Network Path Research Articles

ENDEMIC: End-to-End Network Disruptions - Examining Middleboxes, Issues, and Countermeasures - A Survey

Network middleboxes are important components in modern networking systems, impacting approximately 40% of network paths according to recent studies [1]. This survey paper delves into their endemic presence, enriches the original 2002 RFC with over two decades of findings, and emphasizes the significance of their impact in terms of security and performance. Furthermore, it categorizes network middleboxes based on their functions, objectives, and alterations. In today’s world, network middleboxes emerge as a dual-edged sword. While important for network operations, they also pose security risks. We present the various challenges they introduce, including their contribution to Internet ossification, their potential for censorship, monitoring, and traffic differentiation. Substantial effort remains to make their presence more visible to end users. This paper explores potential solutions, ranging from prevention and detection to curative measures. Ultimately, we aim to establish this survey as a foundational resource for addressing challenges revolving around the notion of network middleboxes, thereby fostering further research and innovation in this area.

Path selection and network equilibrium under non-extreme flood disturbances

Path selection and network equilibrium under non-extreme flood disturbances

Solving Multi-Criteria Shortest Path by Optimization with Morphological Filters

The challenge of determining the shortest path within a multimodal transportation network involves identifying the most efficient travel route while considering various interconnected modes of transportation, such as roads, railways, and public transit. This problem becomes increasingly complex when numerous criteria and modes are involved, complicating the decision-making process. This study proposes a novel approach to computing the shortest path in multimodal networks, focusing on four modes of transportation: metro, trams, buses, and taxis. The optimization criteria include distance, travel time, and monetary cost. The proposed method utilizes a new metaheuristic called Optimization by Morphological Filters (OMF), inspired by image processing techniques. This approach was compared with the Genetic Algorithms (GA) and the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). Experiments were carried out using graph models of multimodal transport networks that closely resemble real-world scenarios varying in size. Furthermore, the proposed method was evaluated using a real network from the city of Lyon, France. The results demonstrate that the OMF approach performs well in terms of convergence to optimal solutions and computation time.

HMLPA*: a hierarchical multi-target LPA* pathfinding algorithm designed for dynamic indoor path network

The Lifelong Planning A* (LPA*) algorithm demonstrates unique advantages in dynamic pathfinding by employing incremental update techniques that reuse previously computed search results, enabling rapid path replanning in dynamic road network environments. However, when changes occur near the starting point or specific positions, such as key intersections, bottlenecks, or locations with high connectivity within the path network, even minor changes can trigger significant adjustments, which significantly increase the re-routing search space and computational costs of LPA*. To address this limitation, we propose a Hierarchical Multi-target LPA* (HMLPA*) algorithm that partitions the indoor path network into multiple subgraphs using the METIS graph partitioning algorithm and constructs an abstract trunk graph based on the key nodes of these subgraphs, thereby forming a hierarchical structure for the indoor path network. By leveraging this hierarchical structure, The HMLPA*’s subalgorithm, Multi-target LPA* (MLPA*), initiates pathfinding and confines re-routing to affected subgraphs and the abstract trunk graph. This localized re-routing approach effectively limits the search scope and significantly reduces computational overhead. Experimental results demonstrate that HMLPA* substantially outperforms LPA* in rerouting efficiency, effectively mitigating the high computational costs associated with the dynamic computational environment of the indoor path network.

Impact of tourist and recreational activities on the indicators of soil-ecological monitoring of the adjacent territory of Lake Teletskoe (Altai Mountains)

