Carrier Networks Research Articles

Testing the algebraic modeling of competitive impacts from wage premium shocks: a case study from a booming airline market

Labor relations issues such as collective bargaining and strike threat power have recently gained increased attention in the Brazilian air transportation market due to a short-term shortage of qualified workforce, leading stronger pilot unions to demand higher wages and better working conditions. Exacerbated by the notable expansion of the Brazilian economy between 2020 and 2023, where air travel demand surged by 60%, this pressure has driven labor costs to grow more rapidly than other cost categories. This paper examines exogenous flight crew cost shocks, treating these as increases in wage premiums resulting from stronger unionization and higher labor market rents. Using a differentiated duopoly model, we analyze the impact of these wage increases on competition between a major network carrier and a small low-fare carrier, introducing the hypothesis of non-exhausted economies of density. Our findings indicate that smaller airlines are more adversely affected by labor cost shocks, though differentiated wage increase schemes can mitigate these impacts, reducing market concentration and preserving consumer welfare. This study contributes to the literature by incorporating wage premium shocks into existing models and suggesting that labor regulations in Brazil should be liberalized to address the rapid growth in air transportation demand and the resultant workforce shortage.

Characterising the low-cost carrier network in Southeast Asia: a complex network analysis

This study analyses the low-cost carrier network (LCCN) in Southeast Asia using complex network analysis. An analysis is conducted using the data from 2010 to 2018 covering 442 airports connected by 2,296 air routes. The LCCN is a scale-free network with a degree distribution following a power law in which fewer airports have high connectivity. It is a sparse network with a low network density. The network is efficient with a small average shortest path length, but low intra-connectivity amongst airports in the same cluster. This suggests that with good affordability and low costs, low-cost carriers play an important role in providing essential air connectivity to small and distanced destinations. Although low-cost carriers tend to use a point-to-point network instead of a hub-and-spoke network, major airports still play essential roles in shaping network connectivity and performance. Therefore, airports must have ample capacity and good infrastructure to ensure the network’s performance.

Distributed service function chaining in NFV-enabled networks: A game-theoretic learning approach

In network function virtualization (NFV), Service Function Chaining (SFC) provides an ordered sequence of virtual network functions (VNFs) and subsequent steering of traffic flows through them to cater to end-to-end services. This paper addresses the NP-hard problem of minimum cost SFC deployment to support customer services that access the carrier network’s NFV infrastructure (NFVI) through some edge routers. To determine the mappings of VNFs to physical servers, a challenging aspect would be the inter-server latencies that may fluctuate over time because of the sharing nature of cloud data centers. To construct the SFC, we come up with three different formulations, each corresponding to a different informational assumption about the link latencies: First, a centralized integer linear programming (ILP) formulation is given under the assumption of the non-causal availability of exact and instantaneous inter-server latencies. The solution to this ILP can serve as a lower bound to benchmark more scalable and realistic schemes. Next, we give a distributed game-theoretic formulation (with service broker agents as players) which only requires the statistical knowledge of link latency fluctuations. The game provably admits a pure Nash equilibrium (NE) and can be solved iteratively through the well-known best response dynamics (BRD) algorithm. Our main novelty lies in the third formulation in which each service broker has neither instantaneous nor statistical knowledge of the latencies. Instead, it relies on a game-theoretic learning algorithm to compose its VNF chain only based on its own history of adopted decisions and experienced delays on each logical link. We prove that the proposed learning algorithm asymptotically converges to NE and evaluate its performance through simulations in terms of convergence and the impact of network parameters.

Accelerating Anhydrous Proton Transport in Covalent Organic Frameworks: Pore Chemistry and its Impacts

AbstractProton conduction is important in both fundamental research and technological development. Here we report designed synthesis of crystalline porous covalent organic frameworks as a new platform for high‐rate anhydrous proton conduction. By developing nanochannels with different topologies as proton pathways and loading neat phosphoric acid to construct robust proton carrier networks in the pores, we found that pore topology is crucial for proton conduction. Its effect on increasing proton conductivity is in an exponential mode other than linear fashion, endowing the materials with exceptional proton conductivities exceeding 10−2 S cm−1 over a broad range of temperature and a low activation energy barrier down to 0.24 eV. Remarkably, the pore size controls conduction mechanism, where mesopores promote proton conduction via a fast‐hopping mechanism, while micropores follow a sluggish vehicle process. Notably, decreasing phosphoric acid loading content drastically reduces proton conductivity and greatly increases activation energy barrier, emphasizing the pivotal role of well‐developed proton carrier network in proton transport. These findings and insights unveil a new general and transformative guidance for designing porous framework materials and systems for high‐rate ion conduction, energy storage, and energy conversion.

