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As the capabilities of mobile devices and mobile communication techniques expand, vehicular ad hoc networks (VANETs) play an increasingly significant role in transportation and traffic management, particularly in Intelligent Transportation Systems (ITS). However, the rapid topology changes, high vehicle mobility, and frequent link disconnections make routing in VANETs a challenging task, necessitating the development of efficient routing protocols. Moreover, as VANET services provided in our daily lives become more extensive and situations in which they are provided simultaneously to an increasing number of users become more frequent, numerous data delivery optimization algorithms have been researched to address these issues. Alongside this, the research related to Unnamed Aerial Vehicles (UAVs) has also been utilized as a solution to solve the physical data link disconnection problem of VANETs. In this paper, we propose a routing protocol called PSUV (Particle Swarm UAV-VANET). First, we have solved the software-related issues of VANETs by measuring data transmission availability of vehicles existing in the topology and conducting topology optimization by creating a vehicle routing table, utilizing a mathematical value calculation formula that combines Particle Swarm Optimization (PSO) from Swarm Intelligence (SI) and the directional vector information of the vehicle. Furthermore, by utilizing UAVs, we address the physical disconnectivity issues that arise during data transmission in VANETs, thereby minimizing the delay and maximizing the total data rate under realistic conditions. Finally, extensive simulations are conducted to validate the superiority of the proposed protocol in various circumstances in an NS-3 simulation. Simulation results indicate that the proposed protocol solves the challenging issues in realistic VANET with significant improvement.

Botrytis cinerea is a major fungal plant pathogen that causes gray mold disease in strawberries, leading to a decrease in strawberry yield. While benzimidazole is widely used as a fungicide for controlling this disease, the increasing prevalence of resistant populations to this fungicide undermines its effectiveness. To investigate benzimidazole resistant B. cinerea in South Korea, 78 strains were isolated from strawberries grown in 78 different farms in 2022, and their EC50 values for benzimidazole were examined. As a result, 64 strains exhibited resistance to benzimidazole, and experimental tests using detached strawberry leaves and the plants in a greenhouse confirmed the reduced efficacy of benzimidazole to control these strains. The benzimidazole resistant strains identified in this study possessed two types of mutations, E198A or E198V, in the TUB2 gene. To detect these mutations, TaqMan probes were designed, enabling rapid identification of benzimidazole resistant B. cinerea in strawberry and tomato farms. This study utilizes TaqMan real-time polymerase chain reaction analysis to swiftly identify benzimidazole resistant B. cinerea, thereby offering the possibility of effective disease management by identifying optimum locations and time of application.

Objectives This study aimed to examine the correlations between the regional characteristics of counties in Gangwon Province, Republic of Korea and the ratio of intracounty to extracounty sources of coronavirus disease 2019 (COVID-19) infection. Methods The region of the infectious contact was analysed for each COVID-19 case reported in Gangwon Province between February 22, 2020 and February 7, 2022. The population, population density, area, the proportion of urban residents, the proportion of older adults (>65 years), financial independence, and the number of adjacent counties were assessed for each of the 18 counties in Gangwon Province. Correlation coefficients between regional characteristics and the ratio of intracounty to extracounty infections were calculated. Results In total, 19,645 cases were included in this study. The population, population density, proportion of older adults, and proportion of urban residents were significantly correlated with the ratio of intracounty to extracounty infections. A stratified analysis with an age cut-point of 65 years showed that the proportion of older adults had a significant negative correlation with the ratio of intracounty to extracounty infections. In other words, the proportions of extracounty infections were higher in counties with higher proportions of older adults. Conclusion Regions with ageing populations should carefully observe trends in infectious disease outbreaks in other regions to prevent possible transmission.

