Mobile Router Research Articles

From efficiency to equity: A multi-user paradigm in mobile route optimization

This study addresses the challenge of optimizing vehicle mobility in urban environments, which is significant for the advancement of smart city initiatives and spatial data analysis. We introduce a novel mobile recommendation system designed for multi-user scenarios, aiming to achieve a balance between effectiveness and fairness. The system prioritizes maximizing the profitability of vehicle service providers while ensuring an equitable distribution of recommended routes among users. Our approach features a redefined objective function that integrates a fairness criterion alongside path quality optimization. We further propose PSA-DLMA (Parallel Simulated Annealing with Deep Learning-Guided Move Adaptation), a stochastic path search method that leverages deep learning to guide move and strategy selection, alongside a dynamic termination mechanism and a parallel processing strategy. We validate our methodology using recent yellow taxi data from New York City and its surroundings, conducting comprehensive experiments to assess the performance of the system. The results demonstrate the superiority of PSA-DLMA over existing state-of-the-art solutions, offering significant contributions to improving urban vehicle mobility within the smart city framework.

Multi-objective-derived efficient energy saving in multipath routing for mobile ad hoc networks with the modified aquila–firefly heuristic strategy

Mobile ad hoc networks (MANETs) suffer from a major problem with the energy drainage of network nodes, as the mobile nodes rely on batteries and do not have a permanent power supply. Therefore, a new multipath routing technique, using a novel hybrid heuristic algorithm, is designed to solve the diverse metrics of a multi-objective function, including energy consumption, distance, routing overhead ratio, throughput, end-to-end delay and packet delivery ratio. This approach implements a new hybrid algorithm termed the modified aquila–firefly heuristic strategy (MA-FHS), which integrates the aquila optimizer and the firefly algorithm. This derived fitness function is applied to achieve optimal paths in multipath routing with minimization of the multi-objective function. The simulation demonstrates that the developed routing protocols outperformed traditional protocols under several network constraints.

Design, Analysis and Detection of Urban Mobility Patterns in Guayaquil through Supervised Learning Algorithms

This work explores the use of GPS trajectory data (Git Hub) and supervised learning algorithms to analyze mobility patterns in the city of Guayaquil-Ecuador. The analysis reveals that identifying mobility patterns is crucial to improve urban planning and optimize public transport in terms of its innovations from 2024. The methodology has included data collection from various open access sources, data preprocessing and the use of a Random Forest Classifier to detect mobility patterns. The results indicate a model accuracy of 50%, opening the possibilities for future specialized research to optimize the model and collect more data to improve its performance and propose new StartUPS for the city. The data compiled supports the implementation of the Single Card for Public Transport (TUT), which modernizes and unifies the payment system, facilitating the collection of essential data for analysis. The research concludes that the integration of data from applications such as Waze and Moovit is crucial for efficient and sustainable urban planning and that supervised learning algorithms are effective tools for urban mobility analysis and leaving open the possibility of exploring additional data and other algorithms to improve the accuracy of models and the generation of new mobility routes.

A Method for Air Route Network Planning of Urban Air Mobility

Urban air mobility is an effective solution to address the current issue of ground traffic congestion in future cities. However, as the user scale continues to expand, the current civil aviation flight scheduling and control methods are becoming inadequate to meet the high-volume flight guarantee demands of future urban air transportation. In order to effectively handle and resolve potential issues in this field in the future, this paper proposes a method for planning urban air mobility route networks. The planning process is divided into two stages: construction and optimization. Methods for constructing urban air mobility route networks based on flight routes and global optimization methods based on node movement are proposed in each stage. In the construction stage, a complete construction process is designed to generate routes based on existing flight routes, in line with the trend of urban air transportation development. In the optimization stage, inspired by the ant colony algorithm, node transfer rules and information transfer rules are incorporated to design a global optimization process and algorithm for route networks. Experimental results demonstrate the effectiveness and advancement of the proposed planning method.