Relevance. The increasing recreational load on the ecosystems of the Lake Teletskoe basin, its related obvious damage and the necessity to quantify the ongoing transformations. Aim. To assess the current state of a soil cover of the adjacent territory of Lake Teletskoe in terms of tourism and recreation impact. Methods. Comparative geographical and chemical as well as soil-ecological monitoring of studied indicators of early, short- and long-term diagnostics. Results and conclusions. Because of the tourist activities in the coastal zone of the mountain-forest belt of Lake Teletskoe, a developed path network transforming its natural ecosystems appeared. Some parameters of soil properties and composition on this path and in the sites not affected by recreation differed significantly. The analysis of water extract showed the decrease in acidity, the reduced content of ammonium and nitrate nitrogen, phosphates, a change in the concentration of calcium cations, potassium and magnesium in the top soil layer on the path, as compared to the undisturbed places. Soil trampling by recreants has damaged litter, decreased its thickness or completely destructed the promenade area. Reduction in litter reserves on the moderately developed paths exceeded by more than 2.7–4.0 times, whereas on the well-defined ones (as in the Altai State Biosphere Reserve with the established systemized movement across the territory), litter was absent at all on a few or even single paths. On weakly developed (fresh) paths, litter reserves turned out to be even higher than on the undisturbed areas or on the paths located next to a gravel site. Recreational loads were responsible for the 1.2–1.7 times increase in soil density of the upper (0–5 cm) layer, accompanied by a decrease in soil porosity and air supply. The hardness of soil was 1.3–1.5 times higher on the path than around it. The tourist effect on general physical properties of soil was traced to a depth of 20–30 cm, but maximum changes were noted in its upper (0–5 cm) layer. Recreational loads did not impact essentially on the aggregate soil composition. No significant changes, caused by tourist and recreational activities, were found in the elemental chemical composition of soils. The content of nutrients and lead were within the background and did not exceed the standardized values. The detected high concentrations of arsenic were not associated with the influence of tourist and recreational activities.

Enhancing Real-Time Video Streaming Quality via MPT-GRE Multipath Network

The demand for real-time 4K video streaming has introduced technical challenges due to the high bandwidth, low latency, and minimal jitter required for high-quality user experience. Traditional single-path networks often fail to meet these requirements, especially under network congestion and packet loss conditions, which degrade video quality and disrupt streaming stability. This study evaluates Multipath tunnel- Generic Routing Encapsulation (MPT-GRE), a technology designed to address these challenges by enabling simultaneous data transmission across multiple network paths. By aggregating bandwidth and adapting dynamically to network conditions, MPT-GRE enhances resilience, maintains quality during network disruptions, and offers throughput nearly equal to the sum of its physical paths’ throughput. This feature ensures that even if one path fails, the technology seamlessly continues streaming through the remaining path, significantly reducing interruptions. We measured key video quality metrics to assess MPT-GRE’s performance: Structural Similarity Index Measure (SSIM), Mean Squared Error (MSE), and Peak Signal-to-Noise Ratio (PSNR). Our results confirm that the MPT-GRE tunnel effectively improves SSIM, PSNR, and reduces MSE compared to single-path streaming, offering a more stable, high-quality viewing experience. Our results indicate that analyzing the SSIM, MSE, and PSNR values for 4K video streaming using the MPT tunnel demonstrates a significant performance improvement compared to a single path. The improvement percentages of the SSIM and PSNR values for the MPT tunnel are (29.05% and 29.04%) higher than that of the single path, while MSE is reduced by 81.17% compared to the single path.

Association of quality of life in older patients with breast cancer: a cross-sectional study from China

ObjectivesThe purpose of this study was to investigate the quality of life (QoL) of older Chinese patients with breast cancer and to explore further the associations of functions, symptoms, financial...

Automating the search for the shortest closed path in transport network by means of MATLAB

