• ETRI Journal
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• v.36 no.5
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• pp.808-818
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• 2014

To deal with the major challenges of embedded sensor networks, we consider the use of magnetic fields as a means of reliably transferring both information and power to embedded sensors. We focus on a power allocation strategy for an orthogonal frequency-division multiplexing system to maximize the transferred power under the required information capacity and total available power constraints. First, we consider the case of a co-receiver, where information and power can be extracted from the same signal. In this case, we find an optimal power allocation (OPA) and provide the upper bound of achievable transferred power and capacity pairs. However, the exact calculation of the OPA is computationally complex. Thus, we propose a low-complexity power reallocation algorithm. For practical consideration, we consider the case of a separated receiver (where information and power are transferred separately through different resources) and propose two heuristic power allocation algorithms. Through simulations using the Agilent Advanced Design System and Ansoft High Frequency Structure Simulator, we validate the magnetic-inductive channel characteristic. In addition, we show the performances of the proposed algorithms by providing achievable ${\eta}$-C regions.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.140-146
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• 2023

Resource allocation is one of the top challenges in Internet of Things (IoT) networks. This is due to the scarcity of computing, energy and communication resources in IoT devices. As a result, IoT devices that are not using efficient algorithms for resource allocation may cause applications to fail and devices to get shut down. Owing to this challenge, this paper proposes a novel algorithm for managing computing resources in IoT network. The fog computing devices are placed near the network edge and IoT devices send their large tasks to them for computing. The goal of the algorithm is to conserve energy of both IoT nodes and the fog nodes such that all tasks are computed within a deadline. A bi-partite graph-based algorithm is proposed for stable matching of tasks and fog node computing units. The output of the algorithm is a stable mapping between the IoT tasks and fog computing units. Simulation results are conducted to evaluate the performance of the proposed algorithm which proves the improvement in terms of energy efficiency and task delay.

• Journal of KIISE:Software and Applications
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• v.41 no.8
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• pp.569-579
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• 2014

In a tactical-edge environment, where multiple weapon resources are coordinated together via services, it is essential to make an efficient binding between an abstract service and a resource that are needed to execute composite services for accomplishing a given mission. However, the tactical network that is used in military operation has low bandwidth and a high rate of packet loss. Therefore, communication overhead between services must be minimized to execute composite services in a stable manner in the tactical network. In addition, a tactical-edge environment changes dynamically, and it affects the connectivity and bandwidth of the tactical network. To deal with these characteristics of the tactical network we propose two service-resource reallocation methods which minimize the communication overhead between service gateways and effectively manage neutralization of gateways during distributed service coordination. We compared the effectiveness of these two - methods in terms of total communication overhead between service gateways and resource-allocation similarity between the initial resource allocation and the reallocation result.

• Journal of Advanced Navigation Technology
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• v.19 no.4
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• pp.318-322
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• 2015

In wireless communication networks, most of the prediction techniques are used for predicting the amount of resource required by user's calls for improving their demanding quality of service. However, we propose a channel allocation scheme based on predicting the resources of white spectrum holes for improving the QoS of rental user's spectrum handoff calls for cognitive radio networks in this paper. This method is supported by Wiener predictor to predict the amount of white spectrum holes of license user's free spectrum resources. We classify rental user's calls into initial calls and spectrum handoff calls, and some portion of predicted spectrum-hole resources is reserved for spectrum handoff calls' priority allocation. Simulations show that the performance of the proposed scheme outperforms in spectrum handoff call's dropping rate than an existing method without spectrum hole prediction(11% average improvement in 50% reservation).

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.1
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• pp.5-10
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• 2015

D2D (Device-to-Device) communication underlaying LTE-advanced networks is a promising technology to improve the system capacity and spectral efficiency. By sharing the same radio resources with cellular user equipments, D2D communications can significantly enhance the overall spectral efficiency. However, it may cause interference between D2D link and cellular link. Careful resource allocation and interference coordination between cellular and D2D communications are very important and need to be properly handled. This paper proposes a radio resource allocation scheme based on FFFR (Flexible Fractional Frequency Reuse) for D2D communication underlaying cellular networks. The base station selects randomly resource blocks assigned to cellular users, and reuses them for a D2D pair. Through simulations, we have confirmed that the proposed scheme improves the system throughput, reduces the computational complexity, and mitigates the interference of D2D link and cellular link.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1311-1324
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• 2019

