Improve Network Connectivity Research Articles

F-Bypass: a low-power network-on-chip design utilizing bypass to improve network connectivity

With the development of transistor feature size to nanometer level, static power consumption has gradually become the main factor affecting the overall power consumption of network on chip (NoC). Power gating is an effective technology to reduce static power consumption, but it also brings new challenges, such as BET violation, wake-up latency and network connectivity. Therefore, a power gating method is needed to improve NoC performance and reduce static power consumption. This paper proposes a low-power bypass method, namely Forwarding bypass (F-Bypass). First, F-Bypass adds bypass paths between all input and output ports and the network interface (NI), and connects the pop-up port and injection port in NI through the bypass path. When the router is powered off, F-Bypass performs wake-up-free packet transmission, which reduces the break-even time (BET) violation and cumulative wake-up latency while ensuring network connectivity. Secondly, This paper add the modified VC state table to NI, so that the power-off router can perform normal traffic control. Finally, a new wake-up criterion is proposed, which can effectively avoid the frequent wake-up of power-off routers, and the detailed hardware implementation of F-Bypass is provided.The simulation results under integrated traffic load show that compared with the traditional scheme, the delay of F-Bypass is reduced by 2.2%, the throughput is increased by 13.1%, and the total static power consumption is reduced by 75.2%. Key performance indicators are superior to other solutions, and the increased area cost is moderate.

A topological network connectivity design problem based on spectral analysis

How to improve network connectivity and which parts of the network are vulnerable are critical issues. We begin by defining an equal distribution problem, in which supplies are distributed equally to all nodes in the network. We then derive a topological network connectivity measure from the convergence speed, which is the second minimum eigenvalue of a Laplacian network matrix. Based on the equal distribution problem, we propose a method for identifying critical links for network connectivity using the derivative of the second minimum eigenvalue. Furthermore, we develop a network design problem that maximizes topological connectivity within a budget creating strengthening network links. The problem is convex programming, and the solution is global. Furthermore, it can be converted into an identical semidefinite programming problem, which requires less computational effort. Finally, we test the developed problems on road networks in the Japanese prefectures of Ishikawa and Toyama to determine their applicability and validity.

Articulating the dynamics among stakeholders in KwaZulu-Natal's bather-shark conflict to create a productive research-implementation space

Research-implementation gaps pervade conservation practice. However, reconceptualising these gaps as productive learning spaces for stakeholder engagement can yield solutions. The first step in this process is to identify the stakeholders to engage in this research-implementation space and understand their relationships. An important research-implementation gap arose when research showed that fishing gear, set on South Africa's east coast to protect bathers from sharks, was a threat to endangered dolphins that were caught incidentally. It became apparent that it was necessary to improve our understanding of the social aspects of the human-wildlife conflict involving bathers and sharks. In this study, we aimed to (i) identify stakeholders in this bather-shark conflict and their involvement and (ii) describe the dynamics among these stakeholders. We interviewed 29 stakeholders whose work intersects with the conflict, assessed perceptions of their influence and interest, and the structure of their communication network. We found that governance is top-down and the communication network is small with limited information flow about non-lethal alternatives to the current fishing method. Since power dynamics impact conservation initiatives, articulating the relative decision-making positions may aid future negotiations for conservation. In small networks, such as this one, improving connectivity and thus information flow can transform the system. Forming a Working Group composed of interested and affected stakeholders who contribute knowledge and diverse perspectives could make governance more inclusive and improve network connectivity. Our research simultaneously identified who to work with in this research-implementation space and began the process of learning together to improve the flow of information.

