• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.24 no.6
• /
• pp.1147-1157
• /
• 2014

Intelligent transportation system (ITS) is realized through a highly ephemeral network, i.e. vehicular ad hoc network (VANET) which is on its way towards the deployment stage, thanks to the advancements in the automobile and communication technologies. However, it has not been successful, at least to date, to install the technology in the mass of vehicles due to security and privacy challenges. Besides, the users of such technology do not want to put their privacy at stake as a result of communication with peer vehicles or with the infrastructure. Therefore serious privacy measures should be taken before bringing this technology to the roads. To date, privacy issues in ephemeral networks in general and in VANET in particular, have been dealt with through various approaches. So far, multiple pseudonymous approach is the most prominent approach. However, recently it has been found out that even multiple pseudonyms cannot protect the privacy of the user and profilation is still possible even if different pseudonym is used with every message. Therefore, another privacy-aware mechanism is essential in vehicular networks. In this paper, we propose a novel identity exchange mechanism to preserve conditional privacy of the users in VANET. Users exchange their pseudonyms with neighbors and then use neighbors' pseudonyms in their own messages. To this end, our proposed scheme conditionally preserves the privacy where the senders of the message can be revoked by the authorities in case of any dispute.

• Journal of the Korean Society for Railway
• /
• v.13 no.1
• /
• pp.71-77
• /
• 2010

It is increasing annually that the cost for bridge Maintenance Repair & Rehabilitation (MR&R) in developed countries. Based on Intelligent Technology, Bridge Management System (BMS) is developed for optimization of Life Cycle Cost (LCC) and reliability to predict long-term bridge deteriorations. However, such data are very limited amongst all the known bridge agencies, making it difficult to reliably predict future structural performances. To alleviate this problem, an Artificial Neural Network (ANN) based Backward Prediction Model (BPM) for generating missing historical condition ratings has been developed. Its reliability has been verified using existing condition ratings from the Maryland Department of Transportation, USA. The function of the BPM is to establish the correlations between the known condition ratings and such non-bridge factors as climate and traffic volumes, which can then be used to obtain the bridge condition ratings of the missing years. Since the non-bridge factors used in the BPM can influence the variation of the bridge condition ratings, well-selected non-bridge factors are critical for the BPM to function effectively based on the minimized discrepancy rate between the BPM prediction result and existing data (deck; 6.68%, superstructure; 6.61%, substructure; 7.52%). This research is on the generation of usable historical data using Artificial Intelligence techniques to reliably predict future bridge deterioration. The outcomes (Long-term Bridge deterioration Prediction) will help bridge authorities to effectively plan maintenance strategies for obtaining the maximum benefit with limited funds.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.10
• /
• pp.4717-4737
• /
• 2017

Today, smart grids, smart homes, smart water networks, and intelligent transportation, are infrastructure systems that connect our world more than we ever thought possible and are associated with a single concept, the Internet of Things (IoT). The number of devices connected to the IoT and hence the number of traffic flow increases continuously, as well as the emergence of new applications. Although cutting-edge hardware technology can be employed to achieve a fast implementation to handle this huge data streams, there will always be a limit on size of traffic supported by a given architecture. However, recent cloud-based big data technologies fortunately offer an ideal environment to handle this issue. Moreover, the ever-increasing high volume of traffic created on demand presents great challenges for flow management. As a solution, flow aggregation decreases the number of flows needed to be processed by the network. The previous works in the literature prove that most of aggregation strategies designed for smart grids aim at optimizing system operation performance. They consider a common identifier to aggregate traffic on each device, having its independent static aggregation policy. In this paper, we propose a dynamic approach to aggregate flows based on traffic characteristics and device preferences. Our algorithm runs on a big data platform to provide an end-to-end network visibility of flows, which performs high-speed and high-volume computations to identify the clusters of similar flows and aggregate massive number of mice flows into a few meta-flows. Compared with existing solutions, our approach dynamically aggregates large number of such small flows into fewer flows, based on traffic characteristics and access node preferences. Using this approach, we alleviate the problem of processing a large amount of micro flows, and also significantly improve the accuracy of meeting the access node QoS demands. We conducted experiments, using a dataset of up to 100,000 flows, and studied the performance of our algorithm analytically. The experimental results are presented to show the promising effectiveness and scalability of our proposed approach.

