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

• Proceedings of the KIEE Conference
• /
• 1996.07b
• /
• pp.878-882
• /
• 1996

This paper discusses the definition and concepts, approach methodologies, capable application areas in electricity business, and tentative calculation of avoided generation costs based on the Korea's official long-term generation expansion plan. The objective to evaluate avoided costs of a resource is to supply decision makers with the breakeven cost of a targeting avoided resource. For the evaluation of avoided costs of the Korea's generation system, we consider the pseudo-DSM option which has 1,000MW peak savings, load factor with 70 percent, and life-time With 25 years as the avoided resource. The DSM resource can save the fuel and capacity additions of a electric utility during its life time. The capacity and fuel savings are evaluated from the two different cashflows with and Without the DSM option, which are generated on the basis of the generation system optimization model(WASP-II), independently. The breakeven kWh costs of the DSM option over this 25-year period is projected to be 34.1[won/kWh], which is composed of generation-capacity and fuel avoided costs with 101.139[won/kW] and 17.6[won/kWh], respectively.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.10
• /
• pp.2382-2388
• /
• 2014

To provide network reliability in indoor wireless communication systems, we should resolve the problem of unexpected network failure rapidly. In this paper, we propose an adaptive resource management (ARM) scheme to support seamless connectivity to users. In consideration of system throughput and user fairness simultaneously, the ARM scheme adaptively determines the set of healing channels, and performs scheduling and power allocation iteratively based on a constrained non-convex optimization technique. Through intensive simulations, we demonstrate the superior performance results of the proposed ARM scheme in terms of the average cell capacity and user fairness.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.8
• /
• pp.2774-2796
• /
• 2015

Quality-of-service (QoS) provisioning for a cognitive mesh network (CMN) with heterogeneous services has become a challenging area of research in recent days. Considering both real-time (RT) and non-real-time (NRT) traffic in a multihop CMN, [1] studied cross-layer resource management, including joint access control, route selection, and resource allocation. Due to the complexity of the formulated resource allocation problems, which are mixed-integer non-linear programming, a low-complexity yet efficient algorithm was proposed there to approximately solve the formulated optimization problems. In contrast, in this work, we present an application of genetic algorithm (GA) to re-address the hard resource allocation problems studied in [1]. Novel initialization, selection, crossover, and mutation operations are designed such that solutions with enough randomness can be generated and converge with as less number of attempts as possible, thus improving the efficiency of the algorithm effectively. Simulation results show the effectiveness of the newly proposed GA-based algorithm. Furthermore, by comparing the performance of the newly proposed algorithm with the one proposed in [1], more insights have been obtained in terms of the tradeoff among QoS provisioning for RT traffic, throughput maximization for NRT traffic, and time complexity of an algorithm for resource allocation in a multihop network such as CMN.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.10
• /
• pp.1986-1993
• /
• 2015

We investigate the optimal resource and power allocation for device-to-device (D2D) communications in a multicell environment. When D2D links reuse the cellular radio resources, each D2D user will interfere with a cellular link and other D2D links, in its own cell as well as in adjacent cells. Under such situation, we propose a coordinated resource allocation scheme that can handle the intercell interferences as well as the intracell interference. For a given resource allocation, we also formulate a power optimization problem and present an algorithm for finding the optimal solution. The resource and power allocation algorithms are designed to maximize the achievable rate of the D2D link, while limiting the generated interference to the cellular link. The performance of the proposed algorithms is evaluated through simulations in a multicell environment. Numerical results are presented to verify the coordination gain in the resource and power allocation.

• Journal of the Korea Society of Computer and Information
• /
• v.15 no.6
• /
• pp.49-56
• /
• 2010

In this paper, a joint PHY-MAC layer optimized resource allocation scheme for OFDMA based micro base stations is investigated. We propose cross-layer optimized two-stage resource allocation scheme including cross-layer functional description and control information flow between PHY-MAC layers. The proposed two-stage resource allocation scheme consists of a user grouping stage and a resource allocation stage. In the user grouping stage, users are divided into a macro base station user group and a micro base station user group based on the PHY-MAC layer characteristics of each user. In the resource allocation stage, a scheduling scheme and an allotment of resources are determined. In the proposed scheme, diversity and adaptive modulation and coding (AMC) schemes are exploited as schedulers. Simulation results demonstrate that the proposed scheme increases the average cell throughput about 40~80 % compared to the conventional system without micro base stations.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2006.05a
• /
• pp.373-378
• /
• 2006

