Network Infrastructure Research Articles

Unveiling barriers to EHR implementation for effective decision support in tanzanian primary healthcare: Insights from practitioners.

This study investigates the barriers to implementing electronic health records (EHR) systems for decision support in Tanzanian primary healthcare (PHC) facilities and proposes strategies to address these challenges. A qualitative, inductive approach was used, guided by the Diffusion of Innovations (DOI) theory, the Technology Acceptance Model (TAM), and the Sociotechnical Systems theory. Using snowball sampling, data were collected from 14 participants through semi-structured interviews in Dodoma, Tanzania. Thematic analysis identified key barriers. Critical barriers to EHR implementation include lack of leadership support, poor network infrastructure, increased workload, and resistance to technology due to concerns over professional autonomy. Technical challenges, such as system downtime and lack of skilled personnel, hinder EHR use, resulting in inefficiencies and incomplete system adoption, negatively affecting patient outcomes. This study offers unique insights into barriers to EHR adoption in Tanzanian PHC facilities. Grounded in multiple theoretical frameworks, the findings contribute to health informatics discourse in low-resource settings and provide practical recommendations for improving EHR implementation. The study's implications are relevant for policymakers, healthcare leaders, and IT developers in similar contexts.

An adaptive multistage intrusion detection and prevention system in software defined networking environment

The advancements made in Software-Defined Networking (SDN) technology seem quite promising, with potential wide application in managing and controlling the latest network infrastructures. SDN technology decouples the control plane from the data plane, enabling effective and flexible network management. However, this dynamic phenomenon brings new security challenges. With the increasing dynamism and programmable nature of networks, conventional security protocols may not sufficient to protect against advanced and sophisticated attacks. Although Intrusion Detection Systems (IDSs) have been extensively applied for identifying and preventing security threats in traditional network environments, IDS models designed specifically for traditional network requirements may not be adequate for SDN environments. These issues may stem from the static nature of conventional networks, contrasting with the dynamicity of advanced SDN networks, and the traditional IDS’s inability to adapt to the dynamic nature of SDN. To address these challenges, the current research proposes a novel Deep Hybrid IDS model to enhance network security in SDN environments and prevent attacks using Scapy. The proposed model detects signature-based attacks by integrating Gated Recurrent Units (GRU) and Long Short-Term Memory (LSTM) for real-time simulated datasets, achieving an accuracy of 97.8%, which is comparatively better than existing models.

Mobility–Multihoming Duality

In modern Internet-based communication, especially mobile systems, a mobile node (MN) will commonly have more than one possibility for Internet Protocol (IP) connectivity. For example, an MN such as a smartphone may be associated with an IEEE 802.11 network at a site while also connected to a cellular base station for 5G. In such a scenario, the smartphone might only be able to utilise the IEEE 802.11 network, not making use of the cellular connectivity simultaneously. Currently, IP does not allow applications and devices to easily utilise multiple IP connectivity opportunities—multihoming for the MN—without implementing special mechanisms to manage them. We demonstrate how the use of the Identifier Locator Network Protocol (ILNP), realised as an extension to IPv6, can enable mobility with multihoming using a duality mechanism that treats mobility and multihoming as the same logical concept. We present a network layer solution that does not require any modification to transport protocols, can be implemented using existing application programming interfaces (APIs), and can work for any application. We have evaluated our approach using an implementation in Linux and a testbed. The testbed consisted of commercial equipment to demonstrate that our approach can be used over existing network infrastructure requiring only normal unicast routing for IPv6.

Digital economy and green transformation of regional industries: New insights from sustainability.

Studying the impact of the digital economy on carbon emissions in the distribution industry is of great significance for realizing sustainable development goals and coping with climate change. This study finds that increasing the level of digital economy development can reduce the carbon emission intensity of the circulation industry through fixed-effects modeling. Moreover, the effect is different in different geographic regions, and the improvement of the digital economy development level in the east and central regions can significantly reduce the carbon emission intensity of the distribution industry. The digital economy can simultaneously reduce the carbon emission intensity of the circulation industry by reducing the degree of labor factor mismatch in the circulation industry and improving the regional green innovation capacity. Therefore, in order to promote the green development of the distribution industry, it is also necessary to make efforts to improve the construction of network infrastructure, accelerate the process of research and development and cultivation of green technology, and break down the barriers of cross-regional mobility of talents.

