Green Networks Research Articles

Cooperation and energy harvesting based spectrum sensing schemes for green cognitive radio networks

AbstractCognitive radio network (CRNs) with energy harvesting approach to identify unused spectrum bands and utilize them opportunistically is observed as an evolving technology to handle spectrum scarcity problems. In CRNs, the secondary users (SUs) continuously sense the primary user's (PUs) spectrum to secure the data transmission of PUs and to access the vacant PU's spectrum for their data transmission. For designing future green networks, it is essential that the spectrum sensing process must be accurate, rapid, and energy‐efficient. Therefore, in this work, three sensing schemes are proposed. The first is a cooperation‐based joint cooperation spectrum sensing (JCSS) scheme in which the cooperative CRNs permit the SUs, working in an identical band, to cooperate, and this cooperation approach decreases sensing time and improves sensing probability for vacant spectrum. The result shows that the sensing probability for a vacant spectrum is increased by 34%. The proposed JCSS scheme considers the inherent asymmetry property of the network; therefore, it helps to improve the overall rapidity gain of the networks. The other two proposed sensing schemes, preset spectrum sensing (PSS) and viscous spectrum sensing (VSS), are based on energy harvesting that analyzes the percentage of energy‐saving for various states. The suggested schemes are better in terms of scalability because, in these schemes, it is not essential to sense all spectrums, which leads to a reduction in sensing time.

Blood plasma supply chain planning to respond COVID-19 pandemic: a case study.

The COVID-19 pandemic causes a severe threat to human lives worldwide. Convalescent plasma as supportive care for COVID-19 is critical in reducing the death rate and staying in hospitals. Designing an efficient supply chain network capable of managing convalescent plasma in this situation seems necessary. Although many researchers investigated supply chains of blood products, no research was conducted on the planning of convalescent plasma in the supply chain framework with specific features of COVID-19. This gap is covered in the current work by simultaneous regular and convalescent plasma flow in a supply chain network. Besides, due to the growing importance of environmental problems, the resulting carbon emission from transportation activities is viewed to provide a green network. In other words, this study aims to plan the integrated green supply chain network of regular and convalescent plasma in the pandemic outbreak of COVID-19 for the first time. The presented mixed-integer multi-objective optimization model determines optimal network decisions while minimizing the total cost and total carbon emission. The Epsilon constraint method is used to handle the considered objectives. The model is applied to a real case study from the capital of Iran. Sensitivity analyses are carried out, and managerial insights are drawn. Based on the obtained results, product demand impacts the objective functions significantly. Moreover, the systems' total carbon emission is highly dependent on the flow of regular plasma. The results also reveal that changing transportation emission unit causes significant variation in the total emission while the total cost remains fixed.

Energy-Aware Hierarchical Resource Management and Backhaul Traffic Optimization in Heterogeneous Cellular Networks

The dense deployment of small-cell networks is a key feature of the next-generation mobile networks employed to provide the necessary capacity increase. The small cells are installed in the areas covered by macro base stations (eNBs) to supply the required local capacity based on the known concept of the hierarchical HetNets. Moreover, small-cell networks use high-capacity backhaul links on millimeter-wave bands to develop multihop topologies to mitigate the costs of data transmission. Nonetheless, green networking gains great importance for the uncontrolled installation of too many small cells may escalate operational costs and emit more carbon dioxide. This article proposes a dynamic optimization model to minimize the overall energy consumption of fifth-generation (5G) heterogeneous networks and provide the essential coverage and capacity. Optimizing carrier allocation and power utilization, the proposed model determines when to turn <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on</small> or <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">off</small> small cells to meet the quality of service constraints of users with the highest level of energy efficiency. We also proposed a multihop backhauling strategy to effectively use the existing infrastructure of small-cell networks for simultaneous dual-hop transmissions. The numerical results indicated considerable rates of power saving in different traffic models while guaranteeing the throughput requirements for uniform and hotspot user equipment distribution patterns. Also, according to the simulation results, energy efficiency and system data rates can significantly be improved.