Recently the technical advances and complexities have generated much of the difficulties in managing the project resources, for both scheduling and costing to accomplish the project in the most efficient manner. The project manager is frequently required to render judgments concerning the schedule and resource adjustments. This research develops an analytical model for a schedule-cost and risk analysis based on visual PERT/CPM. We used a three-step approach: 1) in the first step, a deterministic PERT/CPM model for the critical path and estimating the project time schedule and related resource planning and we developed a heuristic model for crash and stretch out analysis based upon a time-cost trade-off associated with the crash and stretch out of the project. 2) In second step, we developed web-based risk evaluation model for project analysis. Major technologies used for this step are AHP (analytic hierarchy process, fuzzy-AHP, multi-attribute analysis, stochastic network simulation, and web based decision support system. Also we have developed computer programs and have shown the results of sample runs for an R&D project risk analysis. 3) We developed an optimization model for project resource allocation. We used AHP weighted values and optimization methods. Computer implementation for this model is provided based on GUI-Type objective-oriented programming for the users and provided displays of all the inputs and outputs in the form of GUI-Type. The results of this research will provide the project managers with efficient management tools.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2019.05a
• /
• pp.186-189
• /
• 2019

The technique named CORD is an algorithm that optimizes resources of Data Service Platform(DSP) in real time, and it has been developed for enhancing operability of DSP of Korean e-Navigation Project performed by Hanwha Systems and Ministry of Oceans and Fisheries(MOF) since 2016. It plays a critical role to recognize the state of DSP in early time and handling problems immediately when it occurs logical, physical error in order to make DSP steady state condition, which has something in common with maximizing operability of DSP and seamless maritime service to various ships in the sea. Therefore, as developing a noble technique that makes DSP steady state by diagnosing resource and operation status of DSP as well as by reconfiguring service queue optimally in real time, DSP can have shorter response time and higher chance of providing proper maritime service to ships in voyage.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.3
• /
• pp.1325-1344
• /
• 2019

Recently, to satisfy mobile users' increasing data transmission requirement, energy efficiency (EE) resource allocation in distributed antenna systems (DASs) has become a hot topic. In this paper, we aim to maximize EE in DASs subject to constraints of the minimum data rate requirement and the maximum transmission power of distributed antenna units (DAUs) with different density distributions. Virtual cell is defined as DAUs selected by the same user equipment (UE) and the size of virtual cells is dependent on the number of subcarriers and the transmission power. Specifically, the selection rule of DAUs is depended on different scenarios. We develop two scenarios based on the density of DAUs, namely, the sparse scenario and the dense scenario. In the sparse scenario, each DAU can only be selected by one UE to avoid co-channel interference. In order to make the original non-convex optimization problem tractable, we transform it into an equivalent fractional programming and solve by the following two sub-problems: optimal subcarrier allocation to find suitable DAUs; optimal power allocation for each subcarrier. Moreover, in the dense scenario, we consider UEs could access the same channel and generate co-channel interference. The optimization problem could be transformed into a convex form based on interference upper bound and fractional programming. In addition, an energy-efficient DAU selection scheme based on the large scale fading is developed to maximize EE. Finally, simulation results demonstrate the effectiveness of the proposed algorithm for both sparse and dense scenarios.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.7
• /
• pp.2496-2512
• /
• 2021

The requirements for powerful computing capability, high capacity, low latency and low energy consumption of emerging services, pose severe challenges to the fifth-generation (5G) network. As a promising paradigm, mobile edge networks can provide services in proximity to users by deploying computing components and cache at the edge, which can effectively decrease service delay. However, the coexistence of heterogeneous services and the sharing of limited resources lead to the competition between various services for multiple resources. This paper considers two typical heterogeneous services: computing services and content delivery services, in order to properly configure resources, it is crucial to develop an effective offloading and caching strategies. Considering the high energy consumption of 5G base stations, this paper considers the hybrid energy supply model of traditional power grid and green energy. Therefore, it is necessary to design a reasonable association mechanism which can allocate more service load to base stations rich in green energy to improve the utilization of green energy. This paper formed the joint optimization problem of computing offloading, caching and resource allocation for heterogeneous services with the objective of minimizing the on-grid power consumption under the constraints of limited resources and QoS guarantee. Since the joint optimization problem is a mixed integer nonlinear programming problem that is impossible to solve, this paper uses deep reinforcement learning method to learn the optimal strategy through a lot of training. Extensive simulation experiments show that compared with other schemes, the proposed scheme can allocate resources to heterogeneous service according to the green energy distribution which can effectively reduce the traditional energy consumption.