Prioritization of Ecological Conservation and Restoration Areas through Ecological Networks: A Case Study of Nanchang City, China

Rapid urbanization has led to ecosystem fragmentation, conversion, and degradation, posing great threats to natural habitat and biodiversity. The utilization of ecological networks has gained importance in ecological restoration planning to mitigate the negative impacts of urbanization on ecosystems. This study focused on Nanchang City, China, as a case study area to examine the application of integrated ecological networks in 2000, 2010 and 2020. This study analyzed the dynamic characteristics and spatial differences in landscape connectivity, providing evidence-based support for ecological conservation and restoration. The results indicate the following: (1) a decrease in the number of ecological sources and corridors, especially general sources and corridors, along with a decreasing trend in their importance; (2) an increase in ecological barrier points and breakpoints over time, especially in the southeastern region of the study area; and (3) the identification of ecological conservation priority areas, ecological improvement priority areas, and ecological restoration points based on connectivity and dynamic analysis. Multiple priority actions were proposed, which remarkably improved network connectivity and strengthened biodiversity conservation. Our research provides a valuable reference for identifying ecological priorities and developing ecological protection and ecological restoration actions in highly urbanized areas.

Advanced Dual-Band Antenna for Optimised Vehicular Communication Systems

The advancement of Intelligent Transportation Systems (ITS) has rendered the development of robust communication networks critical. Within the realm of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) exchanges, this necessity becomes even more pronounced. Addressing this pivotal requirement, our study details the design and realisation of a sophisticated dual-frequency antenna system. Utilising the cutting-edge Advanced Design System (ADS) software, the design targets efficacious support for V2V and V2I communications across separate frequency bands, thus mitigating interference and enhancing data throughput, crucial for uninterrupted connectivity. Through rigorous simulations, modelling, iterative optimisation, and meticulous prototyping, the design is actualised. Preliminary testing demonstrated the antenna’s superior performance in gain, bandwidth, and radiation patterns within the designated frequencies. These performance indicators are essential for reliable communication in dynamic vehicular environments. As vehicles evolve towards greater intelligence, the demand for powerful communicative instruments, such as this antenna, becomes unequivocal. The proposed design not only promises improved network connectivity but also fosters advancements in road safety and traffic efficiency. This investigation lays the groundwork for setting benchmarks in future vehicular antenna communications, articulating the benefits of the proposed system and charting a course for subsequent technological breakthroughs. The ultimate objective remains to hone this design for seamless incorporation into diverse automotive systems. Summarily, the paper presents an intersection of innovation and practical application, casting light on the prospective trajectory of V2V and V2I communications.

Metro-line expansions and local air quality in Shenzhen: Focusing on network effects

We examine the air-quality effects of urban-rail development in Shenzhen, taking a difference-in-differences approach. This study is motivated by existing mixed evidence on the rail-pollution relationship, which we associate with the dynamic nature of the relationship itself. Our results demonstrate that the relationship varies by time, depending on network density and scale. New station openings had no significant impacts on local air quality or even worsened it until the 2010 metro-line extension, when Shenzhen’s metro network density was still low, with limited spatial service coverage. However, the 2016 extension significantly abated air pollution as the network grew denser and more comprehensive. The rail-driven anti-pollution effects tended to be further strengthened with externalities arising from improved network connectivity, spilling over the effects beyond newly opened stations to preexisting ones. Also, metro stations in proximity to neighborhoods that share key characteristics in transit-oriented development tended to generate a greater anti-pollution effect.

Neighborhood Food Accessibility and Health Disparity: Examining the Impact of COVID-19 Using Spatial Models

COVID-19 exacerbated food system vulnerabilities globally. This study assesses the impact of shock events on food accessibility in New York City (NYC) by examining its association with neighborhood characteristics between 2019 and 2020. We model food accessibility using socioeconomic and built environment factors, adjusting for spatial effects with spatial econometric models and geographically weighted regression (GWR). Our spatial modeling methods reveal diverging relationships between minority racial/ethnic groups and food accessibility, as well as a negative change in the effect of income. Overall, our results indicate that food accessibility worsened or polarized during the pandemic, suggesting the need for improved network connectivity and smaller-scale food stores to achieve equitable and resilient food systems.

