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The fifth generation (5G) of mobile networks utilizing millimeter Wave (mmWave) bands can be considered the leading player in meeting the continuously increasing hunger of the end user demands in the near future. However, 5G networks are characterized by high power consumption, which poses a significant challenge to the efficient management of base stations (BSs) and user association. Implementing new power consumption and user association strategies is imperative to address this issue. For that in this work, we focus on the Dual Connectivity-User and Power Allocation (DC-UPA) problem utilizing BS switching on/off along with user dual connectivity. The problem is mathematically formulated as an Integer Linear Program (ILP), and its NP-hardness is proven by showing its equivalence to a variant of the set covering problem. Moreover, we developed two heuristic algorithms: Simulated Annealing (SA) and Distance-Aware (DA) greedy, to mitigate the impact of the problem complexity and resolve the ILP scalability issue. We conducted extensive simulations to validate the effectiveness of the proposed heuristics in a two-dimensional area containing multiple BSs and users with uniform and nonuniform geographical distributions. The performance of the SA and DA algorithms was compared against the ILP approach. We evaluated the performance of the proposed solutions considering different aspects such as the number of users, the BS radius, and the traffic load changes. The numerical results show that SA outperforms the DA in both uniform and nonuniform geographical distributions of users. The SA provides a sub-optimal solution with an optimality gap of about 3.2%, while the optimality gap of the DA is 8.62% in the case of the uniform distribution. Moreover, the optimality gap in the case of nonuniform distribution is equal to about 1% and 5.2% of SA and DA, respectively. Additionally, by utilizing our solutions, the reduction of the level of power consumption up to 16.1% and 20% in the case of uniform and nonuniform distributions can be achieved. The obtained results highlight the efficiency of the proposed algorithms in addressing the DC-UPA problem, providing practical solutions for managing power consumption and maintaining continuous user connectivity in 5G mmWave networks.

In this survey, we analyze the proposals of vehicular communication systems in the context of road traffic management. Starting with the definition of communications between vehicles (V2V), vehicles-to-infrastructure (V2I) and vehicles-to-everything (V2X), we first focus on the requirements and current standards for the Intelligent Transport Systems (ITS), including the maximum communication delay, the communication range and the size of messages (in the case of V2I transmission). After that, we analyze the use cases in line with the implementation of intelligent traffic management and review the respective methods that support or directly manage traffic on roads. One of the primary objectives of this paper is to highlight the architectures of four classes of systems able to support vehicular traffic management and communication between vehicles and roadside infrastructure, namely: vehicular cloud computing (VCC), cloudlets, Mobile Edge Computing (MEC) and fog computing. In this context, we also present our classification of the methods for these four classes of architectures. In the end, we provide our opinion on problems and limitations concerning the deployment of mechanisms belonging to each considered architecture class.

This work presents efficient connection provisioning techniques mitigating high-power jamming attacks in spectrally-spatially flexible optical networks (SS-FONs) utilizing multicore fibers. High-power jamming attacks are modeled based on their impact on the lightpaths' quality of transmission (QoT) through inter-core crosstalk. Based on a desired threshold on a lightpath's QoT, the modulation format used, the length of the path, as well as a set of physical layer characteristics, each lightpath can potentially tolerate a high-power jamming attack. In this paper, an integer linear program is thus formulated, as well as heuristic algorithms to solve the problem of attack-aware routing, spectrum, modulation format, and core allocation in SS-FONs, aiming to both efficiently provision the network in terms of network resources, as well as minimize the impact of high-power jamming attacks on the established lightpaths. Extensive simulation results are obtained for several algorithm variants with different objectives, demonstrating the validity and efficiency of the proposed techniques that can effectively mitigate high-power jamming attacks, by minimizing the number of inter-core interactions, while at the same time establishing connections with high spectral efficiency.

This paper focuses on how to increase the availability of a backbone network with minimal cost. In particular, the new framework focuses on resilience against natural disasters and is an evolution of the FRADIR/FRADIR-II framework. It targets three different directions, namely: network planning, failure modeling, and survivable routing. The steady state network planning is tackled by upgrading a sub-network (a set of links termed the spine) to achieve the targeted availability threshold. A new two-stage approach is proposed: a heuristic algorithm combined with a mixed-integer linear problem to optimize the availability upgrade cost. To tackle the disaster-resilient network planning problem, a new integer linear program is presented for the optimal link intensity tolerance upgrades together with an efficient heuristic scheme to reduce the running time. Failure modeling is improved by considering more realistic disasters. In particular, we focus on earthquakes using the historical data of the epicenters and the moment magnitudes. The joint failure probabilities of the multi-link failures are estimated, and the set of shared risk link groups is defined. The survivable routing aims to improve the network's connectivity during these shared risk link group failures. Here, a generalized dedicated protection algorithm is used to protect against all the listed failures. Finally, the experimental results demonstrate the benefits of the refined eFRADIR framework in the event of disasters by guaranteeing low disconnection probabilities even during large-scale natural disasters.

