Hybrid Satellite-Terrestrial Communication Networks for the Maritime Internet of Things: Key Technologies, Opportunities, and Challenges

With the rapid development of marine activities, there has been an increasing number of maritime mobile terminals, as well as a growing demand for high-speed and ultra-reliable maritime communications to keep them connected. Traditionally, the maritime Internet of Things (IoT) is enabled by maritime satellites. However, satellites are seriously restricted by their high latency and relatively low data rate. As an alternative, shore & island-based base stations (BSs) can be built to extend the coverage of terrestrial networks using fourth-generation (4G), fifth-generation (5G), and beyond 5G services. Unmanned aerial vehicles can also be exploited to serve as aerial maritime BSs. Despite of all these approaches, there are still open issues for an efficient maritime communication network (MCN). For example, due to the complicated electromagnetic propagation environment, the limited geometrically available BS sites, and rigorous service demands from mission-critical applications, conventional communication and networking theories and methods should be tailored for maritime scenarios. Towards this end, we provide a survey on the demand for maritime communications, the state-of-the-art MCNs, and key technologies for enhancing transmission efficiency, extending network coverage, and provisioning maritime-specific services. Future challenges in developing an environment-aware, service-driven, and integrated satellite-air-ground MCN to be smart enough to utilize external auxiliary information, e.g., sea state and atmosphere conditions, are also discussed

Big Data Computing for Geospatial Applications

The convergence of big data and geospatial computing has brought forth challenges and opportunities to Geographic Information Science with regard to geospatial data management, processing, analysis, modeling, and visualization. This book highlights recent advancements in integrating new computing approaches, spatial methods, and data management strategies to tackle geospatial big data challenges and meanwhile demonstrates opportunities for using big data for geospatial applications. Crucial to the advancements highlighted in this book is the integration of computational thinking and spatial thinking and the transformation of abstract ideas and models to concrete data structures and algorithms

Network-supported layered multicast transport control for streaming media

Multicast is very efficient in distributing large volume of data to multiple receivers over the Internet. Layered multicast helps solve the heterogeneity problem in multicast delivery. Extensive work has been done in the area of layered multicast, for both congestion control and error control. In this paper, we focus on network-supported protocols for streaming media. Most of the existing work solves the congestion control and error control problems separately, and do not give an integrated, efficient solution. In this paper, after reviewing related work, we introduce our proposed protocols, RALM and RALF. The former is a congestion control protocol and the latter is an error control protocol. They work under the same framework and provide an integrated solution. We also extend RALM to RALM-II, which is compatible with TCP traffic. We analyze the complexity of the proposed protocols in the network and investigated their performance through simulations. We show that our solution achieves significant performance gains with reasonable additional complexity. © 2007 IEEE.published_or_final_versio

Exploring the geography of China's airport networks: a hybrid complex-network approach

Air networks are normal examples of transportation systems among ubiquitous big data networks in the dynamic nature. This is particularly the case in developing countries with rapid airport network expansions. This paper explores the structure and evolution of the trunk airport network of China (ANC) in major years during 1980s-2000s. We generalise the complex network approach developed in existing studies and further test for statistical properties of weighted network characteristics by using pair-wise traffic flows. The spatiotemporal decomposition of network metric plots and the visualization maps leads to a rich harvest of stylized ANC structures: (i) national hub-and-spoke patterns surrounding mega-cities; (ii) regional broker patterns surrounding Kunming and Urumqi, and (iii) local heterogeneous disparity patterns in isolated geographical cities, such as Lhasa, Lijiang, Huangshan, etc. These findings have important implications towards understanding the geo-political and economic forces at stake in shaping China's urban systems