The development of smart vehicles such as self-driving cars has resulted in an increased demand for content consumption in vehicles. This demand for content, coupled with the improved quality of the content and the expanding resolution of the display, leads to a significant increase in mobile data traffics with larger sizes in content-centric vehicular networks (CCVNs). Since a single RSU cannot fully provide the larger size contents in its communication coverage due to its limited transmission rate, many studies on precaching contents have been actively conducted. By considering only delay-sensitive contents, previous precaching schemes immediately precache contents in the next continuous RSUs on trajectories of vehicles through paying lots of traffics for reducing delays. However, every application content in CCVNs might generally have a tolerable delay time to vehicles according to its characteristics related to service satisfaction. By considering the tolerable delay time, the already stored content on RSUs reached by vehicles within the tolerable delay time can be exploited to download the content without precaching. As a result, precaching of contents can be reduced and thus the traffics can be also reduced. To address this issue, we thus propose a Traffic Optimized Content Precaching (TOCP) scheme based on the tolerable delay time in CCVNs, which minimizes traffics consumed for delay-tolerant contents and decreases delays for delay-sensitive contents. To do this, we first provide a numerical model to judge the precaching necessity by calculating the content provision possibility. Next, we build a Delay-tolerant content Management Module (DMM) for managing the updated information and design new packet formats for reducing the movements of the large-size contents to achieve the optimization purpose of TOCP. Then, we select Optimal Precaching RSUs (OPRs) by solving our optimization problem by using ILP. Last, we provide a process for allowing only OPRs to participate in the content provision. Through simulation results conducted in various environments, we demonstrate that TOCP minimizes the traffic and caching burden while maintaining high reliability in comparison with the previous schemes.

Vehicular clouds represent an appealing approach, leveraging vehicles’ resources to generate value-added services. Thus, efficiently searching for and allocating resources is a challenge for the successful construction of vehicular clouds. Many recent schemes have relied on hierarchical network architectures using clusters to address this challenge. These clusters are typically constructed based on vehicle proximity, such as being on the same road or within the same region. However, this approach struggles to rapidly search for and consistently allocate resources, especially considering the diverse resource types and varying mobility of vehicles. To address these limitations, we propose the Resource Cluster-based Resource Search and Allocation (RCSA) scheme. RCSA constructs resource clusters based on resource types rather than vehicle proximity. This allows for more efficient resource searching and allocation. Within these resource clusters, RCSA supports both intra-resource cluster search for the same resource type and inter-resource cluster search for different resource types. In RCSA, vehicles with longer connection times and larger resource capacities are allocated in vehicular clouds to minimize cloud breakdowns and communication traffic. To handle the reconstruction of resource clusters due to vehicle mobility, RCSA implements mechanisms for replacing Resource Cluster Heads (RCHs) and managing Resource Cluster Members (RCMs). Simulation results validate the effectiveness of RCSA, demonstrating its superiority over existing schemes in terms of resource utilization, allocation efficiency, and overall performance.

Owing to the increasing capabilities of mobile devices and the development of mobile communication techniques in vehicular ad hoc networks (VANETs), mobile multimedia services have focused on supporting high Quality of Service (QoS) and Quality of Experience (QoE) for the subscribers in video streaming services. In VANETs, high-quality video streaming services aim to provide subscribers with safety and various infotainment applications. Due to the dynamic topology and frequent connectivity changes in moving vehicles, video streaming services require elastic and continuous vehicle information updates to present interactive real-time views of nontrivial road scenarios. The QoS and QoE are affected due to obstacles, re-location tracking, network traffic, and bandwidth factors that occur due to mobility problems and significantly influence the ability of vehicles with mobility to provide video streaming services. To achieve high QoS and QoE of video streaming services in VANETs, this paper proposes a novel protocol named PSOstreaming based on a particle swarm optimization (PSO) which is one of the mainstream and nature-inspired algorithms for swarm intelligence (SI). PSOstreaming calculates the PSQ score, which is the scoring method of the node in the topology in terms of the data communication capability measurement to analyze and optimize topology information in real-road circumstances. In addition, PSOstreaming utilizes a 3D vector mobility prediction algorithm for the mobility prediction method for the vehicles to address the characteristics of VANETs. In the topology, PSOstreaming defines Global PSO members and Local PSO members to disseminate video packets for video-streaming services to the service requester by computational equations. Experimental results indicate that PSOstreaming achieves high-quality video streaming services with a flexible response to dynamic topology changes and a high frame delivery ratio in terms of QoS and QoE.