Link reliable on-demand distance vector routing for mobile ad hoc networks

Link reliable on-demand distance vector routing for mobile ad hoc networks

Spatial patterns and trends of inter-city population mobility in China—Based on Baidu migration big data

Based on Baidu migration big data from the Spring Festival travel rush periods in 2022 and 2023, this study employs a combination of GIS-based spatial statistical analysis and social network analysis to analyze over 270,000 travel data records covering 297 prefecture-level cities. The research reveals that the population flow during the 2023 Spring Festival travel rush increased both in overall quantity and in the proportion of inter-provincial population flow compared to the same period in 2022. The distribution of population movement shows a distinct “southeast dense, northwest sparse” pattern, forming a diamond-shaped structure with the Bohai Sea Rim, Yangtze River Delta, Pearl River Delta, and Sichuan-Chongqing regions as the vertices. Among the most significant inter-city mobility routes are Guangzhou ↔ Foshan, Shenzhen ↔ Dongguan, Shanghai ↔ Suzhou, Xi'an ↔ Xianyang, and Beijing ↔ Langfang, which constitute the five routes with the highest flow volumes, each with its own distinctive patterns and characteristics. Significant agglomeration effects in population movement are observed, with the majority of the 40 cities experiencing higher net inflows situated in the Yangtze River Delta and Pearl River Delta regions. On the other hand, many cities in the western and northeastern regions, including some third-tier and even second-tier cities, are facing net population outflows. As the working population and major economic activities increasingly concentrate in large-scale central cities, the future development of prefecture-level cities may gradually diverge.

La Carrera de Campeche (1717-1818): demografia móvel, devoções vernáculas e estradas provincias

This article studies how the Carrera de Campeche, a series of fluvial and land traffic and mobility routes, connected the city port of Campeche and the gulf of Mexico with the Carrera de Guatemala, the commercial circuit that linked the audiencias/kingdoms of New Spain and Guatemala. For this, a review of the regional, economic historiography and anthropological studies was made; also archival documents and cartography collected in Mexico, Guatemala, the United States and Spain to support the hypothesis of the existence of the routes. As a result, it was possible to corroborate the existence of a dynamic demography and in continuous movement, fortified by regional devotions that strengthened the religious-cultural integration and that allowed to sustain the road projects of magistrates and elites in the Carrera de Campeche, at the end of the Spanish colonial period.

Migration Trajectories of Indonesian Expatriates in South Korea

Abstract: Despite its ambition to tap into global talent, South Korea has been struggling to scout and facilitate the migration of professional migrants. This study investigates the migration trajectory of Indonesian expatriates and how they successfully achieve labor market insertion in South Korea. It focuses on the mobility routes of migrants to become highly skilled workers: their motivation, the ways they migrate, and elaborates on how migrants from a developing country enhance their likelihood of getting hired. Nine professionals from the under-researched group were interviewed to uncover a range of migration trajectories and its relationship with employment prospects. The findings suggest that ethnic identity is crucial to improve the labor market outcome, which indicates an exclusive and ethnicized labor market in Korea.

The city as a factor of socialization of preschoolers: routes of movement and semantic points

Based on the materials of sociological surveys, the article reveals the routes and semantic points of urban movements of preschoolers. The subject of the study is the city as a socio-territorial education and a space of socialization, with the main focus on the mobility of preschool children. The city, being a factor in the socialization of children, promotes the development of cognitive interest and communication skills, ensures integration into communities and the accumulation of social capital. Moving around the city forms identity, develops skills and promotes social integration, emphasizing the role of the city in the reproduction of connections and relationships. The study was conducted using the principles of the concept of Sociology of mobility of J. Urry and M. Scheller. The article presents the results of two studies conducted in 2021 and 2023. The object of the first study is the parent community of Yekaterinburg, which has preschool children (n=163), the objects of the second are teachers of preschool educational institutions (n=412). The research includes online surveys and interviews with parents, identifying travel routes and their social contexts in an urban environment. Four routes of urban movement are identified: educational, leisure and gaming, household, educational and recreational. Parents with preschool children do not limit themselves to the proposed trajectories, also visiting relatives, friends, shopping malls, cafes/restaurants. The study of mobility routes contributes to the study of children's space, which depends on factors of different order and level (type of territory, material wealth and type of family, etc.). The work argues that the socialization capabilities of the city for the development of children, on the one hand, are limited by the local infrastructure of the family's residential neighborhood, on the other hand, the choice of parental community routes urban mobility and a semantic map of movements.

