• International Journal of Computer Science & Network Security
• /
• 제22권9호
• /
• pp.376-388
• /
• 2022

The expansion of new applications and business models is being significantly fueled by the development of Fifth Generation (5G) networks, which are becoming more widely accessible. The creation of the newest intelligent vehicular networks and applications is made possible by the use of Vehicular Ad hoc Networks (VANETs) and Software Defined Networking (SDN). Researchers have been concentrating on the integration of SDN and VANET in recent years, and they have examined a variety of issues connected to the architecture, the advantages of software-defined VANET services, and the new features that can be added to them. However, the overall architecture's security and robustness are still in doubt and have received little attention. Furthermore, new security threats and vulnerabilities are brought about by the deployment and integration of novel entities and a number of architectural components. In this study, we comprehensively examine the good and negative effects of the most recent SDN-enabled vehicular network topologies, focusing on security and privacy. We examine various security flaws and attacks based on the existing SDVN architecture. Finally, a thorough discussion of the unresolved concerns and potential future study directions is provided.

• 대한임베디드공학회논문지
• /
• 제19권2호
• /
• pp.107-114
• /
• 2024

Mobile ad hoc networks represent self-configuring networks of mobile devices that communicate without relying on a fixed infrastructure. However, traditional routing protocols in such networks encounter challenges in selecting efficient and reliable routes due to dynamic nature of these networks caused by unpredictable mobility of nodes. This often results in a failure to meet the low-delay and low-energy consumption requirements crucial for such networks. In order to overcome such challenges, our paper introduces a novel multi-objective and adaptive routing scheme based on the Q-learning reinforcement learning algorithm. The proposed routing scheme dynamically adjusts itself based on measured network states, such as traffic congestion and mobility. The proposed approach utilizes Q-learning to select routes in a decentralized manner, considering factors like energy consumption, load balancing, and the selection of stable links. We present a formulation of the multi-objective optimization problem and discuss adaptive adjustments of the Q-learning parameters to handle the dynamic nature of the network. To speed up the learning process, our scheme incorporates informative shaped rewards, providing additional guidance to the learning agents for better solutions. Implemented on the widely-used AODV routing protocol, our proposed approaches demonstrate better performance in terms of energy efficiency and improved message delivery delay, even in highly dynamic network environments, when compared to the traditional AODV. These findings show the potential of leveraging reinforcement learning for efficient routing in ad hoc networks, making the way for future advancements in the field of mobile ad hoc networking.

• Journal of information and communication convergence engineering
• /
• 제7권3호
• /
• pp.241-246
• /
• 2009

Advances in mobile and wireless networking technologies have enabled mobile ad hoc networks applicable to a wide range of areas. Many cases of even such ad hoc networks demand to be accessible to the global network. Owing to be diversified in features depending on applications, however, some those networks may consist of devices or nodes which do not facilitate all the same transport protocols. This results in unreachable situations of establishing ad hoc network: such as non-existence of all required access points, faults or contention in a path of particular protocol communication. Interworking between different transport protocols can alleviate such problems. This paper proposes an interworking scheme to improve data transport performance and network accessibility, especially in such a mobile ad hoc network that is applicable to data communications among ships or user's convenient u-health services. Modeling and simulation analysis are used to verify the improvement.

• Journal of Information Processing Systems
• /
• 제16권4호
• /
• pp.896-914
• /
• 2020

With the rapid growth of network traffic, a large number of connected devices, and higher application services, the traditional network is facing several challenges. In addition to improving the current network architecture and hardware specifications, effective resource management means the development trend of 5G. Although many existing potential technologies have been proposed to solve the some of 5G challenges, such as multiple-input multiple-output (MIMO), software-defined networking (SDN), network functions virtualization (NFV), edge computing, millimeter-wave, etc., research studies in 5G continue to enrich its function and move toward B5G mobile networks. In this paper, focusing on the resource allocation issues of 5G core networks and radio access networks, we address the latest technological developments and discuss the current challenges for resource management in 5G.

• Journal of Communications and Networks
• /
• 제6권4호
• /
• pp.295-306
• /
• 2004

In this paper, a novel air-interface is presented for Fleet-Net1, a self-organizing network for inter-vehicle and vehicle-toroadsidecommunication. The air-interface is based upon the lowchip-rate version of UMTS/TDD. To adapt the cellular UMTS standard to an air-interface for ad hoc networks, changes of the physical layer, medium access control sub-layer and radio resource management are required. An overview of the required modifications is given here. Particularly, a decentralized synchronization mechanism is presented and analyzed by means of simulations. Furthermore, changes for the medium access control are explained in detail, which allow for an efficient operation in partly meshed networks and prioritization. Performance results of the overall system considering throughput and delay are derived by means of analytical evaluations and event-driven simulations. Based on realistic mobility models, it is shown that the presented solution provides a robust communication platform even in vehicular environments. The proposed air-interface is a cost-effective solution not only for inter-vehicle communication, but also for ad hoc networking in general, benefiting from the mass-market of UMTS.

