• Journal of Communications and Networks
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• 제18권1호
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• pp.112-122
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• 2016

Cognitive radio (CR) is considered an attractive technology to deal with the spectrum scarcity problem. Multi-radio access technology (multi-RAT) can improve network capacity because data are transmitted by multiple RANs (radio access networks) concurrently. Thus, multi-RAT embedded in a cognitive radio network (CRN) is a promising paradigm for developing spectrum efficiency and network capacity in future wireless networks. In this study, we consider a new CRN model in which the primary user networks consist of heterogeneous primary users (PUs). Specifically, we focus on the energy-efficient resource allocation (EERA) problem for CR users with a special location coverage overlapping region in which heterogeneous PUs operate simultaneously via multi-RAT. We propose a two-tier crossover genetic algorithm-based search scheme to obtain an optimal solution in terms of the power and bandwidth. In addition, we introduce a radio environment map to manage the resource allocation and network synchronization. The simulation results show the proposed algorithm is stable and has faster convergence. Our proposal can significantly increase the energy efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권5호
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• pp.2243-2257
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• 2019

A heterogeneous cellular network (HCN) is useful to increase the spectral and energy efficiency of wireless networks and to reduce the traffic load from the macro cell. The performance of the secondary user equipment (SUE) is affected by interference from the eNodeB (eNB) in a macro cell. To decrease the interference between the macro cell and the small cell, allocating resources properly is essential to an HCN. This study considers the scenario of a software-defined heterogeneous cellular network and performs the resource allocation process. First, we show the system model of HCN and formulate the optimization problem. The optimization problem is a complex process including power and frequency resource allocation, which imposes an extremely high complexity to the HCN. Therefore, a hierarchical resource allocation scheme is proposed, which including subchannel selection and a particle swarm optimization (PSO)-based power allocation algorithm. Simulation results show that the proposed hierarchical scheme is effective in improving the system capacity and energy efficiency.

• 디지털산업정보학회논문지
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• 제4권1호
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• pp.33-40
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• 2008

This paper presents a new scheduling scheme in wireless distributed network. To overcome the limited information about unfamiliar mobile nodes and to reduce the required system performance, we propose a scheduling algorithm of job allocation based on the trust model. The suggested scheduler evaluate an unfamiliar mobile node's trust and make reference to the trust value of neighboring scheduler. This scheduling algorithm can avoid malicious or selfish mobile nodes by assigning low trust values. We also present a trust evaluation metric and show the efficiency of suggested scheduling algorithm by performance evaluation.

• Management Science and Financial Engineering
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• 제16권1호
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• pp.59-79
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• 2010

This paper considers bandwidth allocation and scheduling problems on Ethernet Passive Optical Networks (EPON). EPON is one of the good candidates for the optical access network. This paper formulates the bandwidth allocation problem as a nonlinear mathematical one and characterizes the optimal bandwidth allocation which maximizes weighted sum of throughput and fairness. Based upon the characterization, two heuristic algorithms are suggested with various numerical tests. The test results show that our algorithms can be used for efficient bandwidth allocation on the EPON. This paper also shows that the WSPT (Weighted Shortest Processing Time) rule is optimal for minimization the total delay time in transmitting the traffic of the given allocated bandwidth.

• 한국멀티미디어학회논문지
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• 제10권12호
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• pp.1645-1654
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• 2007

In this paper, we study the problem of load balancing routing in clustered-based wireless mesh network in order to enhance the overall network throughput. We first address the problems of cluster allocation in wireless mesh network to achieve load-balancing state. Due to the complexity of the problem, we proposed a simplified algorithm using gradient load-balancing model. This method searches for a localized optimal solution of cluster allocation instead of solving the optimal solution for overall network. To support for load-balancing algorithm and reduce complexity of topology control, we also introduce limited broadcasting between two clusters. This mechanism maintain shortest path between two nodes in adjacent clusters while minimizing the topology broadcasting complexity. The simulation experiments demonstrate that our proposed model achieve performance improvement in terms of network throughput in comparison with other clustering methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권5호
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• pp.1984-2002
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• 2020

With the appearance of wireless spectrum crisis in traditional cellular network, device-to-device (D2D) communication has been regarded as a promising solution to ease heavy traffic burden by enabling precise content delivery among mobile users. However, due to the channel sharing, the interference between D2D and cellular users can affect the transmission rate and narrow the throughput in the network. In this paper, we firstly present a weighted interference minimization cluster formation model involving both social attribute and physical closeness. The weighted-interference, which is evaluated under the susceptible-infected(SI) model, is utilized to gather user in social and physical proximity. Then, we address the cluster formation problem via spectrum clustering with iterative operation. Finally, we propose the stable matching theory algorithm in order to maximize rate oriented to accomplish the one-to-one resource allocation. Numerical results show that our proposed scheme acquires quite well clustering effect and increases the accumulative transmission rate compared with the other two advanced schemes.