A method for reliability assessment of complex electromechanical system based on improved network connectivity entropy

The interconnectivity of components in complex electromechanical system (CMES) plays a critical role in ensuring system reliability. To examine the effect of component failures on system reliability, this work proposes a new reliability assessment method for CEMS based on improved network connectivity entropy. This method takes into account the mechanical, electrical, and information characteristics of components, and employs a comprehensive component importance calculation approach based on PageRank, which considers the functional impact of components. The reliability assessment model, considering both functional and topological attributes of the system, is established through the theory of network connectivity entropy. The proposed method is then demonstrated through an application to a bogie system of the CRH2008A high-speed railway. The proposed approach, rooted in topological networks, integrates component degradation into the physical structure of CEMS, providing a comprehensive way to deduce the impact of component failures on system reliability. Validity is demonstrated through case studies.

Probabilistic connectivity assessment of bridge networks considering spatial correlations associated with flood and seismic hazards

To estimate the connectivity of a road network, it is crucial to evaluate the correlation of hazard intensities among individual bridge locations since the probability of multiple bridges being damaged simultaneously depends on the degree of this correlation. However, research on connectivity assessment of bridge networks considering spatial correlations associated with flood intensities is scarce in the literature. When quantifying the spatial correlation of flood intensities, modeling based on the stream distance rather than the Euclidean distance is required, taking into account that river flow is restricted only within the stream network. To achieve this purpose, a novel methodology is proposed to evaluate the spatial correlation of a stream network based on a geostatistical linear model and stream network covariance models. In addition, this study considers the spatial correlation of seismic hazard intensity. With the proposed method, it is possible to identify which bridges play an important role in ensuring the connectivity of the road network under multiple hazards, i.e. flood and seismic. As an illustrative example, the proposed method is applied to a hypothetical bridge network in Kumamoto Prefecture, Japan. The results demonstrate that improved network connectivity can be achieved by implementing a relevant retrofitting strategy for important bridges.

Optimization of Coverage and Capacity Using Smart Antennae

In the rural and geographically remote regions of Taiwan, the high cost of establishing information infrastructure has resulted in significantly lower internet penetration and usage rates compared with urban areas. To address the network demands in such remote mountainous areas, the deployment of multiple mobile base stations has become essential. However, the wireless implementation of base stations can lead to signal interference issues. This research aims to enhance the signal reception capabilities of end-user devices by utilizing intelligent directional antennas. This study employs five directional smart antennas, each of which can be independently adjusted to be active or inactive. Unlike traditional omnidirectional antennas that cause interference in overlapping coverage areas for end-user devices, our proposed adaptive directional antenna algorithm optimizes energy consumption by selectively activating directional antennas and concurrently reduces signal interference problems for end-user devices. The results of this research offer valuable insights for improving network connectivity and efficiency in remote and underserved areas. Through experimental simulations conducted in an environment with 10 base stations per square kilometer, the utilization of smart antennas, as opposed to omnidirectional antennas, results in a significant improvement of 33.8% in signal coverage.

Understanding Global Rice Trade Flows: Network Evolution and Implications.

Rice holds a significant position as one of the world's most important food crops, and international trade plays a crucial role in regulating rice supply and demand. Analyzing the structural evolution of the global rice trade from a network perspective is paramount for understanding the global rice-trade supply chain and ensuring global food security. This study utilizes international rice-trade data from 2000 to 2021 and employs various network analysis methods to depict the spatial and temporal patterns of the global rice trade, examines the network topologies of the global rice trade, and reveals the impacts of its evolution on food security. The research findings are as follows: (1) Global rice-trade scale has increased over time, indicating a relatively stable development with the gradual formation of complex rice-trade networks. Since 2000, the global rice-trade networks have shown increasing density characterized by Asia as the primary export source and Africa as an important import market. (2) Network analysis indicators demonstrate a growing trend in the size and density of the global rice-trade networks, along with increasingly optimized network structures and improved network connectivity efficiency. Core positions in the networks are occupied by Thailand, Vietnam, India, China, Pakistan, and the United States, while import partners in European and American countries, such as Germany, France, UK, Canada, The Netherlands, and Belgium, show greater diversification. Asia, Europe, and North America form agglomeration regions for rice-exporting countries. Additionally, importing and exporting countries in the global rice-trade networks exhibit certain geographical concentrations. (3) The network backbones of the global rice trade are continuously evolving and being refined, characterized by dominant large rice-exporting countries in Asia and prominent developed countries in Europe and North America. The backbone structures revolve around India as the core, Thailand and Pakistan as the second cores, and critical nodes represented by Italy, the United States, China, and Vietnam. Regional backbone networks have also formed in Asia and Europe. Based on these findings, this paper clarifies the complex network characteristics of the global rice trade and offers insights to promote international rice-trade cooperation and safeguard global food security.