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Routing in Mobile ad Hoc Networks Using Machine Learning Techniques

The significance of Mobile Ad Hoc Networks (MANETs) has increased in the current period due to the proliferation of mobile devices and the emergence of Internet of Things (IoT) applications. The function of routing in decentralized wireless networks is of paramount importance in facilitating efficient data transfer. Conventional routing techniques need help in effectively adjusting to the dynamic changes in network topology and the constraints imposed by restricted network resources. To tackle these concerns, a Machine Learning-Based Optimized Routing Algorithm (ML-ORA) is proposed in this research. ML-ORA has been developed to offer adaptable and intelligent routing solutions, especially in MANET. This is achieved via the integration of parameter settings, the use of a Hybrid Particle Swarm Optimization (HPSO) algorithm for Cluster Head (CH) selection, the inclusion of a clustering stage, and the incorporation of a k-Nearest Neighbors (k-NN)-based intrusion detection system. The performance of ML-ORA is assessed by conducting simulations using Network Simulator 3 (NS-3), demonstrating its efficacy in dynamic network settings. The findings exhibit a latency of 15 milliseconds, a packet delivery ratio of 95%, a network throughput of 4Mbps, and an energy efficiency of 85%. ML-ORA presents a potentially advantageous resolution for tackling the obstacles encountered in MANET routing, thereby creating opportunities for enhanced efficacy and security in the transmission of data inside dynamic wireless networks.

Research status and prospect of electrode materials for lithium-ion battery

The lithium-ion battery has become one of the most widely used green energy sources, and the materials used in its electrodes have become a research hotspot. There are many different types of electrode materials, and negative electrode materials have developed to a higher level of perfection and maturity than positive electrode materials. Enhancing the electrochemical capabilities of positive electrode materials is therefore crucial. In addition to exploring and choosing the preparation or modification methods of various materials, this study describes the positive and negative electrode materials of lithium-ion batteries. Among the negative electrode materials, Li4Ti5O12 is beneficial to maintain the stability of the battery structure, and the chemical vapor deposition method is the best way to prepare nitrogen-doped graphene materials. Doping and coating modifications for positive electrode materials can offer a smoother mobile route for lithium ions, which can enhance the cathode materials cycling performance. This papers study, summary, and outlook on electrode materials for lithium-ion batteries can aid those researchers in developing a more thorough understanding of electrode materials. Also, it can be advantageous for the growth of associated follow-up research projects and the expansion of the lithium battery market.

Novel Source-Storage Coordination Strategy Adaptive to Impulsive Generation Characteristic Suitable for Isolated Island Microgrid Scheduling

Wave energy generator (WEG) is a new renewable energy source with prominent advantages and disadvantages. Theoretically, it can move around the sea to harvest wave energy better and will not take up valuable land resources. Normally, WEG collects tiny wave energy continuously and generates electricity intermittently on the minute time-scale to enhance energy harvesting efficiency. Thus, the output of WEG shows prominent impulsive characteristics, which needs to be compensated by the battery energy storage system (BESS) and therefore brings about significant battery life losses. For the purpose of stable and economic operation of the weak power grid connected by WEG, a flexible control method enabling a quantifiable tradeoff between its energy harvesting efficiency and impulsive characteristics is proposed. Then, a novel source-storage coordination strategy and the corresponding energy exchange model of WEG with several optimizable control parameters is formulated to depict the energy flow within the microgrid. Subsequently, an optimization algorithm is proposed to schedule the WEG’s mobile route and optimizable control parameters simultaneously. Simulation results show that the proposed source-storage strategy and the energy management scheme can balance WEG’s energy harvesting and impulsive impact, and utilize its mobility to improve the isolated island microgrid’s operation economy and power quality.

The Illusion of Merit in Political Leadership Selection in China

AbstractIn China, government at all levels relies on the specially selected graduates (SSG) scheme to recruit elite university students as future political leaders. This article examines the mechanism of the SSG scheme and the relationship between elite university education and political selection in China. We show that elite education is increasingly stratified, such that graduates from top elite universities have significant selection advantages in the SSG competition and are more likely to be offered incentives and preferences. We argue that taking elite university education as a hard eligibility criterion reinforces the homophily effects in selection of future political elites and strengthens the political influence of top elite universities on China's politics. Further, because poor and lower-class students have little chance of entering elite universities, the SSG does not provide an effective route of upward mobility for non-elite classes. Merit-based political recruitment as a channel of upward mobility for non-elite classes is largely an illusion.