The paper considers the problem of automating the search and construction of the shortest closed route for a group of merchant ships on a given set of transit nodes of the transport network with known coordinates. The goal is to find the shortest closed route that passes through all hosts only once and ends at the outgoing node. In general, a weighted graph can serve as a mathematical model of such a transport network, in which the criterion for the efficiency of the desired route can be, for example, the distance between cities or ports, time or operating costs. This allows you to identify time reserves that can be used to save fuel and energy, taking into account the load and cost of goods, travel costs and other factors. The work uses a combinatorial method using stochastic (probabilistic) programming, which is implemented using an annealing simulation algorithm supplemented by a recursive step-by-step optimization procedure. The problem belongs to the class of transcomputational even with a small network dimension, which makes it impossible to solve it by brute force on modern computers in a reasonable time. The proposed modification of the simulated annealing algorithm eliminates this limitation and allows not only to evaluate the shortest paths in the network, but also to build closed paths that pass through all the vertices of the network once. The use of an iterative strategy in the algorithm using a probabilistic scenario according to the Monte Carlo method allows you to avoid the solution falling into the local minimum and provides global optimization. The algorithm is implemented in MATLAB codes in the form of a recursive step-by-step optimization procedure with the construction of a curve of a closed route on the coordinate plane through the entire set of nodes of the transport network without mutual intersections of its sections. It is shown that the result of recursive optimization is to obtain a numerical estimate of the closed path of the minimum weight in the full weighted graph, which is a model of the transport network with the definition of an array of transit node numbers on this route. The developed algorithm and global optimization procedure can be used to automate the search for energy-efficient solutions in the control of robotic and unmanned objects, as well as ships in the performance of cargo transportation in water transport.

Optimization of Path for Road Network With Modified Ant Colony Optimization (MACO)

ABSTRACTOptimizing routes in road networks is crucial for smooth transportation and economic progress. Different methods exist for finding the best routes, including genetic algorithms, particle swarm optimization, and simulated annealing. Ant Colony Optimization (ACO) stands out for its efficiency. In this study, we introduce a modified version called MACO, which considers accidents when determining optimal routes. Evaluating different ACO versions reveals differences in solution quality, runtime, and number of iterations. Performance metrics including maximum obtained solution, runtime, and iteration number were evaluated for each method. In Case 1, TACO, and AACO both achieved a maximum of 21 solutions from the available possible solution of 24, exhibiting run‐times of 0.4359 and 0.4575 s, respectively. Meanwhile, MACO attained a maximum of 22 solutions from available possible solution 24, in a runtime of 0.5345 s and 10 iterations. In the second scenario, TACO, AACO, and MACO achieved maximum solutions of 20 with obtained solutions of 15, 16, and 17, respectively. TACO demonstrated a runtime of 0.1853 s with 26 iterations, AACO ran in 0.1749 s with 22 iterations, and MACO completed in 0.5799 s with 15 iterations. These findings highlight the varying performance of the optimization methods and suggest MACO as a promising approach for balancing solution quality and computational efficiency in road network path optimization.

LIA: Latency-Improved Adaptive routing for Dragonfly networks

Low-diameter network topologies require non-minimal routing, such as Valiant routing, to avoid network congestion under challenging traffic patterns like the so-called adversarial. However, this mechanism tends to increase the average path length, base latency, and network load. The use of shorter non-minimal paths has the potential to enhance performance, but it may also introduce congestion depending on the traffic patterns. This paper introduces LIA (Latency-Improved Adaptive), a routing mechanism for Dragonfly networks which dynamically exploits minimal and non-minimal paths. LIA harnesses the traffic counters already present in contemporary switches to determine when it is safe to shorten non-minimal paths and to adjust routing decisions based on their information about the network conditions. Evaluations reveal that LIA achieves nearly optimal latency, outperforming state-of-the-art adaptive routing mechanisms by reducing latency by up to 30% while maintaining stable throughput and fairness.

Enhancing Cognitive Navigation for Sustainable Campus Environments: Insights from Path Network Evaluation Surrounding Egyptian Universities

Cognitive navigation, crucial in architectural and urban planning, involves the mental processes individuals use for navigation within spatial environments. This study investigates the relationship between a path network design and cognitive navigation experiences surrounding closed-access university campuses, focusing on design optimization’s impact on user experience and its alignment with Sustainable Development Goals (SDGs). Employing a mixed-methods approach, the research encompasses site visits, quantitative surveys of 120 randomly selected cases, and qualitative surveys of 60 cases from universities in Egypt. Findings reveal significant factors influencing path choices, such as directness and clear signage, with 77% of participants encountering navigation obstacles. Public universities prioritize clear pathways, while private institutions emphasize scenic views and landmarks. The study highlights the moderate integration of cultural and contextual elements and identifies key challenges, including traffic congestion and signage difficulties. Conclusions underscore the importance of user-centered design, infrastructure improvements, cultural sensitivity, and dynamic campus environments in optimizing path networks. This research aligns with SDGs by promoting good health and well-being (SDG 3), quality education (SDG 4), innovation and infrastructure (SDG 9), sustainable cities and communities (SDG 11), climate action (SDG 13), and life on land (SDG 15), providing valuable insights for enhancing navigable, sustainable, and intuitive educational spaces.