Manufacturer go green: A typology of offerings and capability requirements

Environmental sustainability is becoming an increasingly important motivator for the development of new offerings on business-to-business markets. Taking environmental concerns into account in the creation of new offerings can increase the complexity of the offering development process. Green offering development is therefore associated with new or emphasized capability requirements. This paper aims to explore these capability requirements through a multiple case study of manufacturing firms. It introduces a typology of three distinct kinds of green offering development, and suggests capabilities that are especially important for each type of green offering. The three types of offering are: internally oriented green production, externally oriented green application, and finally, reshaped green networks, which entails modifications in the boundaries between production and use.

A social-ecological perspective for emerging cities: The case of Corniche promenade, “urban majlis” of Doha

In the past decade, the capital city of Doha of the State of Qatar has experienced rapid urban expansion and other changes due to globalization, which has caused (i) the loss of a compact urban pattern, (ii) landscape fragmentation, and (iii) deficiency of green spaces. Therefore, as envisioned by Qatar National Vision 2030 (QNV-2030), the State of Qatar plans to invest substantial funds into the urban regeneration of the built environment, along with the development of large areas of public parks as a means of promoting more sustainable urban development and enhancing city residents’ well-being. Accessibility contributes to the usability of public facilities on the part of the neighborhood community, thus enhancing city dwellers’ well-being. Nonetheless, the authors argue, the urban network along Doha’s Corniche promenade, the dominant open public space and the spine of the city, lacks connectivity at various scales of space. Therefore, this research study aimed to assess the existing conditions of Doha’s Corniche and recommend strategies for implementing its integration into the newly emerging city’s urban fabric. The findings, revealed through a network-analysis investigation based on graph theory, allowed us to generate a framework for shaping open public spaces, promoting higher living standards through a green network system planned at the city scale. The proposed framework addresses social-ecological challenges of distinctive open public spaces and helps define an approach for (i) tailoring the accessibility of open public spaces to their surroundings, and (ii) enhancing city dwellers’ well-being.

The Green Network Panoramic Vision

Most cities worldwide suffer from the unequal distribution of urban areas and country areas around them and the growth of dangerous environmental issues. One of the primary causes of the imbalance is the continued expansion of building blocks and urban development against the open spaces and green areas either in or out of cities. Furthermore, the natural landscape, in general, has a significant impact on protecting the climate from rising temperatures and pollutants. So the aim of this research is to identify a panoramic vision of a green network and get to ‎use sustainable land in a strong and socially solid society. ‎ As a result, the research problem reads: there is dispersion and disintegration in urban open space planning and its development. To solve the research problem, a hypothesis is proposed stating that “the absence of a panoramic vision of green networks and disconnection with the surrounding region is one of the most important causes of dispersion in those spaces”. Erbil city is one of the Iraqi cities in the northern part, was chosen as a case study to examine the green network components or elements. The results showed that Erbil has many aspects of the green network. This study offers some suggestions to fulfill the missing parts of it.

An AHP-TOPSIS Integrated Model for QoS-Aware Energy Efficiency in Green Cognitive Radio Networks

The selection of the best spectrum band available to meet the quality of service requirements of secondary users without interfering with the transmission of the primary users is considered as a challenge in cognitive radio networks. On the other side, green network is a recent concept that refers to the processes used to optimize a network in order to make it more energy efficient. In this paper, we propose a new algorithm ensuring the selection of the best available spectrum satisfying the demands of the secondary users based on TOPSIS and AHP in OFDM-based cognitive radio networks. We will assess the need for the secondary users in terms of quality of service and energy efficiency, by analyzing the characteristics of the available channels and taking into account the interference generated with the presence of the primary user. It efficiently manages energy because it allows a significant reduction of the transmission power used by the secondary user and therefore presents an effective solution in green networking.

