Deep Reinforcement Learning Based Joint Edge Resource Management in Maritime Network

Due to the rapid development of the maritime networks, there has been a growing demand for computation-intensive applications which have various energy consumption, transmission bandwidth and computing latency requirements. Mobile edge computing(MEC) can efficiently minimize computational latency by offloading computation tasks by the terrestrial access network. In this work, we introduce a space-air-ground-sea integrated network architecture with edge and cloud computing components to provide flexible hybrid computing service for maritime service. In the integrated network, satellites and unmanned aerial vehicles(UAVs) provide the users with edge computing services and network access. Based on the architecture, the joint communication and computation resource allocation problem is modelled as a complex decision process, and a deep reinforcement learning based solution is designed to solve the complex optimization problem. Finally, numerical results verify that the proposed approach can improve the communication and computing efficiency greatly.

Maritime network dynamics before and after international events

Investigating the influence of international events on global maritime networks is a challenging task that must comprehensively incorporate geographical, political, and maritime sciences. Understanding global maritime network dynamics is an initial and critical step in this investigation. This study proposes an automatic identification system(AIS)-based approach to understanding maritime network dynamics before and after international events. In this approach, a spatiotemporal modeling method is introduced to measure the similarity in shipping trends before and after international events. Then, a spatiotemporal analytic framework is proposed to understand the maritime network dynamics by grouping similar situation, and assessing possible indirect effects within a network. Finally, three case studies of international events, military conflict, lifted economic sanctions, and government elections, were used to investigate the observed network dynamics possibly affected by international events. The results indicate that container, tanker, and bulk shipping between India and its connected countries all declined more than 69% after military conflicts between India and Pakistan in August 2015. Tanker shipping between Iran and the United Arab Emirates increased 51% after economic sanctions on Iran were lifted. Container shipping between Sri Lanka and Singapore, Malaysia, and India increased more than 74% after the general election in Sri Lanka. These investigations demonstrate the feasibility of the proposed approach in assessing the possible effects of international events on maritime network dynamics.

Collaborative Multiple Access And Energy-Efficient Resource Allocation in Distributed Maritime Wireless Networks

With the rapid increasing of maritime activities, maritime wireless networks(MWNs) with high reliability, high energy efficiency, and low delay are required. However, the centralized networking with fixed resource scheduling is not suitable for MWNs due to the special environment. In this paper,we introduce the collaborative relay communication in distributed MWNs to improve the link reliability, and propose an orthogonal time-frequency resource block reservation based multiple access(RRMA) scheme for both one-hop direct link and two-hop collaborative relay link to reduce the interference. To further improve the network performance, we formulate an energy efficiency(EE) maximization resource allocation problem and solve it by an iterative algorithm based on the Dinkelbach method. Finally, numerical results are provided to investigate the proposed RRMA scheme and resource allocation algorithm, showing that the low outage probability and transmission delay can be attained by the proposed RRMA scheme. Moreover,the proposed resource allocation algorithm is capable of achieving high EE in distributed MWNs.

Location privacy protection of maritime mobile terminals

Mobile Edge Computing(MEC)can support various high-reliability and low-delay applications in Maritime Networks(MNs).However,security risks in computing task offloading exist.In this study,the location privacy leakage risk of Maritime Mobile Terminals(MMTs)is quantified during task offloading and relevant Location Privacy Protection(LPP)schemes of MMT are considered under two kinds of task offloading scenarios.In single-MMT and single-time offloading scenario,a dynamic cache and spatial cloaking-based LPP(DS-CLP)algorithm is proposed;and under the multi-MMTs and multi-time offloading scenario,a pseudonym and alterable silent period-based LPP(PA-SLP)strategy is proposed.Simulation results show that the DS-CLP can save the response time and communication cost compared with traditional algorithms while protecting the MMT location privacy.Meanwhile,extending the alterable silent period,increasing the number of MMTs in the maritime area or improving the pseudonym update probability can enhance the LPP effect of MMTs in PA-SLP.Furthermore,the study results can be effectively applied to MNs with poor communication environments and relatively insufficient computing resources.

Packet Transport for Maritime Communications:A Streaming Coded UDP Approach

The maritime communication network(MCN)plays an important role in the 6th generation(6G)system development.In MCNs,packet transport over long-distance lossy links will be ubiquitous.Transmission control protocol(TCP),the dominant transport protocol in the past decades,have had performance issues in such links.In this paper,we propose a novel transport approach which uses user datagram protocol(UDP)along with a simple yet effective bandwidth estimator for congestion control,and with a proactive packet-level forward erasure correction(FEC)code called streaming code to provide low-delay loss recovery without data retransmissions at all.We show that the approach can effectively address two issues of the state-of-the-art TCP variants in the long-distance lossy links,namely 1)the low bandwidth utilization caused by the slow increase of the congestion window(CWND)due to long roundtrip time(RTT)and the frequent CWND drop due to random and congestion losses,and 2)the high endto-end in-order delivery delay when re-transmissions are incurred to recover lost packets.In addition,we show that the scheme’s goodput has good smoothness and short-term intra-protocol fairness properties,which are beneficial for multimedia streaming and interactive applications that are prominent parts of today’s wireless traffic.