Ranking paths in road networks for equitable improvement in connectivity during disasters

Ranking paths in road networks for equitable improvement in connectivity during disasters

DateLine: Efficient Algorithm for Computing Region Disjoint Paths in Backbone Networks

DateLine: Efficient Algorithm for Computing Region Disjoint Paths in Backbone Networks

Stable Soil Biota Network Enhances Soil Multifunctionality in Agroecosystems.

Unraveling how agricultural management practices affect soil biota network complexity and stability and how these changes relate to soil processes and functions is critical for the development of sustainable agriculture. However, our understanding of these knowledge still remains unclear. Here, we explored the effects of soil management intensity on soil biota network complexity, stability, and soil multifunctionality, as well as the relationships among these factors. Four typical land use types representing a gradient of disturbance intensity were selected in calcareous and red soils in southwest China. The four land use types with increasing disturbance intensity included pasture, sugarcane farmland, rice paddy fields, and maize cropland. The network cohesion, the network topological features (e.g., average degree, average clustering coefficient, average path length, network diameter, graph density, and modularity), and the average variation degree were used to evaluate the strength of interactions between species, soil biota network complexity, and the network stability, respectively. The results showed that intensive soil management increased species competition and soil biota network complexity but decreased soil biota network stability. Soil microfauna (e.g., nematode, protozoa, and arthropoda) stabilized the entire soil biota network through top-down control. Soil biota network stability rather than soil biota network complexity or soil biodiversity predicted the dynamics of soil multifunctionality. Specifically, stable soil communities, in both the entire soil biota network and selected soil organism groups (e.g., archaea, bacteria, fungi, arthropoda, nematode, protozoa, viridiplantae, and viruses), support high soil multifunctionality. In particular, soil microfauna stability had more contributions to soil multifunctionality than the stability of soil microbial communities. This result was further supported by network analysis, which showed that modules 1 and 4 had greater numbers of soil microfauna species and explained more variation of soil multifunctionality. Our study highlights that soil biota network stability should be considered a key factor in improving agricultural sustainability and crop productivity in the context of increasing global agricultural intensification.

Towards the computer systems design based on Zero Trust Architecture

The work is devoted to theoretical and practical aspects of computer systems design based on the zero trust concept. Based on the system thinking of analyzing existing zero trust systems and theoretical models used in their design, the work describes key problems of implementing zero trust systems. Also, based on design and security patterns, the principles representation of the zero trust concept and the abstract access control model (pattern) of the Zero Trust Architecture are considered.The principles representation can be used to mine abstract design and security patterns, and the access control pattern – to create derivative patterns and architectures of computer systems based on zero trust. An advance of the access control pattern is the capacity to more fully formulate functional requirements and represent the architectures of the designed systems due to the description of access control levels (network path, session, transaction).

A risk-based unmanned aerial vehicle path planning scheme for complex air-ground environments.

Multifarious applications of unmanned aerial vehicles (UAVs) are thriving in extensive fields and facilitating our lives. However, the potential third-party risks (TPRs) on the ground are neglected by developers and companies, which limits large-scale commercialization. Risk assessment is an efficacious method for mitigating TPRs before undertaking flight tasks. This article incorporates the probability of UAV crashing into the TPR assessment model and employs an A* path-planning algorithm to optimize the trade-off between operational TPR cost and economic cost, thereby maximizing overall benefits. Experiments demonstrate the algorithm outperforms both the best-first-search algorithm and Dijkstra's algorithm. In comparison with the path with the least distance, initially, the trade-off results in a increase in distance while achieving an reduction in TPR. As the trade-off progresses, this relationship shifts, leading to a reduction in the distance with only a negligible increase in TPR by 0.0001, matching the TPR-cost-based algorithm. Furthermore, we conduct simulations on the configuration of UAV path networks in five major cities in China based on real-world travel data and building data. Results reveal that the networks consist of one-way paths that are staggered in height. Moreover, in coastal cities particularly, the networks tend to extend over the sea, where the TPR cost istrivial.

