• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.2
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• pp.73-86
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• 2018

The increase in the number of private automobiles has incurred various traffic problems. Globally, studies on MaaS(Mobility as a Service) has already been initiated to mobilize the use of public transportation in reducing private passenger cars in roads. This study aims to analyze the passenger's optimal route considering the transfer between different transportation modes through simulation, and analyze the effect of available route through the connected transportation modes. Sejong Special Self-Governing City was chosen as the study area due to its extensive transportation network. As a result of the analysis, the predominant obtainable route is derived either from using public transportation (i.e. bus and subway) only or by bicycle. However, it is also possible to use the car sharing and public bicycle to reach their final destination efficiently when paths that can be traversed were more scrutinized. When various transportation information and location-based services are introduced in smart phone applications, they can provide very useful information to passengers, and also promote social problems such as traffic congestion and environmental issues in the future.

• Journal of Digital Convergence
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• v.15 no.3
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• pp.77-86
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• 2017

This study selected car-related mobile apps for app developers suffering from low revenue and classified car apps assisting users in driving or managing a car. A total of 697 car apps were classified into eight categories. Most apps are in four categories: car news & information (28%), locating service (23%), car rental service (15%), safe/efficient driving service (12%). The remaining categories are buying & selling, driver's communication, maintenance management, and expenses monitoring. Many apps are simple and too similar in their main functions. Only a few apps are designed to be more comprehensive and have functions in two or more categories. For the practicality of the categorization scheme, this study checked the inter-rater reliability in two tests and got 0.886 and 0.828. The result from this study suggests functions that are not implemented yet or need to be combined. Future research will focus on identifying promising car apps or designing multi-functional car apps.

• The Transactions of the Korea Information Processing Society
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• v.13 no.2
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• pp.48-59
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• 2024

As functions that support virtualization on their own in hardware are developed, user applications having various workloads are operating efficiently in the virtualization system. SR-IOV is a virtualization support function that takes direct access to PCI devices, thus giving a high I/O performance by minimizing the need for hypervisor or operating system interventions. With SR-IOV, network I/O acceleration can be realized in virtualization systems that have relatively long I/O paths compared to bare-metal systems and frequent context switches between the user area and kernel area. To take performance advantages of SR-IOV, network resource management policies that can derive optimal network performance when SR-IOV is applied to an instance such as a virtual machine(VM) or container are being actively studied.This paper evaluates and analyzes the network performance of SR-IOV implementing I/O acceleration is compared with Virtio in terms of 1) network delay, 2) network throughput, 3) network fairness, 4) performance interference, and 5) multi-network. The contributions of this paper are as follows. First, the network I/O process of Virtio and SR-IOV was clearly explained in the virtualization system, and second, the evaluation results of the network performance of Virtio and SR-IOV were analyzed based on various performance metrics. Third, the system overhead and the possibility of optimization for the SR-IOV network in a virtualization system with high VM density were experimentally confirmed. The experimental results and analysis of the paper are expected to be referenced in the network resource management policy for virtualization systems that operate network-intensive services such as smart factories, connected cars, deep learning inference models, and crowdsourcing.