• Journal of the Korea Society for Simulation
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• v.9 no.2
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• pp.63-73
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• 2000

Due to the complexity of part flow and limited resources, FMS(Flexible Manufacturing System) develops blocking, starvation and deadlock problems, which reduce its performance. In order to minimize such problems buffers are imposed between workstations of the manufacturing lines. In this paper, we are concerned with finding the optimal buffer allocation with regard to maximizing system throughput in limited total buffer capacity situation of FMS. A dynamic programming algorithm to solve the buffer allocation problem is proposed. Computer simulation using Arena is experimented to show the validation of the proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4680-4697
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• 2017

In future, since the user experience plays a more and more important role in the development of today's communication systems, quality of experience (QoE) becomes a widely used metric, which reflects the subjective experience of end users for wireless service. In addition, the energy efficiency is an increasingly important problem with the explosive growth in the amount of wireless terminals and nodes. Hence, a QoE-aware energy efficiency maximization based joint user access selection and power allocation approach is proposed to solve the problem. We transform the joint allocation process to an optimization of energy efficiency by establishing an energy efficiency model, and then the optimization problem is solved by chaotic clone immune algorithm (CCIA). Numerical simulation results indicate that the proposed algorithm can efficiently and reliably improve the QoE and ensure high energy efficiency of networks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.8A
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• pp.743-751
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• 2010

OFDMA femtocell becomes an effective solution to support indoor high data rate services instead of the macrocell systems. Although the advantage of the femtocell, the co-channel interference between the femocell and the macrocell is the most significant problem that reduces the system performance. Macrocell users who have no permission to access the femtocell suffer from interference of the downlink transmission of femtocell. Therefore, the femtocell should use transmission power as small as possible to reduce interference to macrocell users. In this paper, we define the margin adaptive power allocation problem for the femtocell and propose a heuristic power allocation algorithm to solve the problem. Simulation results show the performance of the proposed algorithm.

• Journal of Communications and Networks
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• v.13 no.4
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• pp.360-366
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• 2011

In this paper, we investigate the problem of power allocation in a heterogeneous network that is composed of a pair of cognitive users (CUs) and an infrastructure-based primary network. Since CUs have only limited effective spectrum-sensing ability and primary users (PUs) are not active all the time in all locations and licensed bands, we set up a new multi-area model to characterize the heterogeneous network. A novel combined interference-avoidance policy corresponding to different PU-appearance situations is introduced to protect the primary network from unacceptable disturbance and to increase the spectrum secondary-reuse efficiency. We use dual decomposition to transform the original power allocation problem into a two-layer optimization problem. We propose a low-complexity joint power-optimizing method to maximize the transmission rate between CUs, taking into account both the individual power-transmission constraints and the combined interference power constraint of the PUs. Numerical results show that for various values of the system parameters, the proposed joint optimization method with combined PU protection is significantly better than the opportunistic spectrum access mode and other heuristic approaches.

• Journal of the Optical Society of Korea
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• v.20 no.6
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• pp.704-715
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• 2016

In this paper, we explore a low-complex bandwidth allocation (BA) scheme with multi-level service guarantees in VLC-OFDM systems. Effective capacity theory, which evaluates wireless channel capacity from a novel view, is utilized to model the system capacity under delay QoS constraints of the link layer. Since intensity modulation of light is used in the system, problems caused by frequency selectivity can be neglected. Then, the BA problem can be formulated as an integer programming problem and it is further relaxed and transformed into a concave one. Lagrangian formulation is used to reformulate the concave problem. Considering the inefficiency of traditional gradient-based schemes and the demand for distributed implementation in local area networks, we localize the global parameters and propose a quasi-distributed quadratic allocation algorithm to provide two-level service guarantees, the first level is QoS oriented, and the second level is QoE oriented. Simulations have shown the efficient performance of the proposed algorithm. The users with more stringent QoS requirements require more subcarriers to guarantee their statistical delay QoS requirements. We also analyze the effect of subcarrier granularity on the aggregate effective capacity via simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5234-5251
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• 2018