A comprehensive cost performance analysis for a QoS-based scheme in network mobility (NEMO)

By shifting the portability task away from a mobile network node and onto a mobile router, the NEMO BS protocol has been given the green light to run by the Internet Engineering Task Force (IETF) working group. It is not effective to anticipate the mobility of each node in a train, bus, or ship individually. Hence, it would be reasonable to hire a Mobile Router (MR) that collectively handles the mobility of the entire mobile network. The NEMO BS protocol encourages efficient mobility for groups. Devices on a mobile network do not recognize the mobility of their network. Uninterrupted Internet connectivity is still given to mobile network nodes (i.e. the devices) despite the fact that the network's connection point is shifted on the Internet. The NBS solution has severe performance limitations (e.g. triangular routing and signalling cost). To address the aforementioned issues, the Diff-FH NEMO pattern has formerly been proposed. This article built a methodology to evaluate signalling costs for major Diff-FH NEMO entities. For verification, the effectiveness of the proposed scheme Diff-FH NEMO is measured against that of the industry-standard NEMO BS protocol and the MIPv6-based Route Optimization (MIRON) scheme. Many important indicators, such as the length of time a user spends in a subnet and the total number of hops, are used to compare the signalling cost to (DiffServ Mobile Router (DMRs), Correspondent Nodes (CNs), Local Fixed Nodes (LFNs), and mobile nodes). The analytical findings indicate that the suggested approach gained considerable act enhancement by shrinking the total signalling cost when the network size was enlarged.

Multi-Sensor Based healthcare monitoring system by LoWPAN-based architecture

The development of the Internet of Things (IoT) has recently revived interest in IPv6 over Low-Power Wireless Personal Area Networks (6LoWPAN). For the enormous IP-based detection technologies in the future IoT, 6LoWPAN mobile compatibility is still in its infancy. A significant 6LoWPAN use of IoT, the hospital's wireless technology, which continuously monitors patients' vital signs, regardless of whether they are moving. To track accurate patient positions, communication between patient nodes and the hospital network needs to be maintained through sensor network. In addition, it must offer automatic switching and improve the power consumption of devices. In this research, a hospital structure based on 6LoWPAN with a Media Access Control (MAC) design for patient data was offered. Our preliminary numerical results indicate a decrease in the expenses associated with transfers on the mobile router, which generally represents a bottleneck in such a network. Biological ECG signals are routed via low pan before transmission via routing algorithms to the gateway network.

High-throughput calculation of organ-scale traits with reconstructed accurate 3D canopy structures using a UAV RGB camera with an advanced cross-circling oblique route

The measurement of organ-scale traits in large-scale fields remains a bottleneck in genotype-phenotype association studies for crop improvement. To address this issue, an advanced cross-circling oblique (CCO) route was proposed, consisting of multiple single-circle routes. Using multi-view images from lightweight UAVs with the CCO route, 3D crop canopies were reconstructed for maize, cotton, and sugar beet. Organ-scale traits were estimated from the CCO-derived and traditional five-directional oblique (FDO)-derived 3D canopy models and were compared to manual measurements. An algorithm was further proposed to compare the image utilisation efficiency between the CCO route and FDO route with three indicators, including the total utilisation (TU), effective utilisation (EU), and occlusion rate (OR). The results showed that the proposed CCO route can obtain complete canopy structures throughout the growth stages for crops with relatively wide-row planting, such as maize. For densely planted crops like cotton, the full canopy structure at early growth stages (47 d after sowing (DAS)) and the upper parts of the canopy architecture at later growth stages (71 and 90 DAS) could be obtained. The leaf length and width from different layers estimated from CCO-derived models were in good agreement with manual measurements for maize (R2 = 0.93, RMSE = 3.05 cm, nRMSE = 4.7% and R2 = 0.88, RMSE = 0.49 cm, nRMSE = 5.5% for leaf length and leaf width, respectively) and cotton (R2 = 0.81, RMSE = 1.16 cm, nRMSE = 8.6% and R2 = 0.93, RMSE = 0.99 cm, nRMSE = 7.2% for leaf length and leaf width, respectively). CCO-derived 3D canopy models also provided higher accuracy for organ-scale trait estimation than FDO-derived 3D canopy models (R2 of 0.80 versus 0.76 for both leaf length and width estimation, respectively). Regarding image utilisation, the CCO route outperformed the FDO route, with an average value of 124% higher in EU and 11.7% lower in OR, tested on sugar beet varieties with different canopy structures. The proposed CCO route adopts a non-linear mobile route to obtain canopy images from more perspectives, taking into account both the model accuracy and efficiency. Although the flight altitude of the CCO in this study was relatively low (4 m above the canopy), the same model accuracy can be achieved at higher flight altitudes using a higher-quality camera, thus significantly reducing image acquisition time. This study represents the first time that accurate crop structures in large-scale fields were characterised using a method featuring mobility, affordability, throughput, accuracy, and efficiency. The proposed method could provide novel opportunities for accelerating plant breeding and precision agriculture.