In vehicular networks, vehicles download vehicular information for various applications, including safety, convenience, entertainment, and social interaction, from the corresponding content servers via stationary roadside units. Since sufficient RSUs might be difficult to deploy due to rough geographical conditions or high deployment costs, vehicular networks can feature uncovered outage zones between two neighboring RSUs. In these outage zones, vehicles cannot download content, and thus the vehicle networks are defined as intermittently connected vehicular networks. In intermittently connected vehicular networks, the download delay and traffic overhead on the backhaul links are increased due to the large size of the content requested by vehicle users and the long distances between RSUs. Using the mobility information of vehicles, several schemes have been proposed to solve this issue by precaching and relaying content via multiple relaying vehicles in the outage zone. However, because they involved the individual ranking of vehicles for precaching and allocated all of the available precaching amounts to the top-ranking vehicles, they decreased the success rate of content requests and the fairness of vehicle precaching. To overcome the problem of these previous schemes, this paper proposes a multiple precaching vehicle selection (MPVS) scheme that efficiently selects a content-precaching vehicle group with multiple precaching vehicles to precache relayed content in outage zones. To achieve this, we first designed numerical models to decide the necessity and the amount of precaching and to calculate the available precaching amounts of vehicles. Next, MPVS calculates all available vehicle sets and ranks each set based on the available precaching amount. Then, the content-precaching vehicle group is identified from the sets by considering both set rankings and vehicle communication overheads. MPVS also provides a content downloading process through the content-precaching vehicle group in the outage zone. Simulation results conducted in various environments with a content request model and a highway mobility model verified that MPVS was superior to a representative previous scheme.

Long range (LoRa) is a low-power wide-area technology because it is eminent for robust long-distance, low-bitrate, and low-power communications in the unlicensed sub-GHz spectrum used for the Internet of things (IoT) networks. Recently, several multi-hop LoRa networks have proposed schemes with explicit relay nodes to partially mitigate the path loss and longer transmission time bottlenecks of the conventional single-hop LoRa by focusing more on coverage expansion. However, they do not consider improving the packet delivery success ratio (PDSR) and the packet reduction ratio (PRR) by using the overhearing technique. Thus, this paper proposes an implicit overhearing node-based multi-hop communication (IOMC) scheme in IoT LoRa networks, which exploits implicit relay nodes for performing the overhearing to promote relay operation while satisfying the duty cycle regulation. In IOMC, implicit relay nodes are selected as overhearing nodes (OHs) among end devices with a low spreading factor (SF) in order to improve PDSR and PRR for distant end devices (EDs). A theoretical framework for designing and determining the OH nodes to execute the relay operations was developed with consideration of the LoRaWAN MAC protocol. Simulation results verify that IOMC significantly increases the probability of successful transmission, performs best in high node density, and is more resilient to poor RSSI than the existing schemes.

