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

Cross-layer Balanced and Reliable Opportunistic Routing Algorithm for Mobile Ad Hoc Networks

For improving the efficiency and the reliability of the opportunistic routing algorithm, in this paper, we propose the cross-layer and reliable opportunistic routing algorithm (CBRT) for Mobile Ad Hoc Networks, which introduces the improved efficiency fuzzy logic and humoral regulation inspired topology control into the opportunistic routing algorithm. In CBRT, the inputs of the fuzzy logic system are the relative variance (rv) of the metrics rather than the values of the metrics, which reduces the number of fuzzy rules dramatically. Moreover, the number of fuzzy rules does not increase when the number of inputs increases. For reducing the control cost, in CBRT, the node degree in the candidate relays set is a range rather than a constant number. The nodes are divided into different categories based on their node degree in the candidate relays set. The nodes adjust their transmission range based on which categories that they belong to. Additionally, for investigating the effection of the node mobility on routing performance, we propose a link lifetime prediction algorithm which takes both the moving speed and moving direction into account. In CBRT, the source node determines the relaying priorities of the relaying nodes based on their utilities. The relaying node which the utility is large will have high priority to relay the data packet. By these innovations, the network performance in CBRT is much better than that in ExOR, however, the computation complexity is not increased in CBRT.Comment: 14 pages, 17 figures, 31 formulas, IEEE Sensors Journal, 201

Cross-layer design of multi-hop wireless networks

MULTI -hop wireless networks are usually defined as a collection of nodes equipped with radio transmitters, which not only have the capability to communicate each other in a multi-hop fashion, but also to route each others’ data packets. The distributed nature of such networks makes them suitable for a variety of applications where there are no assumed reliable central entities, or controllers, and may significantly improve the scalability issues of conventional single-hop wireless networks. This Ph.D. dissertation mainly investigates two aspects of the research issues related to the efficient multi-hop wireless networks design, namely: (a) network protocols and (b) network management, both in cross-layer design paradigms to ensure the notion of service quality, such as quality of service (QoS) in wireless mesh networks (WMNs) for backhaul applications and quality of information (QoI) in wireless sensor networks (WSNs) for sensing tasks. Throughout the presentation of this Ph.D. dissertation, different network settings are used as illustrative examples, however the proposed algorithms, methodologies, protocols, and models are not restricted in the considered networks, but rather have wide applicability. First, this dissertation proposes a cross-layer design framework integrating a distributed proportional-fair scheduler and a QoS routing algorithm, while using WMNs as an illustrative example. The proposed approach has significant performance gain compared with other network protocols. Second, this dissertation proposes a generic admission control methodology for any packet network, wired and wireless, by modeling the network as a black box, and using a generic mathematical 0. Abstract 3 function and Taylor expansion to capture the admission impact. Third, this dissertation further enhances the previous designs by proposing a negotiation process, to bridge the applications’ service quality demands and the resource management, while using WSNs as an illustrative example. This approach allows the negotiation among different service classes and WSN resource allocations to reach the optimal operational status. Finally, the guarantees of the service quality are extended to the environment of multiple, disconnected, mobile subnetworks, where the question of how to maintain communications using dynamically controlled, unmanned data ferries is investigated

Cross-layer schemes for performance optimization in wireless networks

Wireless networks are undergoing rapid progress and inspiring numerous applications. As the application of wireless networks becomes broader, they are expected to not only provide ubiquitous connectivity, but also support end users with certain service guarantees. End-to-end delay is an important Quality of Service (QoS) metric in multihop wireless networks. This dissertation addresses how to minimize end-to-end delay through joint optimization of network layer routing and link layer scheduling. Two cross-layer schemes, a loosely coupled cross-layer scheme and a tightly coupled cross-layer scheme, are proposed. The two cross-layer schemes involve interference modeling in multihop wireless networks with omnidirectional antenna. In addition, based on the interference model, multicast schedules are optimized to minimize the total end-to-end delay. Throughput is another important QoS metric in wireless networks. This dissertation addresses how to leverage the spatial multiplexing function of MIMO links to improve wireless network throughput. Wireless interference modeling of a half-duplex MIMO node is presented. Based on the interference model, routing, spatial multiplexing, and scheduling are jointly considered in one optimization model. The throughput optimization problem is first addressed in constant bit rate networks and then in variable bit rate networks. In a variable data rate network, transmitters can use adaptive coding and modulation schemes to change their data rates so that the data rates are supported by the Signal to Noise and Interference Ratio (SINR). The problem of achieving maximum throughput in a millimeter-wave wireless personal area network is studied --Abstract, page iv