Accelerating Anhydrous Proton Transport in Covalent Organic Frameworks: Pore Chemistry and its Impacts.

Proton conduction is important in both fundamental research and technological development. Here we report designed synthesis of crystalline porous covalent organic frameworks as a new platform for high-rate anhydrous proton conduction. By developing nanochannels with different topologies as proton pathways and loading neat phosphoric acid to construct robust proton carrier networks in the pores, we found that pore topology is crucial for proton conduction. Its effect on increasing proton conductivity is in an exponential mode other than linear fashion, endowing the materials with exceptional proton conductivities exceeding 10-2 S cm-1 over a broad range of temperature and a low activation energy barrier down to 0.24 eV. Remarkably, the pore size controls conduction mechanism, where mesopores promote proton conduction via a fast-hopping mechanism, while micropores follow a sluggish vehicle process. Notably, decreasing phosphoric acid loading content drastically reduces proton conductivity and greatly increases activation energy barrier, emphasizing the pivotal role of well-developed proton carrier network in proton transport. These findings and insights unveil a new general and transformative guidance for designing porous framework materials and systems for high-rate ion conduction, energy storage, and energy conversion.

Ru-doping W4.6N4 nanoparticles anchored on N-doped graphene tubes as efficient hydrogen evolution electrocatalyst

Designing efficient electrocatalysts for hydrogen evolution reaction (HER) is essential to facilitate hydrogen energy applications. Herein, efficient strategies of doping with metal atoms (Ru) and incorporating with conductive carbon-based material (N-doping graphene tubes) have been developed to construct the hybrid electrocatalyst RuW4.6N4@N-GTs, in which, Ru-doped W4.6N4 nanoparticles integrated on the surface of N-doped graphene tubes. RuW4.6N4@N-GTs reveals superior HER activity and good stability, with a low overpotential of 29 mV to deliver the current density of 10 mA cm−2 and a low Tafel slope of 57 mV dec−1. The unique 3D nano-structure morphology of abundant homogeneous RuW4.6N4 nanoparticles supported on conductive N-GTs network carrier contributes to expose more electrochemical active sites, promoting electrolyte transport and gas emission. At the same time, the N-GTs skeleton could prevent the RuW4.6N4 particles from agglomerating and collapsing, thus leading to the superior stability during HER process. The in situ Ru heteroatom doping could cause the directional electron transfer and more nitrogen vacancies, thus modulating the electron structure of catalysts and optimizing the hydrogen adsorption free energy. The synergistic effect of the above merits endows RuW4.6N4@N-GTs with outstanding HER performance for potential applications in the hydrogen production field.

Scheme of carrier cooperation with coordinated scheduling for faster and lower-cost failure/disaster recovery

Large-scale carrier networks are fundamental ICT infrastructures that support future 5G/6G services, and their resilience is a primary societal concern. Differently from single-carrier networks (in which one carrier owns multiple networks), in multi-carrier network ecosystems (in which the networks in the fields are operated by different carriers), cooperation among such different carriers is crucial to achieve resilience against large-scale failures. However, such cooperation is challenging since carriers may not disclose confidential information, e.g., detailed resource availability. In this study, we investigate how to perform carrier cooperative recovery in the case of large-scale failures/disasters. We propose two-stage carrier-carrier cooperative recovery planning by incorporating a coordinated scheduling for faster recovery. Through numerical evaluation, we confirm the potential benefit of carrier cooperation in terms of both recovery time and recovery cost reduction.

