• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5455-5475
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• 2016

In this article, we model the distributed relay assignment network as a many-to-one matching market with peer effects. We discuss two scenarios for throughput optimization of relay networks: the scenario of aggregate throughput optimization and the scenario of fairness performance optimization. For the first scenario, we propose a Mutual Benefit-based Deferred Acceptance (MBDA) algorithm to increase the aggregate network throughput. For the second scenario, instead of using the alternative matching scheme, a non-substitution matching algorithm (NSA) is designed to solve the fairness problem. The NSA improves the fairness performance. We prove that both two algorithms converge to a globally stable matching, and discuss the practical implementation. Simulation results show that the performance of MBDA algorithm outperforms existing schemes and is almost the same with the optimal solution in terms of aggregate throughput. Meanwhile, the proposed NSA improves fairness as the scale of the relay network expands.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.12A
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• pp.1367-1374
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• 2004

Efforts for standardization of medium access control (MAC) protocol in IEEE802.11e have been made to support quality of service (QoS) in IEEE802.11 MAC protocol. Enhanced distributed coordination function (EDCF) of 802.11e MAC protocol is modified to support QoS for packets that have differentiated priority. However, EDCF still has e problem of throughput optimization and priority support. Therefore, we have proposed a scheme called adaptive EDCF for both supporting priority of packets and throughput optimization. We have derived the relation between the number of nodes and contention window size for throughput optimization. Based on the analytic results, we have evaluated the performance of the proposed scheme using OPNET simulations. The simulation results show that using the proposed scheme can Improve the overall throughput regardless of the number of nodes and the decrement of the throughput with increasing the number of nodes can be alleviated. Additionally, we have shown that the adaptive EDCF can support priority of packets more effectively than existing EDCF.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.1A
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• pp.62-69
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• 2005

Efforts for standardization of medium access control (MAC) protocol in IEEE802.11e have been made to support quality of service (QoS) in IEEE802.11e MAC protocol. Enhanced disoibuted coordination function (EDCF) of 802.11e MAC protocol is modified to support QoS for packets that have differentiated priority. However, EDCF still has the problem of throughput optimization and priority support. Therefore, we have proposed a scheme called adaptive EDCF for both supporting priority of packets and throughput optimization. We have derived the relation between the number of nodes and contention window size for throughput optimization. Based on the analytic results, we have evaluated the performance of the proposed scheme using OPNET simulations. The simulation results show that using the proposed scheme can improve the overall throughput regardless of the number of nodes and the decrement of the throughput with increasing the number of nodes can be alleviated. Additionally, we have shown that the adaptive EDCF can support priority of packets more effectively than existing EDCF.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.4
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• pp.299-304
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• 2017

A wireless passive sensor network is a network consisting of sink nodes, sensor nodes, and radio frequency (RF) sources, where an RF source transfers energy to sensor nodes by radiating RF waves, and a sensor node transmits data by consuming the received energy. Against theoretical expectations, a wireless passive sensor network suffers from many practical difficulties: scarcity of energy, non-simultaneity of energy reception and data transmission, and inefficiency in allocating time resources. Perceiving such difficulties, we propose a simple contending-type medium access control (MAC) scheme for many sensor nodes to deliver packets to a sink node. Then, we derive an approximate expression for the network-wide throughput attained by the proposed MAC scheme. Also, we present an approximate expression for the optimal partition, which maximizes the saturated network-wide throughput. Numerical examples confirm that each of the approximate expressions yields a highly precise value for network-wide throughput and finds an exactly optimal partition.

