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Despite extensive research efforts, underwater sensor networks (UWSNs) still suffer from serious performance issues due to their inefficient and uncoordinated channel access and resource management. For example, due to the lack of holistic knowledge on the network resources, existing decentralized routing protocols fail to provide globally optimal performance. On the other hand, Software Defined Networking (SDN), as a promising paradigm to provide prominent centralized solutions, can be employed to address the aforementioned issues in UWSNs. Indeed, SDN brings unprecedented opportunities to improve the network performance through the development of advanced algorithms at controllers. In this paper, we study the routing problem in such a network with new features including centralized route decision, global network-state awareness, seamless route discovery while considering the optimization of several long-term global performance metrics. We formulate the entire routing problem of a multi-modal UWSN as an optimization problem while considering the interference phenomenon of ad hoc scenarios and some long-term global performance metrics of an ideal routing protocol. Our formulated problem nicely captures all possible flexibilities of a sensor node no matter it has the full-duplex or half-duplex functionality. Upon the formulation, we recognize the NP-hard nature of the problem for all possible scenarios. We adopt a rounding technique based on the convex programming relaxation concept to solve the formulated routing problem that considers full-duplex scenarios, whereas we solve the problem for half-duplex scenarios using a greedy method upon interpreting it as a submodular function maximization problem. Through extensive simulation via our Python-based in-house simulator, we verify that our proposed globally optimal routing scheme always outperforms three existing decentralized routing protocols (each of these protocols are selected from each of three prominent protocol types, i.e., flooding, cross-layer information and adaptive machine learning based, respectively) in terms of reliability, latency, energy efficiency, lifetime and fairness.

QUasi-Affine TRansformation Evolutionary algorithm (QUATRE) is a new optimization algorithm based on population for complex multiple real parameter optimization problems in real world. In this paper, a novel multi-group multi-choice communication strategy algorithm for QUasi-Affine TRansformation Evolutionary (MM-QUATRE) algorithm is proposed to solve the disadvantage that the original QUATRE is always easily to fall into local optimization in the strategy of updating bad nodes with multiple groups and multiple choices. We compared it with other intelligent algorithms, the most advanced PSO variant, parallel PSO (P-PSO) variant, native QUATRE and parallel QUATRE (P-PSO) under CEC2013 large-scale optimization test suite. Thus, the performance of MM-QUATRE was verified. The conclusion that the MM-QUATRE algorithm is superior to other intelligent algorithms is proved by the experimental results. In addition, the application results of MM-QUATRE algorithm (MM-QUATRE-RSSI) based on RSSI in WSN node localization were analyzed and studied. The results appear that this method has higher localization accuracy than other similar algorithms.

Underwater sensor networks would reap multiple benefits by extending the principles of software-defined networking (SDN) to it, such as programmable and reconfigurable network, enhanced network management and efficiency. However, there are several challenges need to be tackled in the SDN-enabled underwater network design process, especially for underwater mobile networks. Different from the terrestrial wireless sensor networks (WSNs), it is difficult to implement reliable centralized control as underwater wireless sensor networks (UWSNs) typically operate in the harsh ocean environment via band-limited acoustic channels. To cope with the problem, in this paper, we explore hybrid solutions and try to reap advantages of both centralized and distributed control. We proposed a semi-centralized control model for multi-modal mobile autonomous underwater vehicle (AUV) networks which are equipped with multiple communication systems (e.g., optical and acoustic). We present the initial research of the network model and the intelligent control architecture, and hope to inspire more research in the SDN-based mobile multi-modal AUV networks.

Underwater sensor networks have many applications ranging from ocean monitoring, undersea exploration, target tracking, coastal surveillance, to disaster prevention. In multi-application scenarios, the network might need to handle different types of packets to satisfy the requirements of diverse data transmission metric. For example, multimedia-based applications may include different multimedia packets, such as voice, compressed images, even video streams with different quality of experience. To meet the requirements of such applications, in this paper, we propose a hybrid adaptive routing scheme (HARS) for drifting restricted floating ocean sensor networks (DR-OSNs), which exploits both surface wireless and underwater communication channels to fulfill different performance requirements. We evaluate the performance of the routing scheme and investigate the factors which affect the scheme. The simulation results demonstrate that the scheme achieves a reasonable performance for different communication channels and packet delivery.

Ocean sensor networks have many applications ranging from oceanographic data collection, pollution monitoring, disasters prevention to tactical surveillance. However, due to the harsh ocean environment, it is difficult to deploy three-dimensional sensor networks underwater for sustainable monitoring tasks. In this paper, we propose a novel floating three-dimensional sensor networks for ocean monitoring and surveillance applications, which leverage nodes' restricted movement to enlarge the monitoring area. The networks are deployed on both the surface of the ocean and underwater, with many chains of nodes attached to mooring lines. Compared with deployments requiring self-adjusted nodes, our scheme is simpler and more cost-efficient, and the sustainable monitoring cost is low. We design deployment strategies, and provide in-depth mathematical analysis for network coverage. Then we derive the minimum number of sensors to achieve full surface coverage. Evaluated by simulations of a few underwater scenarios, the effectiveness and efficiency of the proposed scheme is proved.

