develop Doppler shift with Archimedes Optimization Algorithm for localizing unknown nodes in UWSN. The projected method predicts that sink node plays a major function in managing the computational load contrasted with the remaining nodes in the network of underwater. This node localization is proceeding with frequency shifts of sound waves contrasted toward real, which are present once observer in addition source can be mobile as they do in a marine atmosphere. The proposed technique is utilized to compute the estimated position of an unknown sensor node; here Archimedes' optimization algorithm is utilized to reduce the error during localization of nodes in UWSNs. This proposed technique can be enhancing the accuracy of the localization of nodes in UWSNs. This proposed methodology can be implemented and evaluated with the help of performance metrics. To validate the proposed technique's efficiency, it is contrasted with conventional techniques like Particle Swarm Optimization (PSO) and Whale Optimization Algorithm (WOA).

Underwater environments are quite different from terrestrial environments in terms of the communication media and operating conditions associated with those environments. In underwater sensor networks, the probability of node failure is high because sensor nodes are deployed in harsher environments than ground-based networks. The sensor nodes are surrounded by salt water and moved around by waves and currents. Many studies have focused on underwater communication environments in an effort to improve the data transmission throughput. In this paper, we present a checkpointing scheme for the head nodes to quickly recover from a head node failure. Experimental results show that the proposed scheme enhances the reliability of the networks and makes them more efficient in terms of energy consumption and the recovery latency compared to the previous scheme without checkpointing.

Underwater wireless sensor networks provide a new remote surveillance way to monitor the underwater environment, and have drawn increasing attention in the past few years from both academic and industry. Underwater sensor networks will find applications in oceanographic data collection, ocean sampling, pollution and environmental monitoring, offshore exploration, disaster prevention, assisted navigation, distributed tactical surveillance, mine reconnaissance, and submarine surveillance. Plenty of challenges have to be faced during the research, since the nature of underwater environment variable temporally and spatially. In this paper, the efficient deployment of surface area for underwater wireless sensor networks was presented. To familiarize with underwater wireless sensor networks deployment, this paper started by providing background information on the architecture and trajectory of the sinking node. Then, a kind of novel inflatable sensor nodes was proposed to make sure that they can have a given trajectory, according to the analysis sinking process of the sensor nodes which tie to the anchor with winch. For a given target area, the reducing of surface deployment area and numbers of nodes is the most significant advantage. To illustrate the performance, the compare was made from two aspects.

Underwater sensor networks are becoming a new field, mainly applied for ocean data collection, ocean sampling, environmental and pollution monitoring, etc. Similar to terrestrial sensor networks, it is essential to provide communication coverage in such a way that the whole monitoring area is covered by the sensor nodes in UWSN. Many important deployment strategies for terrestrial sensor networks have been proposed, most of which cannot be directly applied to UWSN due to its unique 3D characteristics. This paper surveys the different deployment algorithms that can be applied to the domain of UWSN, classified into 3D underwater sensor networks, 2D underwater sensor networks and gateway node deployment. Different schemes are compared and their advantages and disadvantages are discussed.

Underwater acoustic sensor networks typically comprised of sensor nodes that are deployed in sufficiently large numbers for data collection, monitoring and surveillance. Multi-hop relay transmission manner is used to deliver acquired data from sensor nodes to the sink node; nevertheless, hot spots around sink node will bring severe problems. In underwater sensor networks model of this paper, nodes are divided into two components: static sensor nodes and mobile UUV (Underwater Unmanned Vehicles), i.e., conventional sink node is replaced by mobile UUV. The mobile UUV in this novel framework takes charge of collecting sensory data from different sensor nodes and delivering all the sensory data to the monitoring center. Comparing with traditional model of underwater sensor networks, it is beneficial to use mobile UUV to ferry sensory information instead of using multi-hop relay transmission method, because the energy of sensor nodes in harsh oceanic environment is very limited. In order to improve energy efficiency, we therefore proposed a novel UUV mobility management scheme for underwater acoustic sensor networks that aims to achieve robustness and energy efficiency under harsh underwater acoustic channel conditions. The proposed mobility management scheme determines UUV movement routing using directional metric functions considering location information and energy level of sensor nodes. Furthermore, a hierarchical model based on cluster structure is induced where sensor nodes are grouped into clusters after they are deployed, therefore, UUV will only collect fused data of cluster heads but not every cluster members, thus to simplify route of UUV. Finally, the simulation results verified the efficacy of the proposed mobility management scheme.

Underwater Sensor Networks (UWSNs) provide valuable data for research studies and underwater monitoring and protection. UWSNs need to overcome the handicap that high data rate wireless transmissions are not available underwater. Acoustic communications are used as a medium but they are only good for transmitting e.g. signalling information. Autonomous Underwater Vehicles (AUVs) can serve as mobile sinks that gather and deliver larger amounts of data from the underwater sensor network nodes. Value of Information (VoI) is a data tag that encodes the importance and time-based-relevance of a data chunk residing at a sensor node. VoI, therefore, can serve as a heuristic for path planning and prioritizing data retrieval from nodes. The novelty of this paper lies in providing algorithms which schedule multiple mobile sinks (AUVs) for data retrieval from nodes while maximizing the retrieved VoI. The class of algorithms discussed are based on greedy heuristics.