Quantum-Secure Signalling Model for L1/L2 Next-Gen Interconnect and Roaming Networks Over IPX for NB-IoT Traffic: A Review

Signalling security is critical for next-generation mobile (NGN) networks to ensure integrity, privacy, and confidentiality of communication protocols. However, recent research on existing 5G standards has uncovered vulnerabilities that could be exploited by emerging surveillance threats such as HiddenArt and Harvest Now Decrypt Later (HNDTL), as well as the prospect of quantum computing threatening to break classical cryptographic techniques. This systematic literature review (SLR) investigates quantum-based signalling solutions to mitigate these threats in interconnect and roaming 5G networks (IRN) over IP eXchange for Narrowband Internet of Things (NB-IoT) traffic. A database search was conducted, studies were selected and compared based on methods, approaches, techniques, and limitations. The SLR found that quantum key distribution (QKD) combined with quantum teleportation (QT) can protect and mitigate threats and attacks on signalling networks when protocols interact and interoperate in carrier networks. QKD techniques can be used for L1 protocols, while secure direct quantum communication can be used for L2 protocols. This study concludes that further studies are needed to integrate different techniques and protocols for L1/L2 signalling networks to create a robust quantum-secure signalling model for global interconnect and roaming NGN.

Network topology facilitates internet traffic control in autocracies.

Recent years have seen an increase in governmental interference in digital communication. Most research on this topic has focused on the application level, studying how content is manipulated or removed on websites, blogs, or social media. However, in order for governments to obtain and maintain control of digital data flows, they need to secure access to the network infrastructure at the level of Internet service providers. In this paper, we study how the network topology of the Internet varies across different political environments, distinguishing between control at the level of individual Internet users (access) and a higher level in the hierarchy of network carriers (transit). Using a novel method to estimate the structure of the Internet from network measurements, we show that in autocratic countries, state-owned (rather than privately owned) providers have a markedly higher degree of control over transit networks. We also show that state-owned Internet providers often provide Internet access abroad, with a clear focus on other autocratic countries. Together, these results suggest that in autocracies, the network infrastructure is organized in a way that is more susceptible to the monitoring and manipulation of Internet data flows by state-owned providers both domestically and abroad.

Resilience analysis of global agricultural trade

This study examined the transport network of global marine dry bulk carriers for agricultural trade during the period from 2018 to 2021. Firstly, the resilience of agricultural trade network is noteworthy throughout the COVID-19 pandemic. Agricultural trade initially plunged by 10.15% from 2019 to 2020 and bounced by a remarkable 11.45% in 2021, ultimately restoring trade volumes to the average level observed in the pre-pandemic year of 2019. However, the ports in Brazil and Argentina displayed less resilience in their agricultural trade with a continued decline in agricultural trade quantities in 2021. Additionally, the outbound trips increased in Ukraine, Canada, and Russia and decreased in Brazil and Argentina, leading to a more tightly knit agricultural network since 2020. Overall, this study provided evidence in comprehensively assessing the capacity and resilience of global food supply chains, especially in the context of constantly evolving circumstances and challenges.

Subnetwork-Lossless Robust Watermarking for Hostile Theft Attacks in Deep Transfer Learning Models

Recently, considerable progress has been made in providing solutions to prevent intellectual property (IP) theft for deep neural networks (DNNs) in ideal classification or recognition scenarios. However, little work has been dedicated to protecting the IP of DNN models in the context of transfer learning. Moreover, knowledge transfer is usually achieved through knowledge distillation or cross-domain distribution adaptation techniques, which will easily lead to the failure of the IP protection due to the high risk of the underlying DNN watermark being corrupted. To address this issue, we propose a subnetwork-lossless robust DNN watermarking (SRDW) framework, which can exploit out-of-distribution (OOD) guidance data augmentation to boost the robustness of watermarking. Specifically, we accurately seek the most rational modification structure (i.e., core subnetwork) using the module risk minimization, and then calculate the contrastive alignment error and the corresponding hash value as the reversible compensation information for the restoration of carrier network. Experimental results show that our scheme has superior robustness against various hostile attacks, such as fine-tuning, pruning, cross-domain matching, and overwriting. In the absence of malicious jamming attacks, the core subnetwork can be recovered without any loss. Besides that, we investigate how embedding watermarks in batch normalization (BN) layers affect the generalization performance of the deep transfer learning models, which reveals that reducing the embedding modifications in BN layers can further promote the robustness to resist hostile attacks.

Deployment of Carrier supporting Carrier (CsC) Network Providing MPLS-VPN Services to End Customers

Deployment of Carrier supporting Carrier (CsC) Network Providing MPLS-VPN Services to End Customers

Применение операторами телекоммуникационных систем графов знаний позволяет существенно повысить уровень сервиса и минимизировать время реагирования на инциденты.