• Journal of Communications and Networks
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• v.4 no.3
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• pp.230-245
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• 2002

Usually the network-throughput maximization problem for constant-bit-rate (CBR) circuit-switched traffic is posed for a fixed offered load profile. Then choices of routes and of admission control policies are sought to achieve maximum throughput (usually under QoS constraints). However, similarly to the notion of channel “capacity,” it is also of interest to determine the “network capacity;” i.e., for a given network we would like to know the maximum throughput it can deliver (again subject to specified QoS constraints) if the appropriate traffic load is supplied. Thus, in addition to determining routes and admission controls, we would like to specify the vector of offered loads between each source/destination pair that “achieves capacity.” Since the combined problem of choosing all three parameters (i.e., offered load, admission control, and routing) is too complex to address, we consider here only the optimal determination of offered load for given routing and admission control policies. We provide an off-line algorithm, which is based on Lagrangian techniques that perform robustly in this rigorously formulated nonlinear optimization problem with nonlinear constraints. We demonstrate that significant improvement is obtained, as compared with simple uniform loading schemes, and that fairness mechanisms can be incorporated with little loss in overall throughput.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.984-996
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• 2014

In this paper, optimal sensing time allocation for adaptive multiband spectrum sensing-transmission procedure is investigated. The sensing procedure consists of an exploration phase and a detection phase. We first formulate an optimization problem to maximize the throughput by designing not only the overall sensing time, but also the sensing time for every stage in the exploration and detection phases, while keeping the miss detection probability for each channel under a pre-defined threshold. Then, we transform the initial non-convex optimization problem into a convex bilevel optimization problem to make it mathematically tractable. Simulation results show that the optimized sensing time setting in this paper can provide a significant performance gain over the previous studies.

• Journal of the Korea Society for Simulation
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• v.9 no.2
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• pp.89-102
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• 2000

In this paper, we consider an optimal allocation of constant service efforts in queueing network to maximize the system throughput. For this purpose, using the perturbation analysis, we apply a stochastic optimization algorithm to two types of queueing systems. Our simulation results indicate that the estimates obtained from a stochastic optimization algorithm for a two-tandem queuing network are very accurate, and those for closed loop manufacturing system are a little apart from the known optimal allocation. We find that as simulation time increases for obtaining a new gradient (performance measure with respect to decision variables) by perturbation algorithm, the estimates tend to be more stable. Thus, we consider that it would be more desirable to have more accurate sensitivity of performance measure by enlarging simulation time rather than more searching steps with less accurate sensitivity. We realize that more experiments on various types of systems are needed to identify such a relationship with regards to stopping rule, the size of moving step, and updating period for sensitivity.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.9
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• pp.1891-1897
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• 2009

This paper describes the optimization of the spectrum sensing in terms of the throughput of the cognitive radio (CR)system. The conventional rapers do not describe the optimization problem of the spectrum sensing by considering the channel search and channel move of the CR system to be caused by the appearance of the incumbent user. However this paper evaluates the throughput of the CR user by considering the situations such as the channel search and channel move additionally. Also, this paper suggests the sensing structure being separated the data receiver from sensing receiver, and compares the sensing performance for the same receiver structure of sensing and communication with that for the separated sensing receiver in terms of the throughput of the CR user. The numerical result demonstrates that the performance of the throughput efficiency is improved by the proposed sensing receiver to be separated from the data communication path.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.247-248
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• 2008

A recent dynamic increase in demand for wireless multimedia services has greatly accelerated the research on dynamic channel adaptation of high quality video applications. In this paper, we explore a theoretical approach to cross-layer optimization between multimedia and wireless networks by means of a quality criterion termed "visual throughput" for downlink video transmission using a layered coding algorithm. We obtain the optimal loading ratio of orthogonal frequency division multiple access (OFDMA) subcarriers through an optimization problem balancing the trade-off relationship between inter-cell interference (ICI) and channel throughput. In the simulation, we show that the visual throughput gain at the cell boundary is increased by about 32%.

• Nuclear Engineering and Technology
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• v.52 no.5
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• pp.1008-1012
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• 2020

In order to make reasonable design for the improvement of comprehensive mechanical properties of RAFM steels, the design system with both machine learning and high-throughput optimization algorithm was established. As the basis of the design system, a dataset of RAFM steels was compiled from previous literatures. Then, feature engineering guided random forests regressors were trained by the dataset and NSGA II algorithm were used for the selection of the optimal solutions from the large-scale solution set with nine composition features and two treatment processing features. The selected optimal solutions by this design system showed prospective mechanical properties, which was also consistent with the physical metallurgy theory. This efficiency design mode could give the enlightenment for the design of other metal structural materials with the requirement of multi-properties.