City Network Research Articles

Geographies of COVID‐19

Geographies of COVID‐19

A task scheduling algorithm with deadline constraints for distributed clouds in smart cities.

Computing technologies and 5G are helpful for the development of smart cities. Cloud computing has become an essential smart city technology. With artificial intelligence technologies, it can be used to integrate data from various devices, such as sensors and cameras, over the network in a smart city for management of the infrastructure and processing of Internet of Things (IoT) data. Cloud computing platforms provide services to users. Task scheduling in the cloud environment is an important technology to shorten computing time and reduce user cost, and thus has many important applications. Recently, a hierarchical distributed cloud service network model for the smart city has been proposed where distributed (micro) clouds, and core clouds are considered to achieve a better network architecture. Task scheduling in the model has attracted many researchers. In this article, we study a task scheduling problem with deadline constraints in the distributed cloud model and aim to reduce the communication network's data load and provide low-latency services from the cloud server in the local area, hence promoting the efficiency of cloud computing services for local users. To solve the task scheduling problem efficiently, we present an efficient local search algorithm to solve the problem. In the algorithm, a greedy search strategy is proposed to improve the current solutions iteratively. Moreover, randomized methods are used in selecting tasks and virtual machines for reassigning tasks. We carried out extensive computational experiments to evaluate the performance of our algorithm and compared experimental results with Swarm-based approaches, such as GA and PSO. The comparative results show that the proposed local search algorithm performs better than the comparative algorithms on the task scheduling problem.

Secure authentication protocol for home area network in smart grid-based smart cities

The Internet of Things (IoT) allows better solutions for managing challenges such as reliability and power quality in a smart grid environment. It also assists in adopting smart grid measures in smart city development. A smart meter in the smart grid environment must securely access services from a service provider via public channels. An adversary can pose several security vulnerabilities as the communication occurs through a public channel. Various researchers recently conducted several research types to determine the most challenging problems with the smart grid. The security features like integrity, authentication, and confidentiality are indispensable requirements of the smart grid environment. On the other hand, different objects like smart meters in the smart grid environment are resource-constrained, posing in designing lightweight security protocols. Hence, we propose a lightweight mutual authentication scheme to offer surveillance to smart meters in smart grid infrastructure. We analyze the suggested protocol against well-known security threats. Finally, we evaluate the performance of the protocol to illustrate its efficiency.

Quantitative and qualitative approaches in recognizing viable centres to support transit system implementation in developing countries. Case study: Makassar, Indonesia

Implementing transit systems has been seen as one approach to better support land use development and the transport system to overcome the spatial mismatch and subsequently, the traffic congestion problems in many cities. One of the key components of transit system implementation is recognizing the viable center. However, the application of this system in practice is still limited due inadequate spatial form and mobility information, especially in cities in the developing world. This study aims to propose a spatial clustering approach to identify urban center(s) based on openly available data sources combined with expert interviews. The proposed method is intended to support local transport planning processes. Following the case study approach, the method was developed and tested in Makassar, Indonesia. Urban land use and the built environment data were used alongside data about the streets network and the distribution of facilities derived from the local authority’s spatial database and OpenStreetMap (OSM). The results show that urban centers are developed outside the central business district mainly in linear form. Additional findings based on the morphological perspective show that Makassar has three types of urban fabrics, i.e., walking, car city, and transit city fabrics. Based on the urban center distribution and urban fabrics’ typology, recommendations for the adjustment of transport nodes and the city network can be made, which could become a basis for transport planning in the future.

Ensemble Learning Traffic Model for Sofia: A Case Study

Traffic models have gained much popularity in recent years, in the context of smart cities and urban planning, as well as environmental and health research. With the development of Machine Learning (ML) and Artificial Intelligence (AI) some limitations imposed by the traditional analytical, numerical and statistical methods have been overcome. The present paper shows a case study of traffic modeling with scarce reliable data. The approach we propose resorts on the advantages of ensemble learning using a large number of related features such as road and street categories, population density, functional analysis, space syntax, previous traffic measurements and models, etc. We use advanced regression models such as Random Forest, XGBoost, CatBoost etc., ranked according to the chosen evaluation metrics and stacked in a weighted ensemble for optimal fitting. After a series of consecutive data imputations we estimate the annual average daily traffic distribution in the street and road network of Sofia city and the metropolitan municipality for 2018 and 2022, and the NO2 levels for 2021 with accuracy resp. 78%, 74% and 92%, using AutoGluon and Scikit-Learn.