A systemic approach for assessing infrastructure component importance in hazard-prone communities

Investing in pre-event disaster mitigation interventions for physical infrastructure, such as structural retrofits and enhancements, can be costly due to limited resources. To prioritize investments, infrastructure components are ranked by their criticality within the overall system. To be effective in real-world deployment, this approach must account for the complex interactions between components, as failures can occur simultaneously across large geographical areas due to the hazard footprint. As a result, hazard-specific uncertainties and spatial correlations may lead to distinctive failure patterns. In this study, we propose a novel data-driven framework leveraging Monte Carlo simulation, that harnesses the individual realizations to capture and model realistic component damage patterns under a specified hazard scenario. This framework addresses a gap in literature by moving beyond traditional methods that often treat component failures as independent events. By capturing the interdependence between bridges, primarily through failure interactions, and system-wide effects, our method provides a more comprehensive criticality assessment. The simulation data provides a foundation for the framework, which applies to a wide variety of infrastructure networks and performance metrics. To demonstrate the method's effectiveness, a simplified transportation network from Shelby County, TN subjected to an earthquake event is analyzed. The proposed framework provides an effective approach for component ranking, suitable for decision-making where human intuition and simple methods are insufficient. Its broad applicability suggests a potential for large-scale and interdependent network problems.

Urban green streets and water management safety hubs in public schools lots

Abstract Green Stormwater Infrastructure (GSI) represents an effective approach to enhance urban resilience to climate change, contributing to runoff regulation and localized flood risk reduction. This study examines the potential for transforming open spaces in public schools into safety hubs for stormwater management in Mediterranean urban contexts, drawing on best practices from North America. Through a methodological analysis combining Research Through Design and an international literary scoping review, case studies of schools in the Metropolitan City of Naples are presented and compared with U.S. projects implementing GSI in school areas. The results highlight the importance of strategic coordination guidelines for local administrators, designers, and school principals, aimed at planning, designing, and managing highly performant green infrastructure networks. An integrated and shared metropolitan-level approach can maximize environmental benefits, transforming schools into community centers for urban resilience education and participatory management of risks related to extreme weather events.

Virtualized network functions resource allocation in network functions virtualization using mathematical programming

Network Functions Virtualization (NFV) revolutionizes network services by eliminating the need for dedicated hardware. This virtualization enables flexible and efficient deployment of various network functions like proxies, firewalls, and load balancers. Providing the service requested by the user in the network is done by a sequence of virtual network functions, which are known as service functions chain. One of the main challenges in the development of network functions virtualization architecture is the allocation of resources to the requested network services in network infrastructures, this challenge is called network function virtualization resource allocation problem. Therefore, this paper addresses the resource allocation problem in Network Functions Virtualization (NFV) architectures using mathematical programming techniques. A multi-objective mixed-integer linear programming (MILP) model is proposed to optimize resource allocation for virtual network functions (VNFs). The model incorporates constraints related to node and link resource capacities, as well as delay requirements. The objective functions focus on maximizing network throughput, minimizing node resource costs (CPU cores and memory), reducing capital and operational expenses, and ensuring efficient execution time. These constraints and objective functions are formally defined by mathematical functions. The proposed mathematical model is implemented and solved using the Cplex solver. To evaluate the effectiveness of the proposed mathematical model, various network topologies were evaluated under different parameters. These parameters included the length of Service Function Chains (SFCs), the number and length of flows, node resource capacities, the number of nodes and VNFs. The experimental results demonstrated the model’s ability to efficiently allocate resources to VNFs across these different scenarios.

AIRBORNE LASER SCANNER AS A DATA SOURCE FOR BUILDING SELECTED ELEMENTS OF AN INTELLIGENT DATABASE FOR TRANSPORTATION

In this study, the main objective was to detect the road network and key road infrastructure elements based on airborne laser scanning data. The study included identification of the road network and determination of its axes using three independent methods, as well as detection of horizontal signs such as pedestrian crossings. The analysis process was based mainly on digital image processing methods, based solely on lidar data, without using information from other sources. The results of the analysis showed that the use of lidar data provides a fast and effective method for continuously updating information on road infrastructure and expanding the transportation database. This potentially opens the door to effectively updating relevant data in the area of transportation infrastructure.