Long range (LoRa) is one of the most successful low-power wide-area networking technologies because it is ideally suited for long-distance, low-bit rate, and low-power communications in the unlicensed sub-GHz spectrum utilized for Internet of things (IoT) networks. The effectiveness of LoRa depends on the link budget (i.e., spreading factor (SF), bandwidth (BW), and transmission power (TX)). Due to the near–far effect, the allocation of a link budget to LoRa devices (LDs) in large coverage regions is unfair between them depending on their distance to the GW. Thus, more transmission opportunities are given to some LDs to the detriment of other LD’s opportunities. Numerous studies have been conducted to address the prevalent near–far fairness problem. Due to the absence of a tractable analytical model for fairness in the LoRa network, however, it is still difficult to solve this problem completely. Thus, we propose an SF-partition-based clustering and relaying (SFPCR) scheme to achieve enormous LD connectivity with fairness in IoT multihop LoRa networks. For the SF partition, the SFPCR scheme determines the suitable partitioning threshold point for bridging packet delivery success probability gaps between SF regions, namely, the lower SF zone (LSFZ) and the higher SF zone (HSFZ). To avoid long-distance transmissions to the GW, the HSFZ constructs a density-based subspace clustering that generates clusters of arbitrary shape for adjacent LDs and selects cluster headers by using a binary score representation. To support reliable data transmissions to the GW by multihop communications, the LSFZ offers a relay LD selection that ideally chooses the best relay LD to extend uplink transmissions from LDs in the HSFZ. Through simulations, we show that the proposed SFPCR scheme exhibits the highest success probability of 65.7%, followed by the FSRC scheme at 44.6%, the mesh scheme at 34.2%, and lastly the cluster-based scheme at 29.4%, and it conserves the energy of LDs compared with the existing schemes.

By leveraging the development of mobile communication technologies and due to the increased capabilities of mobile devices, mobile multimedia services have gained prominence for supporting high-quality video streaming services. In vehicular ad-hoc networks (VANETs), high-quality video streaming services are focused on providing safety and infotainment applications to vehicles on the roads. Video streaming data require elastic and continuous video packet distributions to vehicles to present interactive real-time views of meaningful scenarios on the road. However, the high mobility of vehicles is one of the fundamental and important challenging issues for video streaming services in VANETs. Nevertheless, previous studies neither dealt with suitable data caching for supporting the mobility of vehicles nor provided appropriate seamless packet forwarding for ensuring the quality of service (QoS) and quality of experience (QoE) of real-time video streaming services. To address this problem, this paper proposes a video packet distribution scheme named Clone, which integrates vehicle-to-vehicle and vehicle-to-infrastructure communications to disseminate video packets for video streaming services in VANETs. First, an indicator called current network quality information (CNQI) is defined to measure the feature of data forwarding of each node to its neighbor nodes in terms of data delivery ratio and delay. Based on the CNQI value of each node and the trajectory of the destination vehicle, access points called clones are selected to cache video data packets from data sources. Subsequently, packet distribution optimization is conducted to determine the number of video packets to cache in each clone. Finally, data delivery synchronization is established to support seamless streaming data delivery from a clone to the destination vehicle. The experimental results show that the proposed scheme achieves high-quality video streaming services in terms of QoS and QoE compared with existing schemes.

Content-Centric Vehicular Networks (CCVNs) are considered as an attractive technology to efficiently distribute and share contents among vehicles in vehicular environments. Due to the large size of contents such as multimedia data, it might be difficult for a vehicle to download the whole of a content within the coverage of its current RoadSide Unit (RSU). To address this issue, many studies exploit mobility-based content precaching in the next RSU on the trajectory of the vehicle. To calculate the amount of the content precaching, they use a constant speed such as the current speed of the vehicle requesting the content or the average speed of vehicles in the next RSU. However, since they do not appropriately reflect the practical speed of the vehicle in the next RSU, they could incorrectly calculate the amount of the content precaching. Therefore, we propose an adaptive content precaching scheme (ACPS) that correctly estimates the predictive speed of a requester vehicle to reflect its practical speed and calculates the amount of the content precaching using its predictive speed. ACPS adjusts the predictive speed to the average speed starting from the current speed with the optimized adaptive value. To compensate for a subtle error between the predictive and the practical speeds, ACPS appropriately adds a guardband area to the precaching amount. Simulation results verify that ACPS achieves better performance than previous schemes with the current or the average speeds in terms of the content download delay and the backhaul traffic overhead.