Effect of innovative-city pilot policy on industry–university–research collaborative innovation

The study applies the social cooperation network and multi-period DID to identify the conduction path and effect of innovative-city pilot policy on IUR collaborative innovation in 26 YRD cities during 2005–2020. The IUR collaboration innovation has made significant progress in YRD. Simultaneously, the IUR cooperative intensity and control capability of cooperative network of YRD cities have increased gradually. However, the IUR R&D efficiency and IUR transformation efficiency both haven’t reached the optimal level in YRD, and the transformation efficiency is always less than R&D efficiency. The pilot policy has a positive effect on improving IUR innovation efficiency. The policy effects for provincial capital cities are greater than those for non-provincial capital cities. Provincially, the pilot policy on IUR collaborative innovation efficiency reaches highest in Zhejiang and lowest in Jiangsu. The IUR cooperative intensity and control capability of cooperative network have partial intermediary effect on pilot policy.

Study of an nZEB Office Building with Storage in Electric Vehicle Batteries and Dispatch of a Natural Gas-Fuelled Generator

The rapid electrification of vehicles has led to a great increase in numbers of charging stations and a growing appetite for charging power, with stochastic charging behaviours heavily loading the electricity grid. The upcoming difficulties and increasing costs associated with electricity production will require a rapid development of smart grids and city networks. Smart micro-grids established in nearly zero-energy buildings (nZEB) are a promising strategy to support grid stability and resilience at a reduced cost. A significant amount of electricity storage capacity is necessary for optimal dispatch of the self-produced photovoltaic electricity. For office buildings, this capacity can be provided by the aggregate battery storage of the employees’ electric vehicles, which connect to the smart grid during working hours for charging and, if allowed, for discharging. An additional, fully controllable electricity source that is necessary to support an optimal micro-grid is the internal combustion engine-powered generator that is present in every commercial and office building as an emergency power supply. In the current study, a preliminary investigation of a smart micro-grid in a near zero-energy office building with a 218 kWp rooftop photovoltaic installation is carried out. The required electricity storage capacity is supplied by the employees’ electric vehicles, which stay connected to the building’s in-house chargers during working hours. The optimal rating of the natural gas-fuelled GenSet is determined based on a system’s operation and control study. Optimal dispatch of the different power sources to support the building’s autonomy and seasonal timing of electricity export to the grid is studied versus the electricity demand profiles of the electricity grid.

DRL-Based Computation Offloading With Queue Stability for Vehicular-Cloud-Assisted Mobile Edge Computing Systems

Computation offloading is considered as a promising method to improve computation performance of Intelligent Vehicles (IVs), where IVs can offload resource-hungry applications to Mobile Edge Computing (MEC) servers. However, due to the dynamic environment of Intelligent Transportation Systems, it's challenging to develop an effective offloading scheme that ensures stable operation of the system. Furthermore, IVs only offload tasks to MEC servers or parked vehicles, how to take full advantage of resources in a random traffic flow is a main challenge. In this paper, we propose a vehicular-cloud-assisted MEC network in urban cities to fully explore the idle resources and ensure the stability of task queue. Specifically, we develop a novel virtual platform based on deep neural network that predicts vehicles trajectory and creates vehicular cloud to integrate computation resources. We then design a vehicular-cloud-assisted offloading scheme that aims to maximize task throughput in continuous time slots subject to multi-constraint. To address the coupling among multiple variables and different time slots, we put forward a lightweight framework to apply the Lyapunov optimization in combination with deep reinforcement learning. In particular, we apply Lyapunov drift-plus-penalty approach to decompose the initial problem into per-slot subproblems and control the long-term task queue stability. To further reduce the computation complexity, we decouple the subproblem into three processes, and the deep Q-network is put forward to solve it. Extensive simulations demonstrate that under different task arrivals, our proposed scheme can achieve the task queue stability within 10 time slots with a low transmission power.