Network Infrastructure Development and Large Shareholder Expropriation: A Quasi-Natural Experiment from the 'Broadband China' Strategy

Network Infrastructure Development and Large Shareholder Expropriation: A Quasi-Natural Experiment from the 'Broadband China' Strategy

Enhancing Network Management Practices in East Africa: A Comprehensive Review

Network management is an integral component of the region’s rapid urbanisation, huge population growth, and technological advancements in East Africa. However, the smooth operation of East African networks is hindered by inadequate infrastructure, complex rules, and cyber-security issues. Both conventional and contemporary technologies are included in the regional network architecture, with mobile networks and fibre optic cables predominating. Among the difficulties are issues with spectrum distribution and regulatory discrepancies, and network management methods differ greatly between carriers. Strategies such as Kenya’s National Optic Fibre Backbone Infrastructure and Rwanda’s Smart Kigali programme are successful initiatives that demonstrate effective ways to develop infrastructure and urban management. Particularly inventive models such as Uganda’s Village Phone programme and Kenya’s M-PESA platform create digital inclusion and economic power. Public-private partnerships facilitate infrastructure development and technology adoption. Network management strategies for Eastern Africa could include the development of rural connectivity projects, policy change for regulatory harmonisation, the use of advanced technologies, capacity-building programmes, and cross-border interactions. This review examines the situation of mobile networks, internet connections, and data centres, as well as other telecommunication network infrastructure, focusing on their existing strong points, weaknesses, and possibilities for further enhancement. Analysing systems of regulations: We used all recently published material (2004–2014) from various highly reliable databases. The findings suggest that adequate measures of network management are required to propel economic growth, digital inclusion, and deeper regional cooperation in East Africa. East African nations may utilise several strategies such as infrastructure development, legislative reforms, technology adoption, capacity building, and collaboration to produce reliable and inclusive communication networks, which will contribute to sustainable development. Keywords: Enhancing, Network, Management, Communication, Cybersecurity, Innovation, East Africa

Infrastructures of power: Governance by energy systems and infrastructure

This paper suggests a synthetization of three classic approaches to analyze infrastructures as interconnected compositions that subtly distribute power and governance. We draw upon conceptualizations within large technological systems (LTS), Internet governance, and information infrastructures (II), and connect them to our own extensive research in energy infrastructure and systems spanning over a decade. This combination serves as the bedrock for our methodological work, which we establish here as pivotal signposts for the study of governance by infrastructures. Rooted empirically in energy research, we advocate for scholars to expand these methodologies to other infrastructures, such as the Internet and II, to illustrate how governance operates across diverse infrastructural networks and their intersections. Our empirical examples draw from studies in smart grids and smart energy technologies, electricity supply management and markets, and energy computer modeling. These diverse cases are utilized to inform the proposed methodological approach.

Structural characterisation for the synthesis of large‐scale combined electric–gas networks

AbstractIn this paper, the authors present a methodology for building realistic synthetic test cases to model combined electric and natural gas infrastructure networks. Because these networks are synthetic, that is, fictitious, they are able to be freely shared; hence, they serve to support research and development in the area of coupled‐infrastructure analysis with large‐scale realistic test cases that do not contain non‐public information. We anchor our process for building these synthetic networks in a structural characterisation of actual electric and natural gas networks. Supply and demand nodes are geographically placed, based on a combination of publicly available information from several sources and a clustering‐based method to match the right fraction of each node type, taking into account the intersection points between the electric and gas grids. Then the networks are connected with pipelines and transmission lines using a systematic graph construction method, validated against network properties including degree distribution, clustering, graph diameter, and degree of planarity, along with operational validation to ensure the simulated solution is realistic. The methodology is demonstrated by creating and validating a test case with 6717 electric buses and 2451 gas nodes.

SAFERIDES: Application of decentralized control edge-computing to ridesharing monitoring services

Edge computing changed the face of many industries and services. Common edge computing models offload computing which is prone to security risks and privacy breach. However, advances in deep learning enabled Internet of Things (IoTs) to onload tasks and run cognitive tasks locally. This research introduces a decentralized-control edge model where computation and decision-making are moved to the IoT level. The model aims at decreasing communication and computation dependance on the edge which affect efficiency and latency. The model also limits data transfer to the edge to avoid security and privacy risks. Decentralized control is a key to many business applications that prioritizes safety, real-time response, and privacy such as ridesharing monitoring and industrial operations. To examine the model, we developed SAFERIDES, a scene-aware ridesharing monitoring system where smart phones are detecting violations at the runtime. Current monitoring systems require costly infrastructure and continuous network connectivity. However, SAFRIDES uses optimized deep learning models that run locally on IoTs to detect and record violations in ridesharing. The system achieved the lowest latency among current solution, while minimizing data sharing and maintaining privacy. Moreover, decentralized edge computing empowers IoTs and upgrades their functionality from sensing to independent decision-making.

