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

A Survey on the Communication Protocols and Security in Cognitive Radio Networks

A cognitive radio (CR) is a radio that can change its transmission parameters based on the perceived availability of the spectrum bands in its operating environment. CRs support dynamic spectrum access and can facilitate a secondary unlicensed user to efficiently utilize the available underutilized spectrum allocated to the primary licensed users. A cognitive radio network (CRN) is composed of both the secondary users with CR-enabled radios and the primary users whose radios need not be CR-enabled. Most of the active research conducted in the area of CRNs has been so far focused on spectrum sensing, allocation and sharing. There is no comprehensive review paper available on the strategies for medium access control (MAC), routing and transport layer protocols, and the appropriate representative solutions for CRNs. In this paper, we provide an exhaustive analysis of the various techniques/mechanisms that have been proposed in the literature for communication protocols (at the MAC, routing and transport layers), in the context of a CRN, as well as discuss in detail several security attacks that could be launched on CRNs and the countermeasure solutions that have been proposed to avoid or mitigate them. This paper would serve as a good comprehensive review and analysis of the strategies for MAC, routing and transport protocols and security issues for CRNs as well as would lay a strong foundation for someone to further delve onto any particular aspect in greater depth

A novel admission control scheme for network slicing based on squatting and kicking strategies

New services and applications impose differentquality of service (QoS) requirements on network slicing. Tomeet differentiated service requirements, current Internet servicemodel has to support emerging real-time applications from 5Gnetworks. The admission control mechanisms are expected tobe one of the key components of the future integrated serviceInternet model, for providing multi-level service guarantees withthe different classes (slices) of services. Therefore, this paperintroduces a new flexible admission control mechanism, basedon squatting and kicking techniques (SKM), which can beemployed under network slicing scenario. From the results, SKMprovides 100% total resource utilization in bandwidth contextand 100% acceptance ratio for highest priority class underdifferent input traffic volumes, which cannot be achieved byother existing schemes such as AllocTC-Sharing model due topriority constraints.Peer ReviewedPostprint (published version

Cache-Enabled in Cooperative Cognitive Radio Networks for Transmission Performance

The proliferation of mobile devices that support the acceleration of data services (especially smartphones) has resulted in a dramatic increase in mobile traffic. Mobile data also increased exponentially, already exceeding the throughput of the backhaul. To improve spectrum utilization and increase mobile network traffic, in combination with content caching, we study the cooperation between primary and secondary networks via content caching. We consider that the secondary base station assists the primary user by pre-caching some popular primary contents. Thus, the secondary base station can obtain more licensed bandwidth to serve its own user. We mainly focus on the time delay from the backhaul link to the secondary base station. First, in terms of the content caching and the transmission strategies, we provide a cooperation scheme to maximize the secondary user’s effective data transmission rates under the constraint of the primary users target rate. Then, we investigate the impact of the caching allocation and prove that the formulated problem is a concave problem with regard to the caching capacity allocation for any given power allocation. Furthermore, we obtain the joint caching and power allocation by an effective bisection search algorithm. Finally, our results show that the content caching cooperation scheme can achieve significant performance gain for the primary and secondary systems over the traditional two-hop relay cooperation without caching

Performance assessment & synergic operation of algorithmic solutions enabling opportunistic networks– D4.2

Deliverable D4.2 del projecte europeu OneFITPeer ReviewedPostprint (updated version

Models and Protocols for Resource Optimization in Wireless Mesh Networks

Wireless mesh networks are built on a mix of fixed and mobile nodes interconnected via wireless links to form a multihop ad hoc network. An emerging application area for wireless mesh networks is their evolution into a converged infrastructure used to share and extend, to mobile users, the wireless Internet connectivity of sparsely deployed fixed lines with heterogeneous capacity, ranging from ISP-owned broadband links to subscriber owned low-speed connections. In this thesis we address different key research issues for this networking scenario. First, we propose an analytical predictive tool, developing a queuing network model capable of predicting the network capacity and we use it in a load aware routing protocol in order to provide, to the end users, a quality of service based on the throughput. We then extend the queuing network model and introduce a multi-class queuing network model to predict analytically the average end-to-end packet delay of the traffic flows among the mobile end users and the Internet. The analytical models are validated against simulation. Second, we propose an address auto-configuration solution to extend the coverage of a wireless mesh network by interconnecting it to a mobile ad hoc network in a transparent way for the infrastructure network (i.e., the legacy Internet interconnected to the wireless mesh network). Third, we implement two real testbed prototypes of the proposed solutions as a proof-of-concept, both for the load aware routing protocol and the auto-configuration protocol. Finally we discuss the issues related to the adoption of ad hoc networking technologies to address the fragility of our communication infrastructure and to build the next generation of dependable, secure and rapidly deployable communications infrastructures

Squatting and kicking model evaluation for prioritized sliced resource management

© Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/Effective management and allocation of resources remains a challenging paradigm for future large-scale networks such as 5G, especially under a network slicing scenario where the different services will be characterized by differing Quality of Service (QoS) requirements. This makes the task of guaranteeing the QoS levels and maximizing the resource utilization across such networks a complicated task. Moreover, the existing allocation strategies with link sharing tend to suffer from inefficient network resource usage. Therefore, we focused on prioritized sliced resource management in this work and the contributions of this paper can be summarized as formally defining and evaluating a self-provisioned resource management scheme through a smart Squatting and Kicking model (SKM) for multi-class networks. SKM provides the ability to dynamically allocate network resources such as bandwidth, Label Switched Paths (LSP), fiber, slots among others to different user priority classes. Also, SKM can guarantee the correct level of QoS (especially for the higher priority classes) while optimizing the resource utilization across networks. Moreover, given the network slicing scenarios, the proposed scheme can be employed for admission control. Simulation results show that our model achieves 100% resource utilization in bandwidth-constrained environments while guaranteeing higher admission ratio for higher priority classes. From the results, SKM provided 100% acceptance ratio for highest priority class under different input traffic volumes, which, as we articulate, cannot be sufficiently achieved by other existing schemes such as AllocTC-Sharing model due to priority constraints.Peer ReviewedPostprint (author's final draft