Ecological networks and corridors development in urban areas: An example of Tabriz, Iran

Landscape fragmentation and the elimination of urban green spaces are the results of human activities which put significant pressure on urban sustainability. The planning and developing of urban ecological networks and corridors as an effective approach is a response to rapid urbanization and fragmentation of natural areas. The Tabriz metropolitan as the fourth-largest city in Iran was selected as a case study that has grown rapidly over the past few decades. This study presents a practical approach and framework for assessing and enhancing ecological connectivity of landscape. The framework was developed based on the landscape metrics, graph theory, least-cost modeling, and geographic information system tools during three different periods (1984-2000-2020). The results using the values of landscape metrics such as CA, Edge Distance, Mean Patch Size, Mean Shape Index, large patch index, NP, Landscape shape index, and COHESION indicate that the urban landscape of Tabriz has been more fragmented over the past 3 decades and has lost its connectivity. To reduce the effects of fragmentation and enhance landscape connectivity in study area, we proposed a network of ecological corridors that passes through the core ecological patches. Our results also indicate that the core patches and the least-cost created corridors are mainly located in the suburbs of Tabriz and the central part of the city cannot be suitable for ecological development. Therefore, using the above-mentioned methods could be an effective approach to develop ecological networks and improve landscape connectivity that can encourage urban planners and managers to protect and develop green networks.

Developing an Integrated and Contextualized Planning and Design Framework for Livable Patterns of Urbanization in Chennai

This article analyses the urban conditions of Chennai, India, and takes a critical look at its planning framework by considering four main aspects: the ecological structures, urban morphology, mobility, and livability. To do so, the article examines policy documents, urban form, public perceptions, and daily mobility patterns. Specific attention is focused on three layers of the urban fabric: water and ecology, transport infrastructure, and housing. First, the city’s river restoration is critically assessed, with a focus on integrating the social dimension into the process. Second, the metro network is analyzed, specifically understanding its usage with respect to different user groups. Third, the densification pattern in different parts of the city is analyzed. Considering the layers of water, transport infrastructure, and housing together, the article sets out an alternative integrated approach to strategic design and planning in the city towards the goal of creating a more livable public realm. The proposed integrated framework, termed “supergrids” is a city-scale strategy that enables a large reconfiguration of the existing networks in the city, integration of ecological systems into the public space network, and a restructuring of movement patterns by upscaling the vehicular network, and aligning pedestrian connections with green networks, public transit, and important functions.

Defending Trace-Back Attack in 3D Wireless Internet of Things

With the development of 5G, it is unsurprising that most of the smart devices in the Internet of Things (IoT) will be wirelessly connected with each other in the near future. This kind of lightweight, scalable and green network architecture will be well-received. In a wide variety of IoT application scenarios, sensor nodes deployed in a local space, such as a multistory building, automatically form a distributed 3D wireless IoT and it can be employed to collect and analyze environmental information. Source-location privacy protection is of great importance in these networks and however, most existing schemes focus on only planar distributed networks which are not suitable for the 3D networks. In this paper, we consider a novel trace-back attack for 3D wireless IoT and then design a source-location privacy protection scheme, named DMR-3D, to defend this kind of novel attacks. In DMR-3D, the source node first selects a set of virtual locations to indirectly choose a set of agent nodes based on the cold start sphere structure and the ellipsoid communication pipeline. Then, a sophisticated mechanism is designed based on both the connected graph and Multiple Delaunay Triangulation (MDT) structure of the network to deliver packets from the source node to the destination node via these agent nodes in a relay manner. Analysis and simulation results illustrate that the proposed scheme can effectively protect source-location privacy with a moderate increment of path stretch, time delay and data transmission amount.