The article describes a method of designing and modeling telecommunication systems based on the joint use of modern business process models, information and functional models developed by the TMForum organization, and knowledge graphs. The systems developed using the proposed method enable to build business models and operating models of all segments of carrier networks by linking elements of TMForum models, as well as by supplementing them with operational data received from the network in the form of log files generated by application servers, and as a result of network devices polling. The generated models can be used by telecom operators to address business and operational problems, as well as by architects of telecommunications systems for their design and modernization.

Incorporating flexible sulfonate-imidazolium ion pair-functionalized MOF in cross-linked polyvinyl alcohol membrane for achieving superprotonic conduction

Designing high-performance metal–organic frameworks (MOFs) based proton exchange membranes for fuel cells simultaneously with a high-density proton carrier and continuous hydrogen-bonded networks remains a challenge. The present study has endeavored to construct a crystalline Cu-MOF with chemically stable based on flexible sulfonate-imidazolium ion pair ligand in which flexible sulfonic acid chains orderly anchoring on the channel wall. Moreover, the cross-linked polyvinyl alcohol (CL-PVA) was choosing as matrix to enhance the practicality of Cu-MOF synergistically in fuel cells due to its hydrophilic and hydrophobic structure distribution. The CL-PVA/Cu-MOF-X (X = 5, 10, 15, 20 wt%) composite membranes exhibit strong water affinity and thus significantly enhanced water uptake which also along with good mechanical properties. The highly hydrophilic hydroxyl groups in CL-PVA and the sulfonic acid groups in Cu-MOF form a continuous hydrogen-bonded pathway, which result to the superprotonic conduction. Among them, CL-PVA/Cu-MOF-15 shows the highest proton conductivity of 2.4 × 10-2 S cm−1 but the smallest activation energy Ea (41 kJ/mol) at 80 °C and 90 % RH, indicating more easily transportation of H+. The single-cell power density of CL-PVA/Cu-MOF-15 is up to 49.3 mW cm−2, which will open a new avenue for the practical application of proton-conducting MOFs in proton exchange membrane fuel cells.

Strategic Response of European Airlines to Market Dynamics: A Comparative Analysis

The airline market is constantly evolving and requires managers to adopt strategies to meet the changing demands and organizational requirements of the sector. As a result of its liberalization, the European market has transformed from a set of national protected sectors to a single sector. Although the market has grown over the last two decades, the industry has faced difficulties due to various economic, safety, environmental, and health issues, which have recently emerged. This study analyzes the airlines’ strategic responses to increased competition from the turn of the century to 2019, excluding the pandemic period, to focus on market dynamics driven by European competition policy. A five-pillar strategic framework highlighting common strategies and divergences between major European network carriers is outlined through a multi-case analysis of major European markets. The sample includes France, Germany, Italy, and Spain. Results have managerial implications that highlight the importance of strategic adaptability in an industry landscape that continues to evolve. Managerial implications fall into the following three categories: strategic positioning, cost optimization, and business diversification.

NETWORK SECURITY ISSUES AND SECURITY ATTACK CLASSIFICATION FOR 5G

Fifth-generation technology [5G] services commercialized in 2019 have not only provided voice and data communication but also undergone significant structural changes in mobile networks to accommodate Internet-of-things devices, sensitive to latency and reliability, by adopting the latest ICT technologies, such as software-defined networking/network function virtualization, multi-access edge computing, and network slicing. However, this technological evolution poses new security chal- lenges, such as creation of new access paths, owing to its complex inter-operation structures, security downgrading, and limitations in security visibility. To address these issues, research on 5G security threats and security architecture has been actively underway at international standards organizations, communication carriers, and universities. However, security researchers find it difficult to conduct studies on 5G security technology design and application methods owing to the relatively unknown nature of the mobile carrier network. Therefore, in this paper, we analyzed five new security issues for each 5G section, relative to 5G technical advantages, by reviewing previous studies. In addition, we classified cyber attacks against nine network protocols primarily used in the 5G core network. The result of this study is expected to be used as basic data for modeling 5G security threats. Keywords: 5G security, Internet of things, 5G security technology, Cyber attacks, 5G threats

Stealthy dynamic backdoor attack against neural networks for image classification

