• Journal of information and communication convergence engineering
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• 제8권3호
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• pp.277-280
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• 2010

We report that broadcast messages in Mobile WiMAX networks should be synchronized throughout all the base stations to gain the benefit of beamforming technique. A simple synchronization implementation of broadcast messages in Mobile WiMAX networks is presented. Using this technique, the interference between broadcast messages and beamformed messages can be reduced.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(3)
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• pp.67-70
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• 2002

본 논문은 IIPv6 기반의 Mobile Ad-hoc Networks 환경에서 화상회의 도구 같은 멀티캐스트 응용을 서비스하는데 이용될 수 있는 IPv6 기반의 자동네트워킹 기술을 제시한다. IPv6 유니캐스트 자동설정 기능을 이용하여 이동단말의 유니캐스트 주소를 자동으로 설정할 수 있고, 멀티캐스트 자동설정 기능을 이용하여 멀티캐스트 주소 할당을 필요로 하는 응용에게 멀티캐스트 주소를 쉽게 할당할 수 있으므로 Mobile Ad-hoc Networks 환경에서의 사용자는 이러한 자동네트워킹 기술을 통해 멀티 캐스트 서비스를 쉽게 이용할 수 있다.

• Journal of Information Processing Systems
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• 제16권4호
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• pp.743-749
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• 2020

Internet of Things (IoT) is a growing technology along with artificial intelligence (AI) technology. Recently, increasing cases of developing knowledge services using information collected from sensor data have been reported. Communication is required to connect the IoT and AI, and 5G mobile networks have been widely spread recently. IoT, AI services, and 5G mobile networks can be configured and used as sensor-mobile edge-server. The sensor does not send data directly to the server. Instead, the sensor sends data to the mobile edge for quick processing. Subsequently, mobile edge enables the immediate processing of data based on AI technology or by sending data to the server for processing. 5G mobile network technology is used for this data transmission. Therefore, this study examines the challenges, opportunities, and solutions used in each type of technology. To this end, this study addresses clustering, Hyperledger Fabric, data, security, machine vision, convolutional neural network, IoT technology, and resource management of 5G mobile networks.

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

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권10호
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• pp.2395-2410
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• 2013

Many telecommunication operators around the world have multiple networks. The networks run by each operator are always of different generations, such as 2G and 3G or even 4G systems. Each system has unique characters and specified requirements for optimal operation. It brings about resource allocation problem among these networks for the operator, because the budget of each operator is limited. However, the evaluation of resource allocation among various networks under each operator is missing for long, not to mention resource allocation optimization. The operators are dying for an algorithm to end their blind resource allocation, and the Resource Allocation Optimization Algorithm for Multi-network Operator (RAOAMO) proposed in this paper is what the operators want. RAOAMO evaluates and optimizes resource allocation in the view of overall cost for each operator. It outputs a resource distribution target and corresponding optimization suggestion. Evaluation results show that RAOAMO helps operator save overall cost in various cases.

• 한국정보통신학회논문지
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• 제14권2호
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• pp.329-334
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• 2010

무선 이동 통신망의 발전으로 단말의 현재 위치를 기반으로 한 다양한 위치 기반 서비스가 출현하고 있다. 와이브로 망과 같은 모바일 와이맥스 망에서도 LBS (Location Based Service) 서비스의 제공은 망 기술의 경쟁력을 제고하기 위해 매우 중요하다. 이를 위해, 와이맥스 포럼은 최근 LBS 서비스 제공을 위한 망 구조 및 프로토콜을 네트워크 워킹 그룹의 release 1.5 문서에 포함하여 표준화 하였다. 그동안 와이브로 망에서 측위에 관한 많은 연구가 있어 왔지만, 최근 확립된 와이맥스 포럼의 LBS 표준을 고려하여 표준에 적합한 위치 결정 방식에 관한 연구는 아직 없다. 본 논문에서는 와이맥스 포럼의 LBS 표준을 고려하여, 이에 부합하는 위치 결정 방식을 제안한다. 이 방식은, RTD (Round Trip Delay) 방식을 결합하여 기존 TDOA 방식을 개선하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권3호
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• pp.1321-1332
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• 2016

Wireless sensor networks (WSN) are self-organized networks that typically consist of thousands of low-cost, low-powered sensor nodes. The reliability and availability of WSNs can be affected by faults, including those from radio interference, battery exhaustion, hardware and software failures, communication link errors, malicious attacks, and so on. Thus, we propose a novel multi-agent fault tolerant system for wireless sensor networks. Since a major requirement of WSNs is to reduce energy consumption, we use multi-agent and mobile agent configurations to manage WSNs that provide energy-efficient services. Mobile agent architecture have inherent advantages in that they provide energy awareness, scalability, reliability, and extensibility. Our multi-agent system consists of a resource manager, a fault tolerance manager and a load balancing manager, and we also propose fault-tolerant protocols that use multi-agent and mobile agent setups.

• Journal of Ubiquitous Convergence Technology
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• 제1권1호
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• pp.35-41
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• 2007

In mobile ad-hoc wireless networks, one of the most important challenging issues is how to conserve energy, maximizing the lifetime of route(networks) in the view points of both power and mobility of nodes. However, many transmission methods presented in the previous works can not satisfy these two objectives simultaneously. To obtain these two goals, in this paper we propose an architecture to support power saving transmission services with route stability in mobile ad-hoc wireless networks. The proposed architecture consists of two parts, the underlying route stability method to support route(network) lifetime and the power saving transmission methods. The performance evaluation of the proposed architecture is achieved via simulation and analysis.

• Journal of Communications and Networks
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• 제6권2호
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• pp.156-162
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• 2004

In recent years, mobile ad-hoc networks have received a great deal of attention in both academia and industry to provide anytime-anywhere networking services. As wireless networks are rapidly deployed, the security of wireless environment will be mandatory. In this paper, we describe a group key management architecture and key agreement protocols for secure communication in mobile ad-hoc wireless networks (MANETs) overseen by unmanned aerial vehicles (UAVs). We use implicitly certified public keys method, which alleviates the certificate overhead and improves computational efficiency. The architecture uses a two-layered key management approach where the group of nodes is divided into: 1) Cell groups consisting of ground nodes and 2) control groups consisting of cell group managers. The chief benefit of this approach is that the effects of a membership change are restricted to the single cell group.

• ETRI Journal
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• 제44권6호
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• pp.915-924
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• 2022

In this paper, we present a two-stage scalable channel estimator (TSCE), a deep learning (DL)-based scalable, and robust channel estimator for wireless cellular networks, which is made up of two DL networks to efficiently support different resource allocation sizes and reference signal configurations. Both networks use the transformer, one of cutting-edge neural network architecture, as a backbone for accurate estimation. For computation-efficient global feature extractions, we propose using window and window averaging-based self-attentions. Our results show that TSCE learns wireless propagation channels correctly and outperforms both traditional estimators and baseline DL-based estimators. Additionally, scalability and robustness evaluations are performed, revealing that TSCE is more robust in various environments than the baseline DL-based estimators.