INTERFACE MODE ASSIGNMENT METHOD FOR SELF-RECONSTRUCTION OF WIRELESS MESH NETWORKS

The key features of computer networks available for disaster situation is reliable, fault tolerance and self-configurable. Therefore, using wireless mesh network for disaster prevention and recover system has gain much attention from the research community in last decades. In addition, from the practical aspects of the network infrastructures of the disaster system, we should assume the core capabilities such as wireless connectivity in wide range, ease of use, and low cost so on. In this paper, we propose an interface mode assignment method for reconstructing a route from an isolated router to a gateway (GW) router in a wireless mesh network based on IEEE 802.11 infrastructure mode after a disaster occurrance. The proposed method assigns an adequate mode to each interface in an isolated router to recover the network reachability in distributed manner. Simulation results show the effectiveness of the proposed method via two different scenarios

Performance analysis and protocol design of opportunistic routing in multi-hop wireless networks.

Luk, Chun Pong.Thesis (M.Phil.)--Chinese University of Hong Kong, 2008.Includes bibliographical references (leaves 122-125).Abstracts in English and Chinese.Abstract --- p.iAcknowledgement --- p.ivChapter 1 --- Introduction / Motivation --- p.1Chapter 1.1 --- Background and Motivation --- p.1Chapter 1.2 --- Performance Analysis of Opportunistic Routing in Multi-hop Wireless Network --- p.3Chapter 1.3 --- Opportunistic Routing Protocol Design --- p.5Chapter 1.4 --- Chapter Summary --- p.6Chapter 2 --- Literature Review --- p.8Chapter 2.1 --- Introduction --- p.8Chapter 2.2 --- Opportunistic Routing Protocols --- p.9Chapter 2.2.1 --- Challenges of the Opportunistic Routing Protocol Design --- p.9Chapter 2.2.2 --- Overview of Existing Opportunistic Routing Protocols --- p.11Chapter 2.2.3 --- Forwarding Set Selection Algorithms --- p.12Chapter 2.2.4 --- Actual Forwarder Determination --- p.13Chapter 2.2.5 --- Duplicate Suppression Strategies --- p.14Chapter 2.2.6 --- Variations of Opportunistic Routing Protocols --- p.16Chapter 2.3 --- Performance Evaluation and Analysis of Opportunistic Routing --- p.16Chapter 2.4 --- Routing in Networks with Directional Antennas --- p.19Chapter 2.4.1 --- Performance Analysis of the use of Directional Antenna in Routing --- p.20Chapter 2.4.2 --- Existing Routing and MAC protocols for Networks with Directional Antennas --- p.21Chapter 2.5 --- Chapter Summary --- p.22Chapter 3 --- Performance Analysis of Opportunistic Routing in Multi-hop Wireless Network --- p.24Chapter 3.1 --- Introduction --- p.24Chapter 3.2 --- Analytical Derivation of the Expected Progress per Transmission of Opportunistic Routing --- p.25Chapter 3.2.1 --- Problem Formulations and Assumptions --- p.26Chapter 3.2.2 --- Reception Probability of a Node in a Given Region --- p.28Chapter 3.2.3 --- Radio Channel Models --- p.30Chapter 3.2.4 --- Average Progress per Transmission --- p.32Chapter 3.3 --- Validation and