Despite the potential benefits of Internet of Underwater Things, a number of issues hinder its realization, including the need for communication reliability and cost-effectiveness. This study aims to optimize network design to implement cost-effective underwater acoustic sensor networks (UASNs) with three-dimensional (3D) topology while supporting diverse communication quality of service (QoS) requirements. First, we present an analytical framework based on a queueing system that evaluates communication performances of UASNs, wherein each underwater sensor distributed within a 3D space under the sea surface performs fountain code (FC)-based automatic repeat request (ARQ) transmissions under the slotted-Aloha medium access control protocol. Under the proposed framework, we evaluate communication performances given in terms of successful FC-based ARQ transmission probability and the average queueing delay of an underwater sensor. When evaluating the performances, we formulate the service time of each underwater sensor as a function of network parameters, i.e., the density of data sink and amount of redundancy for FC-based ARQ transmission, before solving a function for accurate service time, such that each sensor can be represented by an M/G/1 queue. Further, our analysis can formulate an optimization problem that aims at minimizing total cost incurred to install and operate 3D UASNs, without compromising two communication QoS requirements. To solve this problem, we propose a recursive algorithm to approach an optimal solution in reasonable time. Numerical evaluations demonstrate the validity of the proposed algorithm.

Community smart grid is formed by a group of neighboring households to share renewable generators and energy storage facilities. Within a community grid, all power grid entities are connected to power lines which are downstream to a common substation. We use device-to-device (D2D) communications to connect sensors which are installed at grid entities to their respective control units. The topology and node membership of such communication network depends on the topology of its power grid. As such, a communication node may not be assigned the best quality channel. This has imposed additional constraints in radio resource allocation. We exploit the feature that sensors and control units are static but cellular users are mobile, in proposing a two-stage radio resource allocation scheme. In the planning stage, we use the Hungarian method to find the optimal channel assignment for static sensors and control units. In the operation stage, we run recursively the Hungarian algorithm to allocate proportionally all remaining channels to cellular users. Given the channel assignment, the operation stage further performs transmit power allocation to all nodes. The power control problem is originally non-convex. We transform the problem into a difference of convex (DC) structure, which can be solved successively. We have evaluated the proposed radio resource allocation scheme through extensive simulations. Results confirm that the scheme is indeed efficient in assigning channels and finding the minimum transmit power, to maximize sum-rate of cellular users while guaranteeing a minimum throughput to each sensor and control unit.

In this article, we show the development and implementation of the Internet of Maritime Things (IoMT) platform that supports long-range and high-rate communication for remote and online marine water quality monitoring. We first develop the IoMT device and gateway that interwork with international standard Internet-of-Things (IoT) software platforms for universal utilization in the field of marine monitoring. The proposed IoMT device and gateway play a role similar to the IoT device and gateway on land, but it is optimized for marine use with consideration of the practical characteristics of using sensors in the ocean. Furthermore, to realize long-range and high-rate communication between marine sensors and a control center (CC) on land, an automatic beam adjustment system for directional antennas is developed. This enables the use of directional antennas, which can support long-range and high-rate communication by automatically adjusting the beam angle between the antennas while exchanging their control information, despite the antennas being shifted by undulation from the sea. Finally, we conduct real sea experiments to identify the performances of the proposed IoMT platform in various environments. The results show that the proposed IoMT platform can collect data from marine sensors as well as high definition camera video from distances of 25 and 40 km to the CC on land under one-hop and two-hop transmissions, respectively. These results indicate that the proposed IoMT platform provides at least twofold performance improvement in terms of communication coverage under a similar data rate condition, compared with existing commercial wireless networks (e.g., LTE in the ocean) not utilizing satellite communications.

Underwater wireless sensor networks (UWSNs) have emerged as a promising networking technology owing to their various underwater applications. Many applications require sensed data to be routed to a centralized location. However, the routing of sensor networks in underwater environments presents several challenges in terms of underwater infrastructure, including high energy consumption, narrow bandwidths, and longer propagation delays than other sensor networks. Efficient routing protocols play a vital role in this regard. Recently, reinforcement learning (RL)-based routing algorithms have been investigated by different researchers seeking to exploit the learning procedure via trial-and-error methods of RL. RL algorithms are capable of operating in underwater environments without prior knowledge of the infrastructure. This paper discusses all routing protocols proposed for RL-based UWSNs. The advantages, disadvantages, and suitable application areas are also mentioned. The protocols are compared in terms of the key ideas, RL designs, optimization criteria, and performance-evaluation techniques. Moreover, research challenges and outstanding research issues are also highlighted, to indicate future research directions.

This study aims to optimize the design and performance of three-dimensional (3D) underwater acoustic sensor networks (UASNs). First, we develop an analytical model to quantify network performances in terms of the packet queueing delay and packet error probability for sensors in a 3D UASN. The model considers the retransmission delay due to packet transmission errors and packet collisions when calculating the packet queueing delay. The packet queueing delay depends on the choice of medium access control (MAC) protocol. We consider two different MAC protocols: slotted ALOHA and Request-to-Send and Clear-to-Send (RTS/CTS)-based MAC, which are the representative random access-based and handshake-based MAC protocols for UASNs, respectively. Based on the model, we further determine the smallest data sink density required to meet the desired packet error probability requirement for underwater sensor density, which can help network operators to design and build UASNs in a cost-effective way. To do this, we formulate a simple optimization problem that aims to minimize the data sink density while guaranteeing an upper bound for packet error probability. Using extensive numerical evaluations, network operation strategies are then presented to achieve the desired performance requirements in 3D UASNs.

Despite the potential benefits of a maritime Internet of Things, a number of issues hinder its realization, including the need for wide area coverage and cost-effectiveness. Toward these needs, a model is first presented for uplink maritime radio communications that hierarchically employ Wi-Fi and cellular links for data transmission from marine user equipments (MUEs) on a ship to a cellular base station with distributed antennas (DAs) along a coastline. Then, the performances are evaluated given in terms of average data rate and outage probability in the hierarchical maritime radio networks. When evaluating the performances, heterogeneous channel characteristics of the hierarchical networks are taken into account in which Rayleigh fading is considered for the MUE-ship links, whereas shadowed-Rician fading is considered for the ship-DA links. Moreover, the effects due to various transmission errors that can be occurred at different communication layers are reflected in determining the quality of service (QoS) requirements of a ship. With the help of authors' analysis, an antenna selection algorithm is proposed under which the minimum size of a service cloud can be found to support the QoS requirements of MUEs with a ship. The numerical evaluations demonstrate the validity of the proposed algorithm.