In this paper, the proposed approach efficiently reduces the energy consumption in Mobicast routing protocol for 3D underwater sensor networks (USN). Many numbers of sensor nodes exist in the 3-D USN, which are deployed in the 3-D environment and sensor nodes be buoyant at dissimilar profound to monitor a specific phenomenon. The autonomous underwater vehicle (AUV) travels along a path which is defined by the user to fetch the sensing data from an underwater sensor node. The Mobicast routing protocol for underwater sensor networks is used to afford a spatiotemporal solution for the underwater sensor networks and also it provides an efficient data collection and an energy saving routing protocol for the USN. The proposed approaches use a static sensor node which collects the gathered data from other nodes in its region and send these collected data to AUV when it enters 3-D ZOR, thereby reducing the energy used for transmission. The performance is analyzed and simulation result of new Mobicast protocol shows that the sufficient data delivery rate and low energy consumption.

Time synchronization is a cooperative work's foundation among underwater sensor networks' nodes; it takes a crucial role in the application and the study of underwater sensor networks. Several time synchronization protocols have been presented for terrestrial radio networks, but they cannot be instantly utilized to real-time underwater sensor networks due to the slow propagation speed of the underwater acoustic signals, the mobility among sensor nodes, and the energy limitation in the underwater wireless sensor networks. In this paper, we propose an adaptive power-efficient time synchronization for mobile underwater sensor networks, called APE-Sync. The proposed scheme takes into account the time-varying clock skew and combines the Doppler-Enhanced synchronization protocol (DE-Sync) and the Kalman filter tracking the clock skew to achieve time synchronization. The proposed scheme also helps in reducing the energy consumption of the nodes by guaranteeing accurate time synchronization. The simulation results are presented, which show that APE-Sync outperforms existent time synchronization schemes in both power efficiency and precision.

In this paper, we investigate a mobicast, also called a mobile geocast, problem in three-dimensional (3-D) underwater sensor networks (USNs), which aims to overcome the hole problem and minimizes the energy consumption of the sensor nodes while maximizing the data collection. In this paper, all underwater sensor nodes are randomly distributed in a 3-D underwater environment in the sea to form a 3-D USN. Considered a mobile sink or an autonomous underwater vehicle (AUV), all possible sensor nodes near the AUV form a 3-D geographic zone called a 3-D zone of reference (3-D ZOR). The AUV travels a user-defined route and continuously collects data from sensor nodes within a series of 3-D ZORs at different times. The main problem is how to efficiently collect data from sensor nodes within a 3-D ZOR while those sensor nodes are usually in sleep mode for a long period. The routing protocol relies on two phases: the first phase consists of collecting data within a 3-D ZOR, and the second phase consists of waking up those sensor nodes in the next 3-D ZOR to be queried while trying to avoid topology holes. To save power, only sensor nodes in a 3-D ZOR are notified to enter the active mode in order to deliver sensed results to the AUV. The specific characteristics of USNs, including low communication bandwidth, large propagation delay, and ocean current, are significantly different from wireless sensor networks. To consider the characteristics of USNs, a new mobicast routing protocol is developed in 3-D USNs. The key design challenge is to develop a power-saving mobicast protocol in 3-D USNs to overcome the unpredictable 3-D hole problem. To solve the hole problem, an “apple slice” technique is used to build multiple segments to surround the hole and to assure routing path continuity. Finally, performance analysis is derived, and simulation results illustrate the performance improvement in successful delivery rate, power consumption, and message overhead.

The deployment of sensors is of importance in underwater wireless sensor networks (UWSNs) in the area of underwater short distance communication. Aiming at the problem of blind coverage and excessive energy consumption in the deployment of sensors in UWSNs, from the perspective of no vulnerability coverage monitoring area and on the basis of current coverage control method, mobile sensor nodes are introduced to double cover the target area around the UWSNs’ coverage control, and the double-coverage algorithm based on the deployment of mobile sensors is proposed. Firstly, the sensor node sensing model is established and the target area is divided into grid. Further, the deployment of mobile nodes is modeled and analyzed on the basis of the divided grid. Then the sensor node mobility model is designed and the double-coverage algorithm based on sensor node deployment is proposed. Finally, the rationality and effectiveness of the proposed algorithm is verified by simulation experiments. The simulation results show that the proposed algorithm can reduce the number of mobile nodes, which save the cost. At the same time, the energy consumption of sensor nodes is reduced as well under the same conditions and to a certain extent, the average energy consumption of mobile nodes in the network is evenly distributed. The algorithm effectively improves the coverage quality of UWSNs and greatly prolong the network lifetime.