• Journal of Information Processing Systems
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• 제17권4호
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• pp.721-736
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• 2021

For the mobile edge computing (MEC) system supporting dense network, a joint allocation algorithm of computing and communication resources based on reinforcement learning is proposed. The energy consumption of task execution is defined as the maximum energy consumption of each user's task execution in the system. Considering the constraints of task unloading, power allocation, transmission rate and calculation resource allocation, the problem of joint task unloading and resource allocation is modeled as a problem of maximum task execution energy consumption minimization. As a mixed integer nonlinear programming problem, it is difficult to be directly solve by traditional optimization methods. This paper uses reinforcement learning algorithm to solve this problem. Then, the Markov decision-making process and the theoretical basis of reinforcement learning are introduced to provide a theoretical basis for the algorithm simulation experiment. Based on the algorithm of reinforcement learning and joint allocation of communication resources, the joint optimization of data task unloading and power control strategy is carried out for each terminal device, and the local computing model and task unloading model are built. The simulation results show that the total task computation cost of the proposed algorithm is 5%-10% less than that of the two comparison algorithms under the same task input. At the same time, the total task computation cost of the proposed algorithm is more than 5% less than that of the two new comparison algorithms.

• ETRI Journal
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• 제43권4호
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• pp.758-768
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• 2021

In this work, the secrecy of a typical wireless cooperative dual-hop non-orthogonal multiple access (NOMA)-enabled decode-and-forward (DF) relay network is investigated with the impact of collaborative and non-collaborative eavesdropping. The system model consists of a source that broadcasts the multiplexed signal to two NOMA users via a DF relay, and information security against the eavesdropper nodes is provided by a helpful jammer. The performance metric is secrecy rate and ergodic secrecy capacity is approximated analytically. In addition, a differential evolution algorithm-based power allocation scheme is proposed to find the optimal power allocation factors for relay, jammer, and NOMA users by employing different jamming schemes. Furthermore, the secrecy rate analysis is validated at the NOMA users by adopting different jamming schemes such as without jamming (WJ) or conventional relaying, jamming (J), and with control jamming (CJ). Simulation results demonstrate the superiority of CJ over the J and WJ schemes. Finally, the proposed power allocation outperforms the fixed power allocation under all conditions considered in this work.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권9호
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• pp.2573-2589
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• 2023

As 5G mobile systems carry multiple services and applications, numerous user, and application types with varying quality of service requirements inside a single physical network infrastructure are the primary problem in constructing 5G networks. Radio Access Network (RAN) slicing is introduced as a way to solve these challenges. This research focuses on optimizing RAN slices within a singular physical cell for vehicle-to-everything (V2X) and enhanced mobile broadband (eMBB) UEs, highlighting the importance of adept resource management and allocation for the evolving landscape of 5G services. We put forth two unique strategies: one being offline network slicing, also referred to as standard network slicing, and the other being Online reinforcement learning (RL) network slicing. Both strategies aim to maximize network efficiency by gathering network model characteristics and augmenting radio resources for eMBB and V2X UEs. When compared to traditional network slicing, RL network slicing shows greater performance in the allocation and utilization of UE resources. These steps are taken to adapt to fluctuating traffic loads using RL strategies, with the ultimate objective of bolstering the efficiency of generic 5G services.

• 대한산업공학회지
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• 제24권2호
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• pp.241-249
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• 1998

In this paper, we seek to find an optimal allocation of link capacity in a data communication network. The architecture of the data communication network considered in the study is an online-service network based on public switched telephone network(PSTN) and packet switched data network(PSDN). In designing the architecture of the network, we need to deal with various measures of quality of service(QoS). Two important service measures are the call blocking probability in PSTN and the data transfer delay time in PSDN. Considering the tradeoff between the call blocking probability and the data transfer delay time in the network, we have developed the optimal link capacity allocation model that minimizes the total link cost, while guarantees the call blocking probability and the data transfer delay time within an acceptable level of QoS. This problem can be formulated as a non-linear integer programming model. We have solved the problem with tabu search and simulated annealing methods. In addition, we have analyzed the sensitivity of the model and provided the insight of the model along with computational results.