Boosting Thermoelectric Power Factor of Carbon Nanotube Networks with Excluded Volume by Co-Embedded Microparticles.

Carbon nanotube (CNT) networks embedded in a polymer matrix have been extensively studied as a flexible thermoelectric transport medium over the recent years. However, their power factor has been largely limited by the relatively inefficient tunneling transport at junctions between CNTs and the low-density conducting channels throughout the networks. This work demonstrates that significant power factor enhancements can be achieved by adding electrically insulating microscale particles in three-dimensional CNT networks embedded in the polymer matrix. When silica particles of a few μm diameters were co-embedded in single-walled CNT (SWCNT)-polydimethylsiloxane (PDMS) composites, both the electrical conductivity and the Seebeck coefficient were simultaneously enhanced, thereby boosting the power factor by more than a factor of six. We found that the silica microparticles excluded a large volume of the composite from the access of CNTs and caused CNT networks to form around them with the polymer as a binder, resulting in improved network connectivity and alignment of CNTs. Our theoretical calculations based on junction tunneling transport for three-dimensional CNT networks show that the significant power factor enhancement can be attributed to the enhanced tunneling with reduced junction distance between CNTs. Additional power factor enhancement by a factor of three was achieved by sample compression, which further reduced the mean junction distance to enhance tunneling but also reduced the geometric factor at the same time, limiting the enhancement of electrical conductivity.

A social relationship-based energy efficient routing scheme for Opportunistic Internet of Things

Opportunistic Internet of Things (OppIoT) combines Opportunistic Networks and the Internet of Things to provide opportunistic communication between IoT devices and human-created communities in order to improve network connectivity, reliability, and longevity. This is significant because it introduces a new approach to connect and communicate smart devices in situations where there is no end-to-end connectivity. Due to the non-stable existence of connectivity between nodes, building a scalable, flexible, interoperable, and energy efficient routing protocol is a difficult issue. This study presents a new routing protocol for the Opportunistic Internet of Things called Social relationship based Energy Efficient Routing (SEER), which bases routing decisions on the forwarding feasibility degree, residual energy, and buffer capacity of nodes. SEER surpasses EBR and EDR in terms of delivery probability, hop count, and overhead ratio, according to simulation results utilizing the Opportunistic Network Environment (The ONE) simulator.

Topology and evolution of international trade network for fish and fish products

In this study, a complex network method was employed to quantify the changing role of countries in fish trade and the dynamic characteristics of fish globalization. Based on the United Nations Comtrade Database, the International Trade Network for Fish and Fish Products (ITN-Fish) was constructed as a series of weighted-directed networks for each year from 1990 to 2018. Almost all countries and territories worldwide have participated in the fish trade. In 2018, the network identified 229 fish traders. The share of developing countries in imports and exports has increased. Traders actively establish new trade relations, which improve network connectivity. However, these relations only account for a small part of the fish trade. The high connectivity allows risks to spread rapidly in the world through hubs such as the United States and China, which raises concerns about the robustness of these weak links in the Sino-US trade conflict and the outbreak of COVID-19. However, we have optimistic expectations on this issue. The dynamic of network topology property shows that the globalization of fish trade flourished between 1990 and 2018. Although, due to the financial crisis and its subsequent impact, the total amount of fish trade declined in 2009 and 2015, the network structure was not seriously affected, and the trend of topology property remained unchanged. Based on the construction of the international trade network, its node attribute, and its structural attribute, fish trade maintains the trend of globalization. Countries should actively adhere to trade globalization to promote the development of the fish trade.