ANALYSIS OF TRANSPORT PROBLEMS OF LARGE AND MAJOR CITIES

In this article, the authors consider the transport problems of the largest and largest cities on the example of Krasnodar. The growth of housing construction in recent years has led to an increase in motorization, which increases the load of the city’s road network. Based on the analysis, we can conclude about the main directions of the development of the transport network of cities and the most anticipated problems.
 Purpose: is to analyze the rate of population growth in cities, the growth of motorization and draw conclusions about the main transport problems of the city associated with these factors.
 Method or methodology of the work: statistical analysis, synthesis were used in the article.
 Results: the main directions of activity for solving transport problems of large and largest cities are determined on the example of Krasnodar, the growth rates of population, population density, growth of motorization are analyzed and conclusions are drawn about the influence of these factors on the functioning of the city’s transport system.
 Scope of application of the results: research activity on the development of new approaches in the field of organization of transportation and transport services.

Realization of Index Modulation with Intelligent Spatiotemporal Metasurfaces

Advanced wireless communication with high spectrum efficiency and energy efficiency has always fascinated humanity, especially with the explosive increase of global mobile data services. Index modulation (IM) has recently been found to be a promising technique due to the transmission of additional data bits via the indices of the available transmit entities. However, the practical implementation of IM remains a great challenge associated with complicated radio components. Herein, IM with intelligent spatiotemporal metasurfaces is experimentally demonstrated. The spatiotemporal metasurfaces provide a natural and versatile platform to achieve IM in a green and lightweight manner. The whole system is driven by a built‐in inverse‐design agent that automates spatiotemporal metasurfaces to cater to diverse application demands. In doing so, how to mitigate the inherent nonuniqueness issue and how to setup the input target from practical scenes are concretely discussed. In the microwave experiment, the spatiotemporal metasurfaces are fabricated and demonstrate the feasibility by harvesting two harmonic waves as communication channels. An intelligent electromagnetic platform that can manipulate electromagnetic waves in multidimensions is provided, meriting other numerous intelligent meta‐devices that avoid overburdening data analysis networks in smart cities of the future.

Analysis on the Spatial Structure and Interaction of Aviation Network and Tourism Efficiency Network in Major Cities in China

Tourism efficiency is crucial for measuring sustainable tourism development. Examining the relationship between aviation and tourism efficiency networks is key to promoting their synergistic development in China's urban areas. This study employs various methods, such as complex network analysis method, entropy-weighted TOPSIS, tourism efficiency gravity model, and quadratic assignment procedure, to analyze the networks' spatial structure evolution characteristics and interaction effects. Results show that (1) China's major cities' aviation network has improved its organizational efficiency and formed a "double rhombus-single axis" spatial evolution pattern of the axis-spoke network. The number of intermediary networks and hub cities in the central and western regions has increased. (2) The tourism efficiency network adopts a "honeycomb" structure pattern with the simultaneous layout of "point-to-point" and "star" networks. The network's tourism efficiency follows "Pareto's Law," and tourism cities above the second level form a club group development. The tourism efficiency development potential area is shifting to the southwest. (3) The aviation and tourism efficiency networks exhibit a clear trend of synergistic evolution with a "path locking" phenomenon between them. Differences in tourism resource endowment, labor advantage, and capital advantage positively impact the aviation network's structure. Conversely, differences in revenue capacity and market scale negatively impact the structure. The aviation scale advantage, openness, intimacy, and influence exhibit decreasing positive effects on the tourism efficiency network's structure.

Boosting Kembang Kuning Tourism Village's Visibility

This study examines the role of stakeholders in developing tourism in the Old City of Ampenan, Mataram City, Indonesia. Despite being designated as one of the Indonesian Heritage Cities Network's 43 cities, Ampenan's tourism potential has not been fully realized and is even on the decline due to a lack of joint efforts by tourism stakeholders. The Pentahelix players are composed of the government, academia, industry, community, and tourists, and their roles in tourism development are investigated. Strategies for sustainable tourism development are proposed based on data collected through non-participant observation, unstructured interviews, and documentation. The results highlight the potential of Ampenan Old City as a tourist destination and the contributions of various stakeholders to its development. The study concludes that the Ampenan Old City is a must-visit destination, featuring impressive cultural landmarks, natural beauty, and accessibility, and recommends further collaboration between stakeholders to improve its sustainable development.