Incident Diversionary Routing: Survey of Influences and Decisions

When confronted with congestion and delay, drivers often divert their route. Depending on factors like purpose, urgency, destination, route alternatives, type of disruption, and mode options, common diversionary options can range from changing departure time, route, and mode to canceling a trip altogether. The choice to divert depends on several factors, including whether, when, and where they become aware of a disruption. As the ability of transportation agencies to detect incidents, inform drivers of conditions, and implement control-changes to accommodate volume surges has improved, there is increasing interest in knowing whether drivers will divert and why. This article describes the results of research using marketing-based survey techniques to evaluate driver diversionary behavior during roadway incidents. The survey was used to identify and assess diversionary choice-making a) based on travel behaviors and habits, b) under routine and adverse conditions, c) for different incidents and route options; and d) under varied guidance information available to them. The results showed that travel time reduction was the primary motivator for alternate path use to avoid congestion, consistent with previous research. Interestingly, younger males showed the lowest level of influence from guidance information, and route familiarity had a lower influence on diversionary routing among all groups, suggesting a trust in real-time mobile routing guidance. With additional analyses, these findings could be applied to estimate and model driver actions under a range of driver-, network-, travel-, and disruption conditions.

An integrated assignment, routing, and speed model for roadway mobility and transportation with environmental, efficiency, and service goals

Managing all the mobility and transportation services with autonomous vehicles for users of a smart city requires determining the assignment of the vehicles to the users and their routing in conjunction with their speed. Such decisions must ensure low emission, efficiency, and high service quality by also considering the impact on traffic congestion caused by other vehicles in the transportation network.In this paper, we first propose an abstract trilevel multi-objective formulation architecture to model all vehicle routing problems with assignment, routing, and speed decision variables and conflicting objective functions. Such an architecture guides the development of subproblems, relaxations, and solution methods. We also propose a way of integrating the various urban transportation services by introducing a constraint on the speed variables that takes into account the traffic volume caused across the different services. Based on the formulation architecture, we introduce a (bilevel) problem where assignment and routing are at the upper level and speed is at the lower level. To address the challenge of dealing with routing problems on urban road networks, we develop an algorithm that alternates between the assignment-routing problem on an auxiliary complete graph and the speed optimization problem on the original non-complete graph. The computational experiments show the effectiveness of the proposed approach in determining approximate Pareto fronts among the conflicting objectives.

IoT-Enabled Precision Agriculture: Developing an Ecosystem for Optimized Crop Management

The Internet of Things (IoT) has the potential to revolutionize agriculture by providing real-time data on crop and livestock conditions. This study aims to evaluate the performance scalability of wireless sensor networks (WSNs) in agriculture, specifically in two scenarios: monitoring olive tree farms and stables for horse training. The study proposes a new classification approach of IoT in agriculture based on several factors and introduces performance assessment metrics for stationary and mobile scenarios in 6LowPAN networks. The study utilizes COOJA, a realistic WSN simulator, to model and simulate the performance of the 6LowPAN and Routing protocol for low-power and lossy networks (RPL) in the two farming scenarios. The simulation settings for both fixed and mobile nodes are shared, with the main difference being node mobility. The study characterizes different aspects of the performance requirements in the two farming scenarios by comparing the average power consumption, radio duty cycle, and sensor network graph connectivity degrees. A new approach is proposed to model and simulate moving animals within the COOJA simulator, adopting the random waypoint model (RWP) to represent horse movements. The results show the advantages of using the RPL protocol for routing in mobile and fixed sensor networks, which supports dynamic topologies and improves the overall network performance. The proposed framework is experimentally validated and tested through simulation, demonstrating the suitability of the proposed framework for both fixed and mobile scenarios, providing efficient communication performance and low latency. The results have several practical implications for precision agriculture by providing an efficient monitoring and management solution for agricultural and livestock farms. Overall, this study provides a comprehensive evaluation of the performance scalability of WSNs in the agriculture sector, offering a new classification approach and performance assessment metrics for stationary and mobile scenarios in 6LowPAN networks. The results demonstrate the suitability of the proposed framework for precision agriculture, providing efficient communication performance and low latency.