RLS2: An energy efficient reinforcement learning- based sleep scheduling for energy harvesting WBANs

In the Energy-Harvesting Wireless Body Area Networks (EH-WBAN), one of the fundamental challenges is preserving the self-sustainability of sensors without compromising network reliability and connectivity. Determining the sleep/wake schedule of body nodes (BNs) is an efficient way to achieve self-sustainability. Sleeping nodes should be connected to at least one active node to reduce delay and keep the network connected. There are two fundamental problems with previous methods for determining BN's sleep/wake schedule: (1) BN suffers from emergency packet loss and unnecessary frequent sleeping and waking up, and (2) They do not guarantee network connectivity. Studies that have only examined connectivity in EH-WBAN also have two main issues: (1) BNs are considered homogenous in terms of energy harvesting and its consumption, (2) These methods cannot adapt to the time-varying behavior of energy-harvesting resources. This study proposes a new method for sleep/wake scheduling called Reinforcement Learning-based Sleep Scheduling (RLS2). RLS2 has the following innovative points: (1) To avoid emergency packet loss or unnecessary frequent sleeping and waking up, each BN has its own sleep/wake schedule based on its energy level and sensed data changes, (2) Lowest possible number of BNs are determined as relay nodes in each round to increase network reliability and connectivity; these BNs remain active in each round, while the others operate according to the determined schedule. In this part of the proposed method: (1) Heterogeneous BNs are considered, (2) As a first step in solving adaptability, the problem of finding the optimal active groups is formulated as a Markov decision process (MDP), followed by a Q-learning algorithm capable of learning time-varying behavior of energy harvesting resources, (3) The unavailable action space is removed to reduce the problem's complexity, (4) To achieve good Q-learning performance, a reward function based on residual energy level and neighborhood degree of BNs is defined. It can find an active group with the lowest cardinality in the current round, which is maximum in terms of the residual energy of its sensors. The performed simulations indicate the appropriate convergence of the proposed method. The results show that, on average, the proposed method improves network connectivity and energy efficiency by 50% and 31%, respectively, and reduces network delay by 27%.

IMF 2 O 2 : A Fully Connected Sensor Deployment Algorithm for Underwater Sensor Networks

To address the problems of node deployment schemes in existing underwater sensor networks that lack consideration of network connectivity and high deployment costs, this article constructs an optimization model that maximizes network coverage and minimizes deployment costs while ensuring full connectivity. For the NP-hard property of this optimization model, an improved moth flame optimization node deployment algorithm based on fuzzy operators (IMF 2 O 2 ) is proposed. First, comprehensively considering the two performance metrics of network coverage and network connectivity, a multi-objective selection mechanism based on fuzzy operators is proposed to improve network coverage while ensuring full connectivity. Second, a fixed number of nodes are used to monitor the target event points, transforming the node deployment of sensors into an optimal problem and proposing an improved moth flame optimization algorithm to solve this problem. Finally, the two metrics of coverage and deployment cost are measured and the fuzzy operator is used to select the optimal number of nodes to be deployed. Numerical results showed that the proposed algorithm improved network coverage rate by 10%, 22%, and 25%, and improved network connectivity rate by 12%, 20%, and 8% as compared to PSSD, RAWS, and VODA, respectively, while ensuring full connectivity.

Introducing a Framework for Cycling Investment Prioritization

Concerns over urban congestion, air pollution, and health disparities have prompted many cities to expand their bicycle networks to foster a cycling culture. Given limited budgets, choosing a set of road segments for investments in cycling infrastructure to achieve a city’s ambitious goals is still a challenge. This study introduces a quantitative framework for prioritizing future bicycle improvement projects for implementation within budgetary constraints using different intervention strategies with regard to specific goals and objectives. The “connectivity-focused” prioritization strategy aims to consolidate bicycle networks and improve network connectivity. The “equity-based” strategy grows the bicycle networks and favors cycling equity goals; it prioritizes cycling projects that improve bicycle accessibility to urban opportunities for disadvantaged populations and mitigates disparities in access to bicycle facilities. The “modal shift” strategy seeks to build a bicycle network which would appeal to prospective bicycle commuters and thereby reduce vehicle kilometers traveled (VKT) and greenhouse gas (GHG) emissions. The results highlight the importance of growing bicycle networks in a systematic way and show that this framework is useful for guiding the implementation of new bicycle facilities with specific policy priorities.