Deep Neural Networks (DNNs) are vulnerable to backdoor attacks, which are external entity model providers that can inject backdoors into the network for illegal purposes. Current attack methods rely on manipulated images with embedded triggers to infiltrate carrier networks, but they suffer from detectable distortions and limited integration into neural networks. To delve further into the potential vulnerabilities of these models, this study introduces an innovative backdoor attack strategy, leveraging deep learning steganography through a Generative Adversarial Network (GAN). Our approach utilizes steganography to create manipulated images, capitalizing on the unique sensitivity of neural networks to minute perturbations. The network is then trained de novo with these manipulated images, creating a backdoor-infused model. Fundamentally, our method harnesses the pronounced sensitivity of DNNs to nuanced alterations. Experimental outcomes substantiate that our backdoor can be effectively integrated into the models, yielding high attack success rates. Notably, it also adeptly circumvents both contemporary state-of-the-art defense mechanisms and human inspection. Our source code is publicly accessible at https://github.com/DLAIResearch/NNSDB.

COMPETITIVE STRATEGIES OF ENTERPRISES IN CRISIS PERIOD: THE MARKETING ASPECT OF AIRLINES

Goal. The article is devoted to the study of the modification essence of competitive strategies as a result of the impact of crisis phenomena on the example of the activities of airlines. Methodology. Research methods include methods of scientific abstraction, observation, synthesis, generalization to highlight the key features of airlines competitive strategies, system-structural analysis of the market. The classification system of Porter's general strategies was applied in the airline sector. Results. Functional-level strategies in different areas of the firm, such as marketing, operations, finance, can only be properly developed when there is clear understanding of the overall business strategy. The article discusses general strategies that are available to all firms regardless of the sector, in accordance with Porter's view of activities differentiation and low cost, taking into account the breadth of operational goals. The focus was on airline operations, indicating the competitive strategies of full-service network carriers, low-cost carriers, integrated cargo carriers, regional airlines, charter airlines, and carrier-within-a-carrier airlines. These business models form the spectrum of strategic choices that will mix and function in hybrid forms as airlines continue to add nuance to their diverse approaches. The impact of crisis phenomena is direct factor in the hybridization of competitive strategies, although budget airlines have proven to be the most stable business models in terms of staff reduction. Scientific novelty. The competitive strategies of enterprises for the aviation sector and the business models of airlines, which respond to the global crisis challenges to varying degrees, are adapted, among which the budget business model is the most stable due to low operating costs. It was established that the business models of airlines are characterized by the approach of hybridization and mixing of business model features. Practical significance. The obtained results contribute the further development of theoretical approaches to the marketing research of airline activities, the analysis of the functioning of the air transport market. The materials reflect the generalization of competitive strategies of airlines.

Relationship between Airline Ticket Price, Demand and Business Model: A Worldwide Analysis

The aim of this study is to reveal the relationship between the average price per passenger and the number of passenger of airlines. In the study, we analyzed the average price per passenger and number of passenger data of airlines for the period 2013-2022 using panel data analysis. We applied a panel regression model in the sample of all airlines. Therefore, we conducted the analysis using 4194 observations in the sample of all airlines. In addition, in the study, we divided the airlines into different groups according to their business model. In this context, we have classified airlines as Network carriers, Low-cost carriers, Charter carriers and Regional carriers. The findings of the study show that there is a reaction in the number of passengers against the change in the average price per passenger. The results of the analysis revealed that there is a significant and negative relationship between ticket price and airline demand but there are elasticity differences according to the business model.

Probabilistic event-triggered protocol for switched power systems under multi-strategy deception attack

This paper focuses on the security control of a discrete-time switched power system utilizing a probabilistic event-triggered protocol under a multi-strategy deception attack. To better characterize the system mode’s switching behavior, a novel nonhomogeneous sojourn probability is introduced, which is modulated by a upper-level deterministic switching signal. Furthermore, a multi-strategy deception attack is established, wherein different deception attack strategies randomly target various nodes during signal transmission through the network carrier to the controller. To optimize network resource utilization, a probabilistic event-dependent triggering protocol based on a triggering threshold interval is presented, which effectively reduces unnecessary communication, leading to resource savings. Subsequently, sufficient conditions for the closed-loop system’s input-to-state stability in probability is derived. Finally, the effectiveness of the proposed control strategy is demonstrated through simulation results, which verify its capability in enhancing system security and stability, while efficiently utilizing network resources.