Unlocking the Potential of Ampenan Old City

This study examines the role of Pentahelix players in developing tourism in the Old City of Ampenan, Mataram City, Indonesia. Despite being designated as one of the Indonesian Heritage Cities Network's 43 cities, Ampenan's tourism potential has not been fully realized, and is even on the decline due to a lack of joint efforts by tourism stakeholders. The Pentahelix players are composed of the government, academia, industry, community, and tourists, and their roles in tourism development are investigated. The study proposes strategies for sustainable tourism development, and data is collected through non-participant observation, unstructured interviews, and documentation. The results highlight the potential of Ampenan Old City as a tourist destination and the contributions of various stakeholders to its development. The study concludes that the Ampenan Old City is a must-visit destination, featuring impressive cultural landmarks, natural beauty, and accessibility, and recommends further collaboration between stakeholders to improve its sustainable development

Demonstration of duality of fractal gravity models by scaling symmetry

A pair of fractal gravity models can be derived from spatial interaction models based on the entropy maximizing principle and the allometric scaling law. The models can be expressed in dual form in mathematics and are important for analyzing and predicting spatial flows in networks of cities. However, the dual relationship of urban gravity parameters has remained an empirical relationship for a long time and lacks theoretical proof. This paper is devoted to proving the duality of fractal gravity models by means of ideas from scaling invariance. The results show that a fractal gravity model can be derived from its dual form. The observational data of interurban spatial flows of the Beijing-Tianjin-Hebei region of China are employed to make a case study, lending further support for the theoretical derivation. It appears that the duality of gravity models rests with the scaling symmetry of fractal structure. This work may be helpful for understanding the theoretical essence and application direction of spatial interaction modeling.

Regional planning for ecological protection of rivers in highly urbanized areas

The ecological risks associated with rapid urbanization have seriously undermined the river’s ecological security. Especially for developing countries, the weak ecological foundation and enormous population pressure have increased the difficulty of river ecological protection. It is urgent to propose a bottom-line planning and management approach for river ecological protection in highly urbanized areas of developing countries. We quantified the minimum cumulative resistance of the river protection and construction land expansion processes. Then, based on the difference between these two minimum cumulative resistances, we assessed the river ecological risk in the Beijing plain area and presented a complete method to regional-level planning and management for river ecological protection. The results show that: 1) The spatial distribution of river ecological risks follows a three-tier ring structure, decreasing from the city center to the suburbs and then to the outer suburbs. The number of river segments with ecological risk levels 1, 2, and 3 are 44, 42, and 23, respectively, accounting for 39.2% of the total length of all river sections, which indicates that a larger number of rivers are facing high ecological risk. 2) The study area was divided into three zones according to the suitability of river ecological protection, with 2476.89, 765.51, and 3832.09 km2, respectively. Zone I and Zone II can be developed as protection nodes and riparian protection zones to develop the river ecological network in the central city. 3) We extracted 133 large ecological patches and 219 potential ecological corridors, which should be connected with the river network to enhance the connectivity of the local ecological landscape. The complete method proposed in this study is more focused and implementable to assist administrators in protecting and restoring the ecological security of urban rivers.