Code and Data Repository for A Bilevel Optimization Approach for a Class of Combinatorial Problems with Disruptions and Probing

The "data" folder contains all the datasets used in the paper, including the shortest path networks in DIMACS format and the project selection (knapsack) problem instances. For the project selection problem instances, the files display the nominal profits, the weigths, and the right-hand-side coefficient. The name of the files present the size (network size for shortest path and number of items for knapsack) as well as the random seed used for its generation (a number between 0 and 9 corresponding to each one of the ten replicas per configuration).

A Multi-Attribute Decision-Making Approach for Critical Node Identification in Complex Networks.

Correctly identifying influential nodes in a complex network and implementing targeted protection measures can significantly enhance the overall security of the network. Currently, indicators such as degree centrality, closeness centrality, betweenness centrality, H-index, and K-shell are commonly used to measure node influence. Although these indicators can identify critical nodes to some extent, they often consider node attributes from a narrow perspective and have certain limitations. Therefore, evaluating the importance of nodes using most existing indicators remains incomplete. In this paper, we propose the multi-attribute CRITIC-TOPSIS network decision indicator, or MCTNDI, which integrates closeness centrality, betweenness centrality, H-index, and network constraint coefficients to identify critical nodes in a network. This indicator combines information from multiple perspectives, including local neighborhood importance, network topological location, path centrality, and node mutual information, thereby solving the issue of the one-sided perspective of single indicators and providing a more comprehensive measure of node importance. Additionally, MCTNDI is validated through the analysis of several real-world networks, including the Contiguous USA network, Dolphins network, USAir97 network, and Tech-routers-rf network. The validation is conducted from four aspects: the results of simulated network attacks, the distribution of node importance, the monotonicity of rankings, and the similarity of indicators, illustrating MCTNDI's effectiveness in real networks.

Travel patterns and factors explaining green space use for outdoor learning among school and preschool children

Purpose This study aims to examine travel patterns and factors that explain children’s use of green space for outdoor learning. This knowledge will be valuable for urban planners and policymakers to plan, design, develop and maintain green spaces that consider children’s interests. Design/methodology/approach The analysis consists of three steps. First, this paper performed a mapping analysis to explain the accessibility and services of green spaces in supporting children’s education. Second, using data from a survey distributed to school teachers, this paper explored factors affecting trip frequency, travel distance and walking when visiting green spaces. Third, this paper interviewed teachers and conducted observations and conversations with children to gain additional insights. Findings The quantitative analyses found that size, path network linkages, path length, use for nature observation, play features, path density, walking and biking may influence children’s preference for using green spaces. This study identified five factors (playing, socialising, exploring, biodiversity and accessibility) that drive children to visit green spaces. Originality/value There is limited knowledge of the links between green space and children’s travel patterns and factors explaining the use of green spaces. To the ebst of the authors’ knowledge, this study seems to be the first attempt to introduce a mix of methods containing mapping, qualitative and quantitative analyses to explain children’s use towards green spaces.

A systematic assertive wide-band routing using location and potential aware technique

Delays occur when packets must be routed over several paths in a wireless sensor network with multiple origins and destinations. There are several causes, delays may occur everywhere, even in a multi-hop wireless network. Due to the broadcast nature of wireless networks, opportunistic routing was able to circumvent these delays. To avoid unnecessary delays, wide-band routing may be used to calculate the smaller path between two nodes. In this case, we address the shortcomings of the standard approach by taking into account the node's power. Path routing as well as the broadcast nature of wireless signals help mitigate the effects of shoddy wireless connections. The results show that the suggested approach outperformed the baseline in both end-to-end latency and packet delivery ratio.