• Journal of Communications and Networks
• /
• 제17권3호
• /
• pp.256-264
• /
• 2015

Energy harvesting devices have been proposed for sensor networking applications where batteries cannot be replaced, and cooperative communication schemes have been used to increase energy efficiency for wireless systems. Here, we develop transmission scheduling schemes for multi-terminal cooperative energy harvesting networks that maximize the packet delivery ratio, i.e., the probability that an event is reported successfully. We see that the proposed scheme provides virtually the same performance as the state-of-the-art threshold-based scheme, but does not require auxiliary parameter optimization. The proposed scheme also permits extensions to multiple cooperating nodes and sources, and it can be modified to accommodate fairness constraints.

• 한국정보과학회논문지:정보통신
• /
• 제36권3호
• /
• pp.212-221
• /
• 2009

본 논문에서는 GPS가 없는 일반적인 Wireless Sensor Networks(WSNs)상에서 상대적 위치정보를 이용하여 지리적으로 고른 clutter를 구성하고, sensor와 BS사이의 거리를 고려하여 cluster head의 선출빈도를 조절하는 새로운 centralized clustering algorithm "RLCA : Relative Location based Clustering Algorithm for Wireless Sensor Networks"를 제안하고, RLCA의 에너지 소비 효율성이 LEACH에 비해 높다는 것을 실험적으로 보인다.

• 융합경영연구
• /
• 제7권4호
• /
• pp.20-32
• /
• 2019

Purpose - There have been many studies regarding the preceding factors required for success of start-up. The purpose of this study is to verify one of the paths by which the individual characteristics of founders and governmental support lead to enhanced start-up performance, via entrepreneurship and network building. Research design, data, methodology - Data for this study was collected from surveys of 332 founders throughout South Korea, and statistical analyses of this data were performed using SPSS 22.0 and Smart PLS 2.0. To verify our hypothesis, path analysis was performed using a structural equation model. Results -The variables, entrepreneurial self-esteem and experience were found to have positive effects on the entrepreneurship and networks. Secondly, governmental support did not have significant positive effect on entrepreneurship, but it did have positive effect on networking. Thirdly, entrepreneurship and networking were confirmed to have positive effects on both the utilization of opportunities and financial performance, which are variables indicating start-up performance. Conclusion - Although founder's characteristics are important for success of start-up, it is also critically important to actively utilize governmental support. Notably, many founders suffer from inadequate networks. They would be able to enhance their start-up performance by utilizing various governmental support programs to reinforce their network capabilities.

• 전자공학회논문지
• /
• 제49권12호
• /
• pp.20-26
• /
• 2012

인지 기반 융합 중첩 네트워크 환경 하에서의 시스템의 성능이 중요한 이슈로 떠오르는 가운데 단말기의 기능성이 좋아짐에 따라 스마트한 지능을 기반으로 접속 자원의 효과적 활용에 적합한 개별 이종 네트워크의 특성분석과 특성을 반영하는 시스템 측면의 접속 최적화가 매우 중요하다고 할 수 있다. 본 논문에서는 기지국의 소형화와 다집적화, 가상화, 지능화가 진행되는 가운데 기지국 hotelling과 같은 기지국 집중화를 통한 통합적 최적화가 가능하므로 이에 대응한 이중 가상 셀 시스템의 특성에 대해 살펴보고 활용도 측면의 성능을 분석하고 향후 다뤄져야 할 사항들을 확인하였다.

• 인터넷정보학회논문지
• /
• 제22권5호
• /
• pp.27-33
• /
• 2021

With the broad adoption of the Internet of Things (IoT) in a variety of scenarios and application services, management and orchestration entities require upgrading the traditional architecture and develop intelligent models with ultra-reliable methods. In a heterogeneous network environment, mission-critical IoT applications are significant to consider. With erroneous priorities and high failure rates, catastrophic losses in terms of human lives, great business assets, and privacy leakage will occur in emergent scenarios. In this paper, an efficient resource slicing scheme for optimizing federated learning in software-defined IoT (SDIoT) is proposed. The decentralized support vector regression (SVR) based controllers predict the IoT slices via packet inspection data during peak hour central congestion to achieve a time-sensitive condition. In off-peak hour intervals, a centralized deep neural networks (DNN) model is used within computation-intensive aspects on fine-grained slicing and remodified decentralized controller outputs. With known slice and prioritization, federated learning communications iteratively process through the adjusted resources by virtual network functions forwarding graph (VNFFG) descriptor set up in software-defined networking (SDN) and network functions virtualization (NFV) enabled architecture. To demonstrate the theoretical approach, Mininet emulator was conducted to evaluate between reference and proposed schemes by capturing the key Quality of Service (QoS) performance metrics.