Conceptually Related Smart Cities Services from the Perspectives of Governance and Sociotechnical Systems in Europe

The absence of a comprehensive smart city governance model has prompted research into the characteristics of the relationships among cities, services, and stakeholders. This study aims to identify, from the perspectives of governance and sociotechnical systems, the characteristics of conceptually related smart city service implementations based on stakeholder partnerships. Social network analysis was utilized based on existing research datasets. Stakeholders, services, and representative European sustainable smart cities were included in the dataset in relation to this study’s operational definition. The first finding is that the initial conceptually related smart city services are reflected in the accumulated and current characteristics of the smart city services. These depend on stakeholder partnerships, while the network foundation differs between the initial and latter services. The second finding clarifies how different development services depend on stakeholder partnerships and how multiple stakeholders, including local entities, are vital to deal with current challenges in massive urbanizations. The third finding demonstrates the emerging roles of private sectors and some intermediate services in the global network of cities. This study contributes to the management of smart cities by identifying how service development occurs based on stakeholder partnerships and contributes to their theoretical basis by empirically demonstrating the importance of multi-stakeholder partnerships to address current urbanization challenges.

An Intelligent Machine Learning based Intrusion Detection System (IDS) for Smart cities networks

INTRODUCTION: Internet of Things (IoT) along with Cloud based systems are opening a new domain of development. They have several applications from smart homes, Smart farming, Smart cities, smart grid etc. Due to IoT sensors operating in such close proximity to humans and critical infrastructure, there arises privacy and security issues. Securing an IoT network is very essential and is a hot research topic. Different types of Intrusion Detection Systems (IDS) have been developed to detect and prevent an unauthorized intrusion into the network.OBJECTIVES: The paper presents a Machine Learning based light, fast and reliable Intrusion Detection System (IDS).METHODS: Multiple Supervised machine learning algorithms are applied and their results are compared. Algorithms applied include Linear Discriminant analysis, Quadratic Discriminant Analysis, XG Boost, KNN and Decision Tree.RESULTS: Simulation results showed that KNN Algorithm gives us the highest accuracy, followed by XG Boost and Decision Tree which are not far behind.CONCLUSION: A fast, secure and intelligent IDS is developed using machine learning algorithms. The resulting IDS can be used in various types of networks especially in IoT based networks.

Kuznets and the cities: Urban level EKC evidence from Europe

This paper empirically explores the extent to which European cities are on track to sustainable development by examining the environmental performance of a large sample of cities observed during the last two decades. The paper builds on the Environmental Kuznets Curve framework and leverages satellite data to build a set of environmental indicators as varied and as granular as possible. Evidence suggests that European cities are, on average, on track to sustainable development, meaning that the contribution of their economic growth to environmental degradation is already negative or close to becoming so. The paper also examines Transnational City Networks as accelerators of environmental transition. The results suggest that cities participating in such networks anticipate the transition with respect to their peers.

Optimal design of water reuse networks in cities through decision support tool development and testing

Water scarcity and droughts are an increasing issue in many parts of the world. In the context of urban water systems, the transition to circularity may imply wastewater treatment and reuse. Planning and assessment of water reuse projects require decision-makers evaluating the cost and benefits of alternative scenarios. Manual or semi-automatic approaches are still common practice for planning both drinking and reclaimed water distribution networks. This work illustrates a decision support tool that, based on open data sources and graph theory coupled to greedy optimization algorithms, is able to automatically compute the optimal reclaimed water network for a given scenario. The tool provides not only the maximum amount of served reclaimed water per unit of invested cost, but also the length and diameters of the pipes required, the location and size of storage tanks, the population served, and the construction costs, i.e., everything under the same architecture. The usefulness of the tool is illustrated in two different but complementary cities in terms of size, density, and topography. The construction cost of the optimal water reclaimed network for a city of approximately 100,000 inhabitants is estimated to be in the range of €0.17–0.22/m3 (for a payback period of 30 years).

City Governments as Political Actors of Global Governance

Abstract The transnational rise of city networks is increasingly associated with the emergence of hybrid configurations beyond the public sector that contribute to technocratic decisionmaking processes and the depoliticization of global governance. This article takes issue with this argument. By analyzing the legitimation strategy used by the global city network United Cities and Local Governments (UCLG) vis-à-vis the UN system, the article contends that city networks can generate collective agency and frame political issues as a matter of public accountability. The cities gathered under UCLG, a “public membership” city network, are offering their political constitution to the multilateral system, thus complementing rather than replacing the political agency of state-centric processes. Yet the state-centric nature of the international system is also the main obstacle on the (winding) road of UCLG toward multilateral recognition.