Land Utilization, Landscape Pattern, and Ecological Efficiency: An Empirical Analysis of Discrimination and Overlap from Suining, China

The rapid urbanization in recent decades has highlighted the impact of rural land utilization, which further affects the spatial structure and efficiency of rural ecosystems. Optimizing the structure of urban green infrastructure is an effective way to alleviate the fragmentation of rural landscapes, coordinate the relationship between rural development and ecosystem services, and ensure sustainable rural development. The purpose of this paper is to provide a clear direction for the optimization of construction for the sustainable development of rural green infrastructure (RGI). This study provides a new method for RGI identification and analysis by taking Suining County, a typical rural area on the North China Plain, as an example. Morphological spatial pattern analysis (MSPA) was used to distinguish different space scenery elements in RGI and combine them with land utilization elements, so as to obtain two types of overlapping degree data in each village and town. We further combined the overlapping degree data with ecological efficiency indicators to evaluate the spatial structure construction priorities of different land use components in the RGI system. The results show that the MSPA and ecological efficiency analysis method proposed in this paper are conducive to qualitative and quantitative analysis of the relationship between land use type, spatial structure, and ecological efficiency in the RGI system and are suitable for the construction of a green infrastructure network. This method can be used to better understand the spatial distribution and priority of green infrastructure networks to achieve sustainable rural development on the North China Plain.

Optimal Power Allocation for Achieving Secure Green Cognitive Radio Networks

In cognitive radio networks, wireless nodes adapt to the surrounding radio environment and utilize the spectrum of licensed users. The cognitive radio environment is dynamic, and wireless channels are accessible by both legitimate and illegitimate users. Therefore, maintaining the security of cognitive radio networks is a challenging task, which must be addressed thoroughly. Further, with the recent exponential surge in wireless nodes and associated high data rate requirements, energy consumption is also growing at an unprecedented rate. Hence, energy efficiency becomes an important metric that must be considered in the design of future wireless networks. Accordingly, by considering the great ecological and economic benefits of green wireless networks, this work focus on energy-efficient resource allocation in secure cognitive radio networks. Since physical-layer security is an emerging technique that improves the security of communication devices, in this paper, an ergodic secure energy efficiency problem for a cognitive radio network is formulated with a primary user, a secondary user, and an eavesdropper. As the formulated problem is non-convex, a concave lower bound is applied to transform the original non-convex problem into a convex one. Further, by adopting the fractional programming and dual decomposition techniques, optimal power allocation strategies are obtained with the aim of maximizing the ergodic secure energy efficiency of the secondary user with constraints on the average interference power and average transmit power. Numerical examples are used to demonstrate the effectiveness of the proposed algorithm.

IEEE Transactions on Green Communications and Networking

IEEE Transactions on Green Communications and Networking

A novel approach to QoS‐aware resource allocation in NOMA cellular HetNets using multi‐layer optimization

AbstractThe dense deployment of small cells is a key feature of the next‐generation cellular networks aimed at providing the necessary capacity increase. But in such networks the problem of green networking will be of great importance, because the uncontrolled installation of too many cells may increase operational costs and emit more carbon dioxide. Nowadays, unmanned aerial vehicles (UAVs) offer an efficient approach to improve the quality, data rate, and meet the demanding performance requirements of applications in ultra‐dense cellular networks. This article proposes a dynamic optimization model which minimizes the overall energy consumption of UAV cellular networks in addition to guarantying the essential coverage and capacity. The proposed model optimizes user association and power utility to meet users' QoS requirements with the highest level of energy efficiency (EE). For this purpose, the surplus energy pattern of UAVs is first mathematically formulated and then applied to calculate its ruin probability. In fact, the ruin probability denotes the vulnerability of a UAV when it runs out of energy. The ruin probability is used in the next step to efficiently connect every user to the UAVs. Also, power allocation is implemented for the applications to achieve the optimal value of the accessible network's data rate through the water‐filling method. This model also performs coded routing in the multi‐hop backhauls to efficiently use the existing infrastructure of the cooperative networks for coding dual‐hop transmissions. The simulation results exhibit considerable network throughput and EE increase by 42% and 30%, respectively, for the proposed ruin‐based energy‐efficient approach in comparison with the conventional signal‐to‐interference/noise ratio‐based schemes.

