• The Journal of Korean Institute of Communications and Information Sciences
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• 제35권5A호
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• pp.447-451
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• 2010

We propose an advanced BMPA (balanced multimedia packet allocation) scheme. The proposed scheme considers the optimal resource allocation problem in OFDMA system. When NRT (non-real time), RT (real time), multicast packets arrive at the same time in OFDMA system, the advanced BMPA chooses the best sub-carrier as a multicast channel for multicast packets, gives more weight to RT packets and multicast packets than NRT packets and allocates sub-carriers according to the total weight sum of packets in each user. With simulation results, this paper shows that the advanced BMPA scheme ensures QoS (long-term system throughput and multimedia packet delay) in heterogeneous traffic compared with multicast MU-WF (multi-user water-filling) and BMPA schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권8호
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• pp.2774-2796
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• 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.

• Journal of Korea Water Resources Association
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• 제42권3호
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• pp.259-270
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• 2009

The applicability of the developed distributed rainfall runoff model using a multi-directional flow allocation algorithm and a real-time updating algorithm was evaluated. The rainfall runoff processes were simulated for the events of the Andong dam basin and the Namgang dam basin using raingauge network data and weather radar rainfall data, respectively. Model parameters of the basins were estimated using previous storm event then those parameters were applied to a current storm event. The physical propriety of the multi-directional flow allocation algorithm for flow routing was validated by presenting the result of flow grouping for the Andong dam basin. Results demonstrated that the developed model has efficiency of simulation time with maintaining accuracy by applying the multi-directional flow allocation algorithm and it can obtain more accurate results by applying the real-time updating algorithm. In this study, we demonstrated the applicability of a distributed rainfall runoff model for the advanced basin-wide flood management.

• Journal of Institute of Control, Robotics and Systems
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• 제3권1호
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• pp.77-88
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• 1997

Fieldbus is the lowest level communication network in factory automation and process control systems. Performance of factory automation and process control systems is directly affected by the data delay induced by network traffic. Data generated from several distributed field devices can be largely divided into three categories: sporadic real-time, periodic real-time and non real-time data. Since these data share one fieldbus network medium, the limited bandwidth of a fieldbus network must be appropriately allocated to the sporadic real-time, periodic real-time and non real-time traffic. This paper introduces a new fieldbus design scheme which allocates the limited bandwidth of fieldbus network to several different kinds of traffic. The design scheme introduced in this study not only satisfies the performance requirements of application systems interconnected into the fieldbus but also fully utilizes the network resources. The design scheme introduced in this study can be applicable to cyclic service protocols operated under single-service discipline. The bandwidth allocation scheme introduced in this study is verified using a discrete-event/continuous-time simulation experiment.

• Proceedings of the KIEE Conference
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.52-55
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• 2004

Digital communication networks have become a core technology in advanced building automation systems. BACnet(${\underline{B}}uilding$ ${\underline{A}}utomation$ and ${\underline{C}}ontrol$ ${\underline{net}}works$) is a standard data communication protocol designed specifically for building automation and control systems. BACnet adopts Master-Slave/Token-Passing (MS/TP) protocol as one of its field level networks. In this study, we introduce a method of implementing bandwidth allocation scheme in the MS/TP protocol. The bandwidth allocation scheme improves the capability of real-time communication of the original MS/TP protocol. The bandwidth allocation scheme introduced in this paper can be easily implemented in the existing MS/TP protocol with a slight modification. In this study, we actually developed the hardware and firmware of MS/TP module in which bandwidth allocation scheme is implemented.

• Journal of Advanced Research in Ocean Engineering
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• 제1권2호
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• pp.94-105
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• 2015

In this study, a thruster allocation method of a deep-sea working vessel was proposed with the aims of producing the demanded generalized forces and moment for dynamic positioning while at the same time minimizing total power. For this, an optimization problem for thrust allocation was mathematically formulated with design variables, objective function, and constraints. The genetic algorithms (GA) was used to solve the formulated problem. The proposed method was applied to an example of finding optimal thrust allocation of the deep-sea working vessel having 5 thrusters. The result showed that the method could be used to determine better strategy for thruster allocation of the vessel as compared to existing study.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 한국경영과학회 2006년도 추계학술대회
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• pp.513-524
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• 2006

The ammunition allocation problem is a Multi-objective optimization(MOO) problem, maximizing fill-rate of multiple user troops and minimizing transportation time. Recent studies attempted to solve this problem by the prior preference articulation approach such as goal programming. They require that all the preference information of decision makers(DM) should be extracted prior to solving the problem. However, the prior preference information is difficult to implement properly in a rapidly changing state of war. Moreover they have some limitations such as heavy cognitive effort required to DM. This paper proposes a new ammunition allocation model based on more reasonable assumptions and uses an interactive MOO method to the ammunition allocation problem to overcome the limitations mentioned above. In particular, this article uses the GDF procedure, one of the well-known interactive optimization methods in the MOO liter-ature, in solving the ammunition allocation problem.

• Journal of Communications and Networks
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• 제16권4호
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• pp.430-435
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• 2014

The performance of a distributed database system depends particularly on the site-allocation of the fragments. Queries access different fragments among the sites, and an originating site exists for each query. A data allocation algorithm should distribute the fragments to minimize the transfer and settlement costs of executing the query plans. The primary cost for a data allocation algorithm is the cost of the data transmission across the network. The data allocation problem in a distributed database is NP-complete, and scalable evolutionary algorithms were developed to minimize the execution costs of the query plans. In this paper, quadratic assignment problem heuristics were designed and implemented for the data allocation problem. The proposed algorithms find near-optimal solutions for the data allocation problem. In addition to the fast ant colony, robust tabu search, and genetic algorithm solutions to this problem, we propose a fast and scalable hybrid genetic multi-start tabu search algorithm that outperforms the other well-known heuristics in terms of execution time and solution quality.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제32권12A호
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• pp.1276-1285
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• 2007

Since the TD-SCDMA (Time Division-Synchronous Code Division Multiple Access) system is based on TDD (Time Division Duplexing), the uplink and downlink can be allocated asymmetrically according to the traffic e.g. Web browsing. Although this asymmetric allocation can increase the frequency utilization, it may cause time slot opposing, which implies the time slot is assigned in opposing direction between cells. The time slot opposing can generate significant interference between cells, which results in severe performance degradation. In the paper, a novel dynamic channel allocation (DCA) is proposed in the TD-SCDMA system, to mitigate the impact of time slot opposing considering smart antenna. When the smart antenna is applied in the system, the inter-cell interference is largely affected by beam pattern and beam direction between neighboring cells. Therefore, the time slot opposing and smart antenna should be considered together in the DCA. The intensive simulations show that the proposed scheme can improve the system capacity compared to the conventional DCA schemes.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제20권7호
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• pp.1255-1261
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• 2016

Recently, the energy harvesting technology in which energy is collected from the wireless signal which is transmitted by mobile communication devices, has been considered as a novel way to improve the life time of wireless sensors by mitigating the lack of power supply problem. In this paper, we consider the optimal sensing time and power allocation problem for cognitive radio systems, where the energy efficiency of secondary user is maximized while the constraint are satisfied, using the optimization technique. Based on the derived optimal solutions, we also have proposed an iterative resource allocation algorithm in which the optimal power and sensing time allocation can be found without excessive computations. The simulation results confirm that the proposed scheme achieves the optimal performance and it outperforms the conventional resource allocation schemes in terms of energy efficiency while the constraints are guaranteed to be satisfied.