• Journal of Korean Society of Rural Planning
• /
• v.21 no.2
• /
• pp.11-21
• /
• 2015

This study carried out evaluation of vulnerability in accessability and functionality using road network that was extracted from Intelligent Transportation System(ITS) and digital map. It was built in order to figure out accessability that locational data which include community center, public facilities, medical facilities and highway IC. The method for grasping functionality are Digital Elevation Model(DEM) and land slide hazard map provided by Korea Forest Service. The evaluation criteria for figure out accessability was set to related comparison of average time in urban area. Functionality value was calculated by the possibility of backing the vehicle possibility of snowfall and landslides. At last, this research computed weighting value through Analytic Hierarchy Process (AHP), calculated a vulnerable score. As the result, the accessability of rural village came out that would spend more time by 1.4 to 3.2 times in comparison with urban area. Even though, vulnerability of the road by a snowfall was estimated that more than 50% satisfies the first class, however, it show up that the road were still vulnerable due snowing because over the 14% of the road being evaluated the fifth class. The functionality has been satisfied most of the road, however, It was vulnerable around Lake Daechung and Piban-ryung, Yumti-jae, Suriti-jae where on the way Boeun. Also, the fifth class road are about 35 km away from the city hall on distance, take an hour to an hour and a half. The fourth class road are about 25 km away from the city hall on distance, take 25 min to an hour. The other class of the road take in 30 min from the city hall or aren't affected of weather and have been analyzed that a density of road is high. In A result that compare between distribution and a housing density came out different the southern and the eastern area, so this result could be suggested quantitative data for possibility of development.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.1
• /
• pp.96-107
• /
• 2015

VANET technologies provide real-time traffic information for mitigating traffic jam and preventing traffic accidents, as well as in-vehicle infotainment service through Telematics/Intelligent Transportation System (ITS). Due to the rapid increasement of various requirements, the vehicle communication with a limited resource and the fixed frame architecture of the conventional techniques is limited to provide an efficient communication service. Therefore, a new flexible operation depending on the surrounding situation information is required that needs an adaptive design of the network architecture and protocol for efficiently predicting, distributing and sharing the context-aware information. In this paper, Vehicle-to-Infrastructure (V2I) based on communication between vehicle and a Road Side Units (RSU) and Vehicle-to-Vehicle (V2V) based on communication between vehicles are effectively combined in a new MAC architecture and V2I and V2V vehicles collaborate in management. As a result, many vehicles and RSU can use more efficiently the resource and send data rapidly. The simulation results show that the proposed method can achieve high resource utilization in accordance. Also we can find out the optimal transmission relay time and 2nd relay vehicle selection probability value to spread out V2V/V2I collaborative schedule message rapidly.

• Journal of Korean Society for Geospatial Information Science
• /
• v.8 no.1 s.15
• /
• pp.51-63
• /
• 2000

Dynamic traffic assignment(DTA) has been a topic of substantial research during the past decade. While DTA is gradually maturing, many aspects of DTA still need improvement, especially regarding its formulation and solution algerian Recently, with its promise for In(Intelligent Transportation System) and GIS(Geographic Information System) applications, DTA have received increasing attention. This potential also implies higher requirement for DTA modeling, especially regarding its solution efficiency for real-time implementation. But DTA have many mathematical difficulties in searching process due to the complexity of spatial and temporal variables. Although many solution algorithms have been studied, conventional methods cannot iud the solution in case that objective function or constraints is not convex. In this paper, the genetic algorithm to find the solution of DTA is applied and the Merchant-Nemhauser model is used as DTA model because it has a nonconvex constraint set. To handle the nonconvex constraint set the GENOCOP III system which is a kind of the genetic algorithm is used in this study. Results for the sample network have been compared with the results of conventional method.