In the traditional cellular network communication, the cellular user and the base station exchange information through the uplink channel and downlink channel. Meanwhile, device-to-device (D2D) users access the cellular network by reusing the channel resources of the cellular users. However, when cellular user channel conditions are poor, not only D2D user cannot reuse its channel resources to access the network, but also cellular user's communication needs cannot be met. To solve this problem, we introduced a novelty D2D communication mechanism in the downlink, which D2D transmitter users as half-duplex (HD) relays to assist the downlink transmission of cellular users with reusing corresponding spectrum. The optimization goal of the system is to make the cellular users in the bad channel state meet the minimum transmission rate requirement and at the same time maximize the throughput of the D2D users. In addition, i for the purpose of improving the efficiency of relay transmission, we use two-antenna architecture of D2D relay to enable receive and transmit signals at the same time. Then we optimized power of base station and D2D relay separately with consideration of backhaul interference caused by two-antenna architectures. The simulation results show that the proposed HD relay strategyis superior to existing HD and full-duplex (FD) models in the aspects of system throughput and power efficiency.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.5
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• pp.1146-1154
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• 2010

A virtual machine lease service in the cloud computing environment has been implemented using the open source cloud computing platform, OpenNebula. In addition, a web-based cloud user interface is developed for both convenient resource management and efficient service access. The present virtual machine allocation scheme adopted in OpenNebula has performance reduction problem because of not considering CPU allocation scheduler of the virtualization software. In order to address this problem we have considered both the priority of the idle CPU resources of the cluster and credit scheduler of Xen, which resulted in performance improvement of the OpenNebula virtual machine scheduler. The experimental results showed that the proposed allocation scheme provided more virtual machine creations and more CPU resource allocations for cloud service.

• ETRI Journal
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• v.36 no.5
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• pp.741-751
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• 2014

Smart TV is expected to bring cloud services based on virtualization technologies to the home environment with hardware and software support. Although most physical resources can be shared among virtual machines (VMs) using a time sharing approach, allocating the proper amount of memory to VMs is still challenging. In this paper, we propose a novel mechanism to dynamically balance the memory allocation among VMs in virtualized Smart TV systems. In contrast to previous studies, where a virtual machine monitor (VMM) is solely responsible for estimating the working set size, our mechanism is symbiotic. Each VM periodically reports its memory usage pattern to the VMM. The VMM then predicts the future memory demand of each VM and rebalances the memory allocation among the VMs when necessary. Experimental results show that our mechanism improves performance by up to 18.28 times and reduces expensive memory swapping by up to 99.73% with negligible overheads (0.05% on average).

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.211-223
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• 2018

Mobile relay systems have been adopted by $4^{th}$ generation mobile systems as an alternative method to extend cell coverage as well as to enhance the system throughput at cell-edges. In order to achieve such performance gains, the mobile relay systems require path selection and resource allocation schemes that are specifically designed for these systems which make use of additional radio resources not needed in single-hop systems. This paper proposes an integrated path selection and resource allocation scheme for LTE-Advanced relay systems using collaborative communication. We first define the problem of maximizing the downlink throughput of LTE-Advanced relay systems using collaborative communication and transform it into a multi-dimensional multi-choice backpacking problem. The proposed Lagrange multiplier-based heuristic algorithm is then applied to derive the approximate solution to the maximization problem. It is shown through simulations that the approximate solution obtained by the proposed scheme can achieve a near-optimal performance.

• Journal of the Korea Institute of Building Construction
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• v.8 no.5
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• pp.67-73
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• 2008

Recent trends in construction towards larger scale and taller buildings are causing problems by ineffective existing management approach in construction industry have emerged. Delivering necessary materials and mobilizing the human resources and equipment In a timely manner to keep labor on schedule have become a critical issue to be addressed. In particular, many specialty contractors carrying out multiple projects have been experiencing difficulties mobilizing the manpower on time and in right places due to poor communication at each stage of labor supply, resulting in waste of valuable resources. Hence, it's imperative for the specialty contractors to obtain specific information on labor demand so as to set up a communication and labor management system to ensure the right human resources will be mobilized in the right place at the right time. The study therefore is aimed at developing an optimal human resources management system for specialty contractors performing multiple projects. To that end, the study is focused on rebar and concrete work. The outcome of the study is expected to help allocate the right human resources to the right place in a timely fashion, thereby achieving an effective workflow at construction sites.