Study on the planning and scheduling strategies of the hydrogen supply network for road transportation in deep decarbonization scenarios

As the energy decarbonization continues to advance, hydrogen is gaining momentum. With the increasing demand for hydrogen and the lack of hydrogen infrastructure, it is urgent to solve the problem of hydrogen supply network layout planning. In order to reduce redundant construction of hydrogen supply network infrastructure and increase the rationality of its layout, this paper conducts research on the optimal layout planning of hydrogen supply network infrastructure in the transportation sector. By constructing a two-stage real-time scheduling model of hydrogen supply network, the unit cost composition of hydrogen supply network is more complete and accurate, and the location, technology type and quantity of each link of hydrogen supply network are obtained. The results show that the unit cost of China's hydrogen supply network is 27.8 CNY/kg in 2035 and 19.04 CNY/kg in 2050 under the baseline scenario. Compared with the results of existing literature, the two-stage real-time scheduling model can reduce by 7 % of the hydrogen energy supply network unit cost by decreasing the transportation vehicles and the investment capacity of fixed hydrogen storage equipment. The proposed method of the hydrogen supply network planning can provide policy-makers with the selection of sustainability pathways for dynamic hydrogen infrastructure development planning.

ENSURING A SAFE TOMORROW: CONCLUSIONS FROM THE ANALYSIS OF THE LEADING CYBER ATTACKS AND THEIR IMPACT ON INFORMATION SECURITY

In today's world, where digitalization and universal connectivity play a key role, cybersecurity issues are coming to the fore in the context of global security. With increasing dependence on digital technologies, cyberspace continues to evolve, presenting new threats and challenges. This article focuses on the analysis of major attacks on network infrastructure that have occurred in recent years, exploring various types of attacks such as DDoS, APT, ransomware, Man-in-the-Middle (MitM) and SQL Injection. The main focus is on identifying common attack patterns and protection techniques, which allows for a better understanding of the mechanisms and strategies for countering cyber threats. The article examines in detail the various tools and methods of traffic analysis used to detect and neutralize threats, analyzes their effectiveness in real conditions. Using the included histograms, charts and tables, the article visualizes data and trends, which contributes to a better understanding of the complexity and dynamics of cyber attacks. Based on the analysis, recommendations are formulated to improve cyber defense strategies and develop new approaches to ensuring security in the digital world, which is critically important for protecting valuable information assets and maintaining the stability of cyberspace.

Configuración de una red LAN utilizando Python scripting para generar redes definidas por software (SDN).

Network management is an essential task in modern organizations, where the complexity of technological infrastructures demands efficient and accurate solutions. With network devices from leading manufacturers such as Cisco and Mikrotik. In response to these challenges, automating the configuration of network devices has gained popularity as an approach to improve efficiency and reduce errors. Python, a programming language widely adopted for its versatility and ease of use, has become a key tool for this automation. Within this ecosystem, Netmiko emerges as a specialized library that facilitates automated interaction with network devices using SSH. Netmiko allows network administrators to write scripts that can connect to Cisco and Mikrotik devices, execute configuration commands, and retrieve information about the network status. This approach not only speeds up the configuration process, but also ensures consistency and accuracy in deploying configurations, especially in multi-device environments. As networks continue to grow in complexity, the adoption of tools such as Netmiko becomes essential to maintaining the operability and security of network infrastructures.

Will Network Infrastructure Optimization Make Manufacturing Enterprises "Out of Real to Virtual"? --- A Quasi-Natural Experiment from the "Broadband China" Policy