In Software Defined Networks (SDNs), the control plane of a network is decoupled from its data plane. For scalability and robustness, the logically centralized control plane is implemented by physically placing different controllers throughout the network. The determination of the number and placement of controllers is known as the Controller Placement Problem (CPP). In the regular (i.e., failure-free) state, the control plane must guarantee a given maximum delay between every switch and its primary controller and a given maximum delay between every pair of controllers. In general, these delay bounds allow multiple solutions and, so, other goals can be used to determine the best CPP solution. In this paper, we assess the connectivity-based resilience to malicious attacks against multiple network nodes of the CPP solutions obtained with three different aims: the regular state delay optimization without any concern about attacks, the regular state delay optimization taking into consideration the worst-case attacks and the resilience optimization to attacks against multiple nodes. We assess the CPP solutions considering attacks of targeted nature (when the attacker has complete knowledge of the data plane) and attacks of non-targeted nature (i.e., random and epidemic attacks). We present computational results providing an analysis of the CPP solutions to the different types of attacks. The main conclusion is that the connectivity-based resilience between the different CPP solutions strongly depends on the network topology, the regular state delay bounds and the type of attacks. Finally, we provide insights on how SDN operators can consider the conducted assessment when deciding the controller placements in their networks.

The development of broadband network access technologies available to users on land has triggered a rapid expansion of a diverse range of services provided by terrestrial networks. However, due to limitations of digital communication technologies in the off-shore area, the maritime ICT systems evolution so far has not followed that trend. Despite the e-navigation initiative defining the set of Maritime Services, the progress in the maritime ICT systems evolution has been slow. Only a few systems, including the VHF Data Exchange System (VDES), or the TRI-Media Telematic Oceanographic Network (TRITON) have been proposed to extend the basic set of services offered by classical radio-communication solutions. However, all those systems have significant limitations. The purpose of this paper is to introduce the netBaltic system designed as a fully heterogeneous system for modern maritime communications. Its unique feature is the capability to transparently use different communication technologies to efficiently support maritime ICT services, as well as openness for the incorporation of future communication technologies. The paper presents an overview of VDES, TRITON and netBaltic systems and analysis showing their expected strengths and weaknesses. The systems are then compared in simulated environments, illustrating real-world usage scenarios based on real maritime traffic information and performance measurements obtained during off-shore measurement campaigns. Results indicate that netBaltic seems to be the most versatile one and is capable of offering access to all services defined by International Maritime Organization, due to its ability to use different communication technologies simultaneously and functionality offered by its Delay Tolerant Networking component.

Optical wireless networks realized by means of gigabit optical wireless communication (OWC) systems are becoming, in a variety of applications, an important alternative, or a complementary solution, to their fiber-based counterparts. However, performance of the OWC systems can be considerably degraded in periods of unfavorable weather conditions, such as heavy fog, which temporarily reduce the effective capacity of the network. In this paper, we focus on optical wireless mesh networks that use terrestrial links (called FSO – free-space optical – links) composed of several parallel full-duplex FSO systems, and present two complementary solutions that together provide a means to maximize network traffic performance in various weather conditions encountered during network operation. The first solution is a method for estimating the degradation of the effective FSO link capacity in adverse weather conditions such as fog, rain and snow (called the weather states in this paper). The second solution is an optimization model aiming at maximizing the network traffic throughput for a given list of weather states, derived from the conducted measurements. The model assumes the so-called affine flow thinning (AFT) traffic routing and protection mechanism capable of controlling the end-to-end traffic flows in response to fluctuations of capacity available on FSO links caused by changing weather conditions. The proposed link capacity modeling approach and the elaborated optimization model are verified through an exhaustive numerical study, illustrating the trade-off between the increase of traffic performance of the FSO networks and the corresponding cost of additional OWC systems.