Surveillance is a critical problem for harbor protection, border control or the security of commercial facilities. The effective protection of vast near-coast sea surfaces and busy harbor areas from intrusions of unauthorized marine vessels, such as pirates smugglers or, illegal fishermen is particularly challenging. In this paper, we present an innovative solution for ship intrusion detection. Equipped with three-axis accelerometer sensors, we deploy an experimental Wireless Sensor Network (WSN) on the sea's surface to detect ships. Using signal processing techniques and cooperative signal processing, we can detect any passing ships by distinguishing the ship-generated waves from the ocean waves. We design a three-tier intrusion detection system with which we propose to exploit spatial and temporal correlations of an intrusion to increase detection reliability. We conduct evaluations with real data collected in our initial experiments, and provide quantitative analysis of the detection system, such as the successful detection ratio, detection latency, and an estimation of an intruding vessel's velocity.

Ocean covers nearly 71 % of our planet’s surface and deploying wireless sensor networks on the sea can perform monitoring tasks over the oceans. With some applications, we may deploy sensors both on the sea surface and underwater which forms a Hybrid Ocean Sensor Networks (HOSNs). In this paper, we discussed a localization scheme with the hybrid wireless sensor networks which combines the advantages of Wireless sensor networks (WSNs) and Underwater acoustic-sensor networks (UWA-SNs). We first introduced the structure of the hybrid wireless sensor networks and its applications, then we discussed a localization schemes MLA for moored nodes deployed underwater. We present the related work and finally discussed our future research of the hybrid ocean wireless sensor networks.

Surveillance is a vital problem for harbor protection, border control or the security of other commercial facilities. It is particularly challenging to protect the vast near-coast sea surface and busy harbor areas from intrusions of unauthorized marine vessels, such as trespassing boats and ships. In this paper, we present an innovative solution for ship intrusion detection. Equipped with three-axis accelerometer sensors, we deploy an experimental wireless sensor network on the sea surface to detect ships. Using signal processing techniques and cooperative signal processing, we can detect the passing ships by distinguishing the ship-generated waves and the ocean waves. We design an intrusion detection system in which we propose to exploit spatial and temporal correlations of the intrusion to increase detection reliability. We conduct evaluations with real data collected by our initial experiments, and provide quantitative analysis on the detection system, such as the successful detection ratio and the estimation of the intruding ship velocity.

Underwater acoustic sensor networks (UWA-SNs) are envisioned to perform monitoring tasks over the large portion of the world covered by oceans. Due to economics and the large area of the ocean, UWA-SNs are mainly sparsely deployed networks nowadays. The limited battery resources is a big challenge for the deployment of such long-term sensor networks. Unbalanced battery energy consumption will lead to early energy depletion of nodes, which partitions the whole networks and impairs the integrity of the monitoring datasets or even results in the collapse of the entire networks. On the contrary, balanced energy dissipation of nodes can prolong the lifetime of such networks. In this paper, we focus on the energy balance dissipation problem of two types of sparsely deployed UWA-SNs: underwater moored monitoring systems and sparsely deployed two-dimensional UWA-SNs. We first analyze the reasons of unbalanced energy consumption in such networks, then we propose two energy balanced strategies to maximize the lifetime of networks both in shallow and deep water. Finally, we evaluate our methods by simulations and the results show that the two strategies can achieve balanced energy consumption per node while at the same time prolong the networks lifetime.

In this paper, we present a practical wireless sensor network for environmental monitoring (OceanSense) deployed on the sea. The system is mainly composed of TelosB motes, which are deployed on the surface of the sea collecting environmental data, such as temperature, light and RSSI from the testbed. The motes communicate with a base station, which transmits collected data to a visualization system running on a database server. The data can be accessed using a browser-based web application. The OceanSense has been running for more than half a year, providing environmental monitoring data for further study.

Underwater sensor networks (UWSN) are widely used in many applications, such as oceanic resource exploration, pollution monitoring, tsunami warnings and mine reconnaissance. In UWSNs, determining the location information of each sensor node is a critical issue, because many services are based on the localization results. In this paper, we introduce a novel underwater localization approach based on directional signals, which are transmitted by an autonomous underwater vehicle (AUV). Our method utilizes directional beacons (UDB) to replace traditional omni-directional localization which provides more accurate and efficient ways to locate the sensors themselves by simple calculations. The advantage of this novel scheme is that the communications between AUV and sensors are not necessary because the AUV broadcasts signals and sensors only need to passively listen to the signals. Since the energy consumption for transmissions in underwater environments is a nontrivial factor, our localization scheme not only supports accurate positioning, but also reduces energy consumption of sensors. We evaluate our scheme by simulations. The results show that our new approach is very precise in a strap area. At the same time, we minimize the number of beacons issued from the AUV.

Wireless sensor networks have been applied to monitor pipeline structural health. In these networks, expensive multi-sinks with energy harvesting modules are deployed along the linear pipeline, and battery powered sensor nodes are deployed between the sinks. One of the main problems in such networks is the unbalance of energy consumption of sensor nodes, which makes the whole monitoring system lose its functionality with only a small percentage of sensor nodes depleted of their energy. In this paper, we propose a distributed sensing data propagation algorithm based on graded residual energy (GRE) of the sensor nodes, in order to achieve balanced energy consumption among sensor nodes. The optimum number of energy grades of GRE has been calculated through theoretical analysis in terms of maximizing network lifetime. The simulation results have shown that GRE can achieve balanced energy consumption between the sensor nodes and at the same time prolong the lifetime of the whole monitoring system.