Trajectory Design for UAV-Enabled Maritime Secure Communications:A Reinforcement Learning Approach

This paper investigates an unmanned aerial vehicle(UAV)-enabled maritime secure communication network,where the UAV aims to provide the communication service to a legitimate mobile vessel in the presence of multiple eavesdroppers.In this maritime communication networks(MCNs),it is challenging for the UAV to determine its trajectory on the ocean,since it cannot land or replenish energy on the sea surface,the trajectory should be pre-designed before the UAV takes off.Furthermore,the take-off location of the UAV and the sea lane of the vessel may be random,which leads to a highly dynamic environment.To address these issues,we propose two reinforcement learning schemes,Q-learning and deep deterministic policy gradient(DDPG)algorithms,to solve the discrete and continuous UAV trajectory design problem,respectively.Simulation results are provided to validate the effectiveness and superior performance of the proposed reinforcement learning schemes versus the existing schemes in the literature.Additionally,the proposed DDPG algorithm converges faster and achieves higher utilities for the UAV,compared to the Q-learning algorithm.

China's Global Shipping Connectivity:Internal and External Dynamics in the Contemporary Era(1890–2016)

China's global shipping connectivity had been somewhat overlooked as the bulk of related studies predominantly focused on the throughput volume of its own port cities. This article tackles such lacunae by providing a relational perspective based on the extraction of vessel movement archives from the Lloyd's List corpus. Two complementary analyses are proposed: long-term dynamics with all ships included(1890–2008) and medium-term dynamics focusing on container flows(1978–2016). Each analysis examines China's maritime connectivity in various ways and on different spatial scales, from the global to the local, in terms of concentration, vulnerability, and expansion. The main results underline the influence of technological, economic, and political factors on the changing distribution of connectivity internally and externally. In particular, China has managed to reduce its dependence upon external transit hubs, to increase the internal connectivity of its own port system, and to strengthen its dominance towards an increasing number of foreign nodes and trade partners through the maritime network.

Convergence of Broadband and Broadcast/Multicast in Maritime Information Networks

Recently,the fifth-generation(5G)of wireless networks mainly focuses on the terrestrial applications.However,the well-developed emerging technologies in 5G are hardly applied to the maritime communications,resulting from the lack of communication infrastructure deployed on the vast ocean,as well as different characteristics of wireless propagation environment over the sea and maritime user distribution.To satisfy the expected plethora of broadband communications and multimedia applications on the ocean,a brand-new maritime information network with a comprehensive coverage capacity in terms of all-hour,all-weather,and all-sea-area has been expected as a revolutionary paradigm to extend the terrestrial capacity of enhanced broadband,massive access,ultra-reliable,and low-latency to the vast ocean.Further considering the limited available resource of maritime communication infrastructure,the convergence of broadband and broadcast/multicast can be regarded as a possible yet practical solution for realizing an efficient and flexible resource configuration with high quality of services.Moreover,according to such multi-functionality and all-coverage maritime information network,the monitoring and sensing of vast ocean area relying on massive Ocean of Things and advanced radar techniques can be also supported.Concerning these issues above,this study proposes a Software Defined Networking(SDN)based Maritime Giant Cellular Network(MagicNet)architecture for broadband and multimedia services.Based on this network,the convergence techniques of broadband and broadcast/multicast,and their supporting for maritime monitoring and marine sensing are also introduced and surveyed.

Cooperative Spectrum Sensing Based on Centralized Double Threshold in MCN

Cooperative spectrum sensing appears popular currently due to its ability to solve the issue of hidden terminal and improve detection performance in Cognitive Radio Networks. Meanwhile, double threshold based energy detector has attracted much attention for its low computational complexity and superior performance. Motivated by this, a cooperative spectrum sensing scheme is proposed in this paper based on centralized double threshold in the maritime communication networks(MCN), where the energy value of received signal in each cognitive node is forwarded to the fusion center for final decision based on double thresholds. Additionally, the proposed scheme is further optimized for the decisions that the energy is within the scope of maximum threshold and minimum threshold. Simulation experiments verify the performance of the proposed method.