Analytical Results --- p.34Chapter 3.3.1 --- Results Validation --- p.34Chapter 3.3.2 --- Baseline Models --- p.35Chapter 3.3.3 --- Results and Analysis --- p.36Chapter 3.4 --- Further Extension of the Model --- p.40Chapter 3.5 --- Chapter Summary --- p.42Chapter 4 --- Opportunistic Routing in Multi-hop Wireless Networks with Directional Antennas --- p.44Chapter 4.1 --- Introduction --- p.44Chapter 4.2 --- Performance Analysis of Opportunistic Routing in Networks with Directional Antennas --- p.46Chapter 4.2.1 --- Network Model --- p.46Chapter 4.2.2 --- Radio Channel Models --- p.47Chapter 4.2.3 --- Antenna Models --- p.49Chapter 4.2.4 --- Expected Progress per Transmission with Directional Antenna --- p.51Chapter 4.2.5 --- Simulation Setup --- p.52Chapter 4.2.6 --- Results and Analysis --- p.54Chapter 4.3 --- Maximizing the Gain of Opportunistic Routing by Adjusting Antenna Beamwidth and Direction --- p.60Chapter 4.3.1 --- Introduction and Motivation --- p.60Chapter 4.3.2 --- Network Models --- p.61Chapter 4.3.3 --- Algorithms --- p.61Chapter 4.3.4 --- Results and Discussions --- p.66Chapter 4.3.5 --- Section Summary --- p.71Chapter 4.4 --- Chapter Summary --- p.72Chapter 5 --- Impact of Interference on Opportunistic Routing --- p.74Chapter 5.1 --- Introduction --- p.74Chapter 5.2 --- Interference Model --- p.75Chapter 5.3 --- MAC Protocols --- p.76Chapter 5.4 --- Simulation Results and Discussions --- p.78Chapter 5.4.1 --- Simulation Setup --- p.78Chapter 5.4.2 --- Baseline Models --- p.78Chapter 5.4.3 --- Results and Analysis --- p.79Chapter 5.5 --- Chapter Summary --- p.84Chapter 6 --- Threshold-based Opportunistic Routing Protocol --- p.86Chapter 6.1 --- Introduction --- p.86Chapter 6.2 --- Limitations of Existing Opportunistic Routing Protocols --- p.87Chapter 6.3 --- System Model --- p.89Chapter 6.4 --- Operating Principles of TORP --- p.91Chapter 6.5 --- Protocol Details --- p.93Chapter 6.5.1 --- Forwarding Set Computation --- p.93Chapter 6.5.2 --- Update of Forwarding Set and Remaining Transmission Counts --- p.97Chapter 6.5.3 --- Forwarding Threshold Computation and Details of the Packet Forwarding Process --- p.100Chapter 6.5.4 --- Node State --- p.101Chapter 6.5.5 --- Packet Format --- p.101Chapter 6.5.6 --- Batched Acknowledgement --- p.102Chapter 6.6 --- Advantages of TORP --- p.102Chapter 6.6.1 --- Distributed Forwarding Set Computation --- p.102Chapter 6.6.2 --- Threshold-based Forwarding --- p.103Chapter 6.6.3 --- MAC-Independence --- p.104Chapter 6.7 --- Protocol Extensions --- p.104Chapter 6.7.1 --- Implicit ACK --- p.104Chapter 6.7.2 --- Progress Recovery --- p.105Chapter 6.7.3 --- Modification of TORP for Large Networks --- p.106Chapter 6.8 --- Results and Discussions --- p.106Chapter 6.8.1 --- Simulation Setup --- p.106Chapter 6.8.2 --- Baseline Models --- p.107Chapter 6.8.3 --- Performance Evaluations and Analysis --- p.108Chapter 6.9 --- Chapter Summary --- p.116Chapter 7 --- Conclusion and Future Works --- p.118Chapter 7.1 --- Conclusion --- p.118Chapter 7.2 --- Future Work --- p.120Bibliography --- p.12