Neighboring Green Network and Landscape Metrics Explain Biodiversity within Small Urban Green Areas—A Case Study on Birds

Cities’ green areas are fragmented patches and are often confined to smaller sizes than the higher built-up proportions. Such small-sized green areas can be essential components of green infrastructure to compensate for biodiversity loss. As a proxy to biodiversity, we studied birds in nine small green area locations of Freiburg and eight area locations in Regensburg in Germany. We investigated the neighboring green networks (distance to the nearest water body and another green area) and landscape metrics (patch abundance and habitat heterogeneity at a 1 km radius) that might benefit and explain bird richness and composition in small green areas. We found that the variations in the observed species richness and composition at the surveyed locations were better explained solely by green networks in Freiburg and by green networks and landscape metrics in Regensburg. In general, it indicates that a small green area could be biodiverse if its spatial distribution considers a nearby water body and other green areas, allowing a higher abundance of similar patches and habitat heterogeneity in the neighborhood.

To Preserve Green Buffer under Polarization and Diffusion Effects of a Fast-Developing Megalopolis

The polarization and diffusion effects of landscape patterns are important features of megalopolis development. Under the urbanized effects, green space is a key spatial unit in delivering vital ecosystem services for sustainable urban planning. However, currently, fast urban developing is swamping the green space. In this study, by tracing landscape pattern changes of a fast-developing megalopolis, the Chengdu-Chongqing Megalopolis in the southeast of China, and using land-use data from 1980 to 2020, we aimed to determine the polarization and diffusion effects of the megalopolis and their impacts on the green space within and between the cities. We found that: (1) during the past four decades, spatial expansion of the megalopolis mainly occupied grassland and farmland, triggering an increase in landscape fragmentation; (2) based on socio-economic indicators, the spatial-attraction network analysis showed a significant polarization effect; however, based on the natural landscape, this analysis demonstrated a more scattered pattern; (3) importantly, the megalopolis developed at quite a similar pace, which caused the green rural area between the central cities demonstrating an encroached trend by the urbanization. To promote sustainability of the fast-developing megalopolis, we suggest that the boundary of the green space should be broadened to form a green network in which natural green space and urban green space are interconnected, improving the connectivity of habitats within the megalopolis for urban biodiversity. Our study implied that maintaining the green buffer shall be considered in advance for sustainable megaregional planning and establishing resilience of the fast-developing megalopolis.

Implementation of Green Infrastructure in Existing Urban Structures: Tracking Changes in Ferencváros, Budapest

Understanding the resilience of urban forms as a latent force that drives a place’s physical characterization and social cohesion is essential for defining successful adaptive processes of pre-existing urban fabrics. Budapest’s ninth district (Ferencváros) is an outstanding example of transforming a complex historical urban context, which underwent renovation strategies guided by maintaining and enhancing essential morphological elements. Courtyards have great relevance in conditioning the well-being in areas of high occupational density, especially in terms of accessibility to urban green infrastructure. In the case of Ferencváros, they were reframed to add new layers of use and to improve territorial integration by unifying smaller private courtyard unities into more extensive communal areas, creating a comprehensive urban green network, preserving urban heritage, and increasing green coverage. This study assesses how this recent re-urbanization phenomenon is related to political changes in a post-socialist city. The conjuncture found in Ferencváros is unique, yet it can be applied in other similar contexts. The methodology applied to this study is supervised classification for the quantitative analysis of remote-sensing image data with GIS software assistance—a procedure rarely applied in medium-scale urban analysis. However, it was verified to be precise and effective in tracking morphological changes. The preliminary results indicate a significant intensification in greenery in the urban pattern, especially in the core areas of the blocks: the courtyards. After the intervention, green areas became more predominant, cohesive, and articulated.