During and after a disaster, the perceived quality of communication networks often becomes remarkably degraded with an increased ratio of packet losses due to physical damages of the networking equipment, disturbance to the radio frequency signals, continuous reconfiguration of the routing tables, or sudden spikes of the network traffic, e.g., caused by the increased user activity in a post-disaster period. Several techniques have been introduced so far (mainly using data retransmission mechanisms) to tolerate such circumstances. Among them, gossiping has been shown to be efficient in the recovery from message losses. However, a conventional gossiping scheme may exhibit security problems, which can be exploited for further attacks (such as Denial of Service - DoS attack). For instance, the flooding method used by the gossiping can be used to forward the traffic towards many vulnerable nodes to drain their resources and compromise them. Typically, protection against DoS attacks is realized by using cryptographic primitives. However, their scalability limits and costs make them improper for emergency communications after a disaster. In this article, we introduce an approach based on reinforcement learning and game theory to protect the gossiping scheme from DoS attacks without incurring the costs of cryptographic primitives. In our method, nodes properly select which requests to satisfy, which in turn helps other nodes to avoid receiving manipulated gossip messages from malicious and colluded nodes. Additionally, our method operates without exploiting any cryptographic primitives, which prevents excessive energy waste that is undesired in post-disaster resilient networking. Simulation experiments performed in OMNeT++ confirmed the advantages of our approach over the reference schemes in terms of reliability, security, overhead, latency, and power efficiency.

Currently, 5G and the forthcoming 6G mobile communication systems are the most promising cellular generations expected to beat the growing hunger for bandwidth and enable the fully connected world presented by the Internet of Everything (IoE). The cloud radio access network (CRAN) has been proposed as a promising architecture for meeting the needs and goals of 5G/6G (5G and beyond) networks. Nevertheless, the provisioning of cost-efficient connections between a large number of remote radio heads (RRHs) in the cell sites and the baseband unit (BBU) pool in the central location, known as the fronthaul, has emerged as a new challenge. Many wired and wireless solutions have been proposed to address this bottleneck. Specifically, optical technologies presented by passive optical networks (PONs) are introduced as the best suitable solution for 5G and beyond network fronthaul due to their properties of providing high capacity and low latency connections. We considered time and wavelength division multiplexed passive optical networks (TWDM-PONs) as a fronthaul for 5G and beyond. Taking that into consideration, in this paper, we propose an integer linear program (ILP) that results in the optimal optical fronthaul deployment while minimizing the total cost of 5G and beyond instances. However, for larger network instances, solving the ILP problem becomes unscalable and time-consuming. To address that, we developed two heuristic-based algorithms (the K-means clustering algorithm and the one based on the genetic algorithm—GA). We evaluated the suitability of our proposed ILP and heuristic algorithms in simulations by utilizing them to plan different network instances (dense and sparse).

Nowadays, it is quite a challenge for app owners to keep users engaged with an app. Currently, the level of user abandonment is one of the key parameters that application owners are interested in. To meet these challenges, we conduct an extended study of a previously proposed solution that significantly reduces the abandonment rate of a given application. The investigated solution is based on the methods of fairness using the QoE and QoS approach. This paper shows that application abandonment ratios can be reduced by using an appropriate approach to fair bandwidth allocation. Adjusting the bandwidth allocation to users, taking into account the quality of the user experience, has a more effective effect on reducing app abandonment ratios than if quality of service is taken into account. This is because the users make the decision to abandon the application based on their feelings rather than technical parameters. In order to effectively reduce application abandonment ratios, a suitable bandwidth allocation algorithm must be used. This paper presents the impact of using different algorithms on the abandonment ratio and compares the popularly used algorithms and the previously proposed bandwidth allocation algorithm.

Preface

Network survivability is a capability of a networked system to provide its services despite failures or attacks. Attacks, e.g., due to acts of war, being potentially damaging events, were basically considered in the historical definitions of a survivability phenomenon. The meaning of the term: ”network survivability” evolved in the last decade. Recently, attacks replayed the important role again. Their nature, however, including intrusions, probes, denials of service, differs from the old one. Survivability is strongly related to other fields of study. In particular, quality of service depends on network survivability. We investigate these dependencies in scale-free networks. Many networks are scale-free, i.e., their node degree distribution follows the power law. Nodes of the highest degrees, called centers, are highly vulnerable to attacks. Elimination of these nodes seriously degrades the overall performance of network services. In this paper we propose a model, which, based on traffic parameters of a demand, like delay or bit rate, allows to establish the survivable and attack proof end-to-end connections. The key idea of this model is that for the significant traffic, it establishes paths, which omit centers. The important connections become more resistant to attacks. We show that in the best case, obtained for the highest class of service, the number of broken connections is reduced even by factor 3. Example results are compared to those for the standard distance metrics. Our model is applicable to many network architectures and many classes of service.