It is well-known that virtualization technology can bring many benefits not only to users but also to service providers. From the view of system security and resource utility, higher resource sharing degree and higher system reliability can be obtained by the introduction of virtualization technology in distributed cloud. The small size time-sharing multiplexing technology which is based on virtual machine in distributed cloud platform can enhance the resource utilization effectively by server consolidation. In this paper, the concept of memory block and user satisfaction is redefined combined with user requirements. According to the unbalanced memory resource states and user preference requirements in multi-virtual machine environments, a model of proper memory resource allocation is proposed combined with memory block and user satisfaction, and at the same time a memory optimization allocation algorithm is proposed which is based on virtual memory block, makespan and user satisfaction under the premise of an orderly physical nodes states also. In the algorithm, a memory optimal problem can be transformed into a resource workload balance problem. All the virtual machine tasks are simulated in Cloudsim platform. And the experimental results show that the problem of virtual machine memory resource allocation can be solved flexibly and efficiently.

• Journal of Communications and Networks
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• v.16 no.5
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• pp.559-567
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• 2014

In this paper, a framework for power allocation of downlink transmissions in orthogonal frequency division multiple access-based decode-and-forward cellular relay networks is investigated. We consider a system with a single base station communicating with multiple users assisted by multiple relays. The relays have limited power which must be divided among the users they support in order to maximize the data rate of the whole network. Advanced power allocation schemes are crucial for such networks. The optimal relay power allocation which maximizes the data rate is proposed as an upper bound, by finding the optimal power requirement for each user based on knapsack problem formulation. Then by considering the fairness, a new relay power allocation scheme, called weighted-based scheme, is proposed. Finally, an efficient power reallocation scheme is proposed to efficiently utilize the power and improve the data rate of the network. Simulation results demonstrate that the proposed power allocation schemes can significantly improve the data rate of the network compared to the traditional scheme.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.10
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• pp.60-66
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• 2004

Redundant thrusters are generally adopted to satellite designs for a highly reliable attitude control system. So efficient redundancy management is required to take advantage of these redundant thrusters. In this paper, control allocation method is proposed as a method for controlling redundant thrusters. Control allocation is a method to calculate optimal distribution on redundant controls for realizing desired forces/torques. It is shown that a control allocation problem for redundant thrusters is formulated as a linear programming problem which minimizes fuel consumptions with thrusters, constraints. We also show that the proposed method is more efficient than an existing method by numerical examples.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.11
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• pp.3008-3025
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• 2012

In this paper, the downlink resource allocation of OFDMA system with decode-and-forward (DF) relaying is investigated. A non-convex optimization problem maximizing system throughput with users' satisfaction constraints is formulated with joint relay selection, subcarrier assignment and power allocation. We first transform it to a standard convex problem and then solve it by dual decomposition. In particular, an Optimal resource allocation scheme With Time-sharing (OWT) is proposed with combination of relay selection, subcarrier allocation and power control. Due to its poor adaption to the fast-varying environment, an improved version with subcarrier Monopolization (OWM) is put forward, whose performance promotes about 20% compared with that of OWT in the fast-varying vehicular environment. In fact, OWM is the special case of OWT with binary time-sharing factor and OWT can be seen as the tight upper bound of the OWM. To the best of our knowledge, such algorithms and their relation have not been accurately investigated in cooperative OFDMA networks in the literature. Simulation results show that both the system throughput and the users' satisfaction of the proposed algorithms outperform the traditional ones.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.1972-1986
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• 2017

With the advent of the knowledge economy, science and technology resources have played an important role in economic competition, and their optimal allocation has been regarded as very important across the world. Thus, allocation optimization research for regional science and technology resources is significant for accelerating the reform of regional science and technology systems. Regional science and technology resource allocation optimization is modeled as a double-layer optimization model: the entire system is characterized by top-layer optimization, whereas the subsystems are characterized by bottom-layer optimization. To efficaciously solve this optimization problem, we propose a mixed search method based on the orthogonal genetic algorithm and sensitivity analysis. This novel method adopts the integrated modeling concept with a combination of the knowledge model and heuristic search model, on the basis of the heuristic search model, and simultaneously highlights the effect of the knowledge model. To compare the performance of different methods, five methods and two channels were used to address an application example. Both the optimized results and simulation time of the proposed method outperformed those of the other methods. The application of the proposed method to solve the problem of entire system optimization is feasible, correct, and effective.