• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.73-80
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• 2023

The recent growth in the use of mobile devices has contributed to increased computing and storage requirements. Cloud computing has been used over the past decade to cater to computational and storage needs over the internet. However, the use of various mobile applications like Augmented Reality (AR), M2M Communications, V2X Communications, and the Internet of Things (IoT) led to the emergence of mobile cloud computing (MCC). All data from mobile devices is offloaded and computed on the cloud, removing all limitations incorporated with mobile devices. However, delays induced by the location of data centers led to the birth of edge computing technologies. In this paper, we discuss one of the edge computing technologies, i.e., cloudlet. Cloudlet brings the cloud close to the end-user leading to reduced delay and response time. An algorithm is proposed for scheduling tasks on cloudlet by considering VM's load. Simulation results indicate that the proposed algorithm provides 12% and 29% improvement over EMACS and QRR while balancing the load.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.4
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• pp.145-156
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• 2022

To strengthen the security of autonomous vehicles, this study derived checklists through the analysis of the status of autonomous vehicle security. The analyzed statuses include autonomous vehicle characteristics, security threats, and domestic and foreign security standards. The derived checklists are then applied to the AHP(Analytic Hierarchy Process) model to find their relative importance. Relative importance was ranked as one of cyber security management system establishment and implementation, encryption, risk assessment, etc. The significance of this study is to reduce cyber security incidents that cause human casualties as well improve the level of security management of autonomous vehicles in related companies by deriving the autonomous vehicle security level checklists and demonstrating the model. If the inspection is performed considering the relative importance of the checklists, the security level can be identified early.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.2
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• pp.165-171
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• 2013

WAVE(Wireless Access in Vehicular Environments) is a representative V2V communication protocol and its standards of MAC and PHY parts except for security were published. In order to control traffic flow and ensure driver's safety using V2V communication, various projects are conducting. In particular, safety application has been researched. Therefore, in this paper, we designed the safety application algorithm, which informs a driver of the dangerous status when driver tries to turn left in an intersection and we also implemented the algorithm. Proposed algorithm configures a model for a host vehicle and a vehicle coming in opposite lane and in case that there is collision hazard it provides warning message to driver by using HMI. In order to evaluate the proposed algorithm's performance, we configured the test bed using test vehicles and we tested the algorithm on proving ground with the composed test scenarios. As test results, our system showed excellent performance. If the infrastructures for V2I communications are constructed, we will optimize our system more precisely and stably.

• Advanced Industrial SCIence
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• v.3 no.1
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• pp.23-29
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• 2024

In this scholarly investigation, the focus is placed on the transformative potential of edge computing in enhancing Intelligent Transportation Systems (ITS) for the facilitation of autonomous driving. The intrinsic capability of edge computing to process voluminous datasets locally and in a real-time manner is identified as paramount in meeting the exigent requirements of autonomous vehicles, encompassing expedited decision-making processes and the bolstering of safety protocols. This inquiry delves into the synergy between edge computing and extant ITS infrastructures, elucidating the manner in which localized data processing can substantially diminish latency, thereby augmenting the responsiveness of autonomous vehicles. Further, the study scrutinizes the deployment of edge servers, an array of sensors, and Vehicle-to-Everything (V2X) communication technologies, positing these elements as constituents of a robust framework designed to support instantaneous traffic management, collision avoidance mechanisms, and the dynamic optimization of vehicular routes. Moreover, this research addresses the principal challenges encountered in the incorporation of edge computing within ITS, including issues related to security, the integration of data, and the scalability of systems. It proffers insights into viable solutions and delineates directions for future scholarly inquiry.

• Review of KIISC
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• v.27 no.5
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• pp.21-25
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• 2017

최근 자율주행차량 기술의 상용화가 임박함에 따라, 차량통신보안 기술의 중요성도 부각되고 있다. 이와 더불어 차량통신보안 표준화의 중요성도 대두되고 있으며, 그 일환으로 ITU-T SG17에서는 2017년 ITS 보안 연구반을 신설하여 표준화를 활발히 추진하고 있다. 특히, 최근 차량 소프트웨어 업데이트 규격이 표준 승인되었으며, V2X 통신 보안 가이드라인의 표준화가 활발히 진행되고 있다. 또한, 최근 회의에서 차내망 침입탐지시스템, 차량 접속 디바이스 보안 요구사항, 차량에지 컴퓨팅 보안 가이드라인 등이 신규 표준화 과제로 선정되었다. 본 논문에서는 SG17에서 신설된 ITS 보안 연구반에서의 표준화 동향을 살펴 본다.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.406-412
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• 2022

Storing large amounts of data has always been a big problem from the beginning of computing history. Big Data has made huge advancements in improving business processes by finding the customers' needs using prediction models based on web and social media search. The main purpose of big data stream processing frameworks is to allow programmers to directly query the continuous stream without dealing with the lower-level mechanisms. In other words, programmers write the code to process streams using these runtime libraries (also called Stream Processing Engines). This is achieved by taking large volumes of data and analyzing them using Big Data frameworks. Streaming platforms are an emerging technology that deals with continuous streams of data. There are several streaming platforms of Big Data freely available on the Internet. However, selecting the most appropriate one is not easy for programmers. In this paper, we present a detailed description of two of the state-of-the-art and most popular streaming frameworks: Apache Ignite and Hazelcast. In addition, the performance of these frameworks is compared using selected attributes. Different types of databases are used in common to store the data. To process the data in real-time continuously, data streaming technologies are developed. With the development of today's large-scale distributed applications handling tons of data, these databases are not viable. Consequently, Big Data is introduced to store, process, and analyze data at a fast speed and also to deal with big users and data growth day by day.