Manufacturing is the most important component of the real economy, and the application of modern network information technology can effectively improve the operational efficiency of manufacturing enterprises. In the context of "Made in China 2025", it is particularly important to prevent manufacturing enterprises from deviating from their main business and becoming excessively financialized. Maintaining the essential business activities of manufacturing enterprises is of great importance to China's economic development. Based on the operating data of all A-share listed manufacturing companies from 2010 to 2020 and combining the "Broadband China" demonstration city policy, this paper uses a multi-point double-differenced model to explore the relationship between network infrastructure optimization and excessive financialization of manufacturing enterprises. The research shows that: 1) Network infrastructure optimization will make manufacturing enterprises increase their financialization level, and this effect is mainly manifested through optimizing accounts receivable management. 2) From the perspective of enterprise size, compared with small and medium-sized manufacturing enterprises, large manufacturing enterprises are more likely to improve their financialization level through network infrastructure optimization. 3) From the perspective of the degree of diversified operations, manufacturing enterprises with high diversified operations are more likely to take advantage of network infrastructure to improve their financialization level. This study provides reference and guidance for later researchers on the impact of "new infrastructure" represented by network infrastructure construction on the business model of manufacturing enterprises.

Bridging the Gap to 6G: Leveraging the Synergy of Standardization and Adaptability

The field of wireless network and communication technology is evolving from generation to generation from 1G to 6G as of now till expected to be deployed and used by 2030. It is to succeed in 5G and bring significant improvements in terms of connectivity, speed, and size in next-generation communication technology. 6G aims to deal with the rising need for more rapid information speed, low latency, and wider network coverage. This intelligent communication is proposed to meet these demands and enable new services and applications. This review paper highlights the key enablers and challenges involved in implementing intelligent communication beyond 5G. The paper identifies the research gaps for incorporating beyond 5G communication networks and outlines the possible 6G key objectives from a flexibility standpoint. It reviews infrastructure deployment, network densification, spectrum capacity and network energy efficiency in predecessors to 6G. This paper emphasizes the need for standardization and adaptation of research areas to revolutionize 6G wireless communication, focusing on areas like, ultra massive MIMO, Terahertz Communications, Cell-Free Communications, Intelligent Reflecting Surface, Visible Light Communication, Internet of Things, Big Data management, Artificial Intelligence, and network connectivity techniques.

Quantum-Secured Data Centre Interconnect in a field environment

In the evolving landscape of quantum technology, the increasing prominence of quantum computing poses a significant threat to the security of conventional public key infrastructure. Quantum key distribution (QKD), an established quantum technology at a high readiness level, emerges as a viable solution with commercial adoption potential. QKD facilitates the establishment of secure symmetric random bit strings between two geographically separated, trustworthy entities, safeguarding communications from potential eavesdropping. In particular, data centre interconnects can leverage the potential of QKD devices to ensure the secure transmission of critical and sensitive information in preserving the confidentiality, security, and integrity of their stored data. In this article, we present the successful implementation of a QKD field trial within a commercial data centre environment that utilises the existing fibre network infrastructure. The achieved average secret key rate of 2.392 kbps and an average quantum bit error rate of less than 2% demonstrate the commercial feasibility of QKD in real-world scenarios. As a use case study, we demonstrate the secure transfer of files between two data centres through the Quantum-Secured Virtual Private Network, utilising secret keys generated by the QKD devices. %This demonstration marks a significant milestone in the deployment of QKD across Singapore, establishing a foundation for widespread adoption and enhancing the infrastructure for practical, quantum-safe communication in commercial environments.

BBR-R: Improving BBR performance in multi-flow competition scenarios

The development of network infrastructures and the evolving demands of internet services impose higher requirements on congestion control algorithms. Although Google’s BBR algorithm achieves lower latency and higher goodput compared to traditional congestion control algorithms, it still has many issues. BBR sets the congestion window larger than the calculated ideal value to prevent transmission stalling in the presence of delayed and aggregated ACKs. However, in scenarios with multi-flow competition, this compromise on the congestion window leads to large amounts of queued data, causing increased latency and decreased fairness. Additionally, the ProbeRTT mechanism deviates from its original intent. In this study, we analyze the existing issues of the BBR algorithm from a theoretical standpoint and propose the BBR-R algorithm, which incorporates an adaptive sending rate adjustment mechanism and a new ProbeRTT triggering mechanism. While maintaining the ability for dynamic bandwidth exploration, the sending rate is adjusted based on a latency-related factor called Adaptive_RTprop to control the over-injected data. Coupled with the new ProbeRTT triggering mechanism, BBR-R reduces the frequency of entering the ProbeRTT phase and thereby improves transmission stability. In conducted experiments, BBR-R decreases the frequency of entering the ProbeRTT phase in many scenarios, achieves a 41.86% reduction in latency in the dual-flow competition scenario, and improves fairness by 22.79% in the five-flow competition scenario.