The Construction of Urban Park Green Infrastructure Network Based on Genetic Algorithm

In order to build a scientific and reasonable urban park green infrastructure network. Genetic Tabu hybrid algorithm is introduced into the field of urban park green infrastructure network construction, using ENVI5.5, ArcGIS10.2, Conefor2.6, and other software to construct the comprehensive green infrastructure network model and corresponding algorithm of a city park and improve and compare the genetic algorithm and Tabu search algorithm. Firstly, the ecological sensitivity of urban parks was evaluated, and 58 ecological source patches with high ecological value were selected. With the help of GIS platform, 71 potential corridors are simulated and generated by using the minimum cost path model. Then, select the index that can evaluate the importance of source patches in the ecological network to determine the importance ranking of source patches. Finally, according to the principles of clustering and network connectivity, select the ecological source with high patch importance, analyze the potential ecological corridor and current corridor, and combine and screen the factors of green infrastructure network. The results show that a city park green infrastructure network composed of 38 ecological source patches and 19 corridors is finally formed. Genetic algorithm has a potential application prospect in the construction of urban park green infrastructure network. By introducing genetic Tabu hybrid algorithm into the field of urban park green infrastructure network construction, it will change the mode of traditional urban park green infrastructure network construction.

Multiple scenario simulation and optimization of an urban green infrastructure network based on complex network theory: a case study in Harbin City, China

BackgroundUrban green infrastructure (GI) networks play a significant role in ensuring regional ecological security; however, they are highly vulnerable to the influence of urban development, and the optimization of GI networks with better connectivity and resilience under different development scenarios has become a practical problem that urgently needs to be solved. Taking Harbin, a megacity in Northeast China, as the case study, we set five simulation scenarios by adjusting the economic growth rate and extracted the GI network in multiple scenarios by integrating the minimal cumulative resistance model and the gravity model. The low-degree-first (LDF) strategy of complex network theory was introduced to optimize the GI network, and the optimization effect was verified by robustness analysis.ResultsThe results showed that in the 5% economic growth scenario, the GI network structure was more complex, and the connectivity of the network was better, while in the other scenarios, the network structure gradually degraded with economic growth. After optimization by the LDF strategy, the average degree of the GI network in multiple scenarios increased from 2.368, 2.651, 2.189, 1.972, and 1.847 to 2.783, 3.125, 2.643, 2.414, and 2.322, respectively, and the GI network structure connectivity and resilience were significantly enhanced in all scenarios.ConclusionsEconomic growth did not necessarily lead to degradation of the GI network; there was still room for economic development in the study area, but it was limited under existing GI conditions, and the LDF strategy was an effective method to optimize the GI network. The research results provide a new perspective for the study of GI network protection with urban economic growth and serve as a methodological reference for urban GI network optimization.

RobustSTL and Machine-Learning Hybrid to Improve Time Series Prediction of Base Station Traffic

Green networking is currently becoming an urgent compulsion applied for cellular network architecture. One of the treatments that can be undertaken to fulfill such an objective is a traffic-aware scheme of a base station. This scheme can control the power consumption of the cellular network based on the number of demands. Then, it requires an understanding of estimated traffic in future demands. Various studies have undertaken experiments to obtain a network traffic prediction with good accuracy. However, dynamic patterns, burstiness, and various noises hamper the prediction model from learning the data traffic comprehensively. Furthermore, this paper proposes a prediction model using deep learning of one-dimensional deep convolutional neural network (1DCNN) and gated recurrent unit (GRU). Initially, this study decomposes the network traffic data by RobustSTL, instead of standard STL, to obtain the trend, seasonal, and residual components. Then, these components are fed into the 1DCNN-GRU as input data. Through the decomposition method using RobustSTL, the hybrid model of 1DCNN-GRU can completely capture the pattern and relationship of the traffic data. Based on the experimental results, the proposed model overall outperforms the counterpart models in MAPE, RMSE, and MAE metrics. The predicted data of the proposed model can follow the patterns of actual network traffic data.