A Delaunay Edges and Simulated Annealing-Based Integrated Approach for Mesh Router Placement Optimization in Wireless Mesh Networks.

Wireless Mesh Networks (WMNs) can build a communications infrastructure using only routers (called mesh routers), making it possible to form networks over a wide area at low cost. The mesh routers cover clients (called mesh clients), allowing mesh clients to communicate with different nodes. Since the communication performance of WMNs is affected by the position of mesh routers, the communication performance can be improved by optimizing the mesh router placement. In this paper, we present a Coverage Construction Method (CCM) that optimizes mesh router placement. In addition, we propose an integrated optimization approach that combine Simulated Annealing (SA) and Delaunay Edges (DE) in CCM to improve the performance of mesh router placement optimization. The proposed approach can build and provide a communication infrastructure by WMNs in disaster environments. We consider a real scenario for the placement of mesh clients in an evacuation area of Kurashiki City, Japan. From the simulation results, we found that the proposed approach can optimize the placement of mesh routers in order to cover all mesh clients in the evacuation area. Additionally, the DECCM-based SA approach covers more mesh clients than the CCM-based SA approach on average and can improve network connectivity of WMNs.

A multi-scale analysis framework of different methods used in establishing ecological networks

Ecological networks (ENs) can bridge the paradox between conservation and development. Although many useful methods can be applied to establish ENs, their differences in spatial outputs and scale applicability need to be examined as landscape planners and policymakers start including implementation concerns. Dividing Jiangsu into three scales (i.e., provincial, city cluster, and city scale), we comparatively analyzed the spatial consistency of the structure-oriented, function-oriented and integration-oriented methods in establishing three types of ENs (i.e., SENs, FENs and IENs), and comprehensively assessed their scale applicability under specific goals in improving network connectivity, optimizing landscape pattern and maintaining ecosystem services value (ESV). Our results show that the consistency of the three methods in identifying spatially priorities of protection ranged from 81.03% to 93.70%. A structure-oriented method to establish SENs had applicability in improving network connectivity despite scale changes, while an integration-oriented method to establish IENs had the advantages of forming an ecological space with low fragmentation, high complexity and dominance, and maintaining the maximum ESV, relatively. We discussed the speciality of each method performed at each scale and suggested the possible trade-offs of decision-making in landscape planning which would be complicated during scale changes. Thus, although the applicable method could be selected under clear goals/orientations, its applicability would be limited to different contexts and observational scales. The seemingly inconsistent results could be used synergistically to promote ENs implementation across scales under inclusive decision-making. The developed multi-scale analysis framework and study results can provide new insights to incorporate ENs into landscape planning practice.

Mapping a Green Infrastructure Network: a framework for spatial connectivity applied in Northern Italy

Global environmental changes, including landscape fragmentation, are threatening the integrity of ecosystems and reducing their capacity to deliver ecosystem services. Spatial configuration of a green network supports ecological functions and services, that depend on living organisms and material movements across the landscape. It is important to study the structure of green infrastructure networks and to develop robust methodologies that can inform future planning. In this paper we describe a framework for connectivity analysis and enhancement within the green infrastructure networks. We review and combine methods to map and analyse the current spatial network configuration of green elements, in order to identify the key nodes and links that can maintain connectivity and consequently support the benefits provided across the landscape. The study explores the creation of network scenarios and the improvement or reduction of connectivity by adding, preserving, or removing corridors and core areas. Methods include morphological spatial pattern analysis, landscape connectivity metrics and graph theory elements. The analysis has been applied in the Northern Italian Plain, considering green riparian zones and the protected areas as elements of the network. The results show that this method can be used to analyse the status of green infrastructure networks and to identify the main needs for maintaining and improving network connectivity. This is important in the current context of change, as it may support decision-makers in developing tailored adaptation strategies that exploit nature-based solutions to reduce the risks caused by the major drivers of change.