• Journal of Korean Society of Industrial and Systems Engineering
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• v.16 no.27
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• pp.73-82
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• 1993

In this paper, We determine the expected travel time for several forks Storage/Retrieval machine which is allowed multiple stops in aisle. When throughput is increased, We propose adding to fork number of each S/R machine rather than adding to number of S/R machine, We also describe such a model which determines the optimal number of each several forks S/R machine subject to constraints on the hourly throughput and warehouse dimensions. Numerical example is presented to compare warehouse shapes against each single fork, twin forks, triple forks S/R machine for various throughput values.

• International Journal of Advanced Culture Technology
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• v.1 no.2
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• pp.18-23
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• 2013

In this paper, we consider the problem of designing optimal sensing time and the minimization of energy consumption in the Cognitive radio Network. Trade-off between throughput and the sensing time are observed, and the equations are derived for the optimal choice of design variables. In this paper, we also look at the optimization problem involving all the design parameters together. The advantages of the proposed scheme for the spectrum sensing and access process are shown through simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3542-3566
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• 2018

In this paper, we investigate a buffer-aided wireless powered cooperative communication network (WPCCN), in which the source and relay harvest the energy from a dedicated power beacon via wireless energy transfer, then the source transmits the data to the destination through the relay. Both the source and relay are equipped with an energy buffer to store the harvested energy in the energy transfer stage. In addition, the relay is equipped with a data buffer and can temporarily store the received information. Considering the buffer-aided WPCCN, we propose two buffer-aided relaying protocols, which named as the buffer-aided harvest-then-transmit (HtT) protocol and the buffer-aided joint mode selection and power allocation (JMSPA) protocol, respectively. For the buffer-aided HtT protocol, the time-averaged achievable rate is obtained in closed form. For the buffer-aided JMSPA protocol, the optimal adaptive mode selection scheme and power allocation scheme, which jointly maximize the time-averaged throughput of system, are obtained by employing the Lyapunov optimization theory. Furthermore, we drive the theoretical bounds on the time-averaged achievable rate and time-averaged delay, then present the throughput-delay tradeoff achieved by the joint JMSPA protocol. Simulation results validate the throughput performance gain of the proposed buffer-aided relaying protocols and verify the theoretical analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2063-2081
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• 2018

A resource allocation algorithm is proposed in this paper to simultaneously minimize the total system power consumption and maximize the system throughput for the downlink of multi-user multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems. With the Lagrange dual decomposition method, we transform the original problem to its convex dual problem and prove that the duality gap between the two problems is zero, which means the optimal solution of the original problem can be obtained by solving its dual problem. Then, we use convex optimization method to solve the dual problem and utilize bisection method to obtain the optimal dual variable. The numerical results show that the proposed algorithm is superior to traditional single-objective optimization method in both the system throughput and the system energy consumption.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.2
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• pp.455-461
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• 2008

Enhanced Distributed Channel Access (EDCA) is a channel access scheme adopted by the IEEE 802.11e draft standard for QoS-enabled wireless local area networks. It classifies traffic into separate Access Categories (ACs) and achieves service differentiation by allowing each AC to have its own values of channel access parameters. This paper proposes a scheme to dynamically adapt the EDCA parameters to traffic environment so that they both maximize the throughput of non real-time traffics and meet the delay and throughput constraints of real-time traffics. For this purpose, we develop a design algorithm for efficient exploration of the EDCA parameter space. Using the algorithm, we derive a Pareto curve fur delay-throughput trade-off in each anticipated traffic environment. The Pareto database can then be used to optimally adjust the parameter according to the traffic environment and administrative policies. Simulation results show that compared with the default parameter configuration, the proposed scheme is better for delay, throughput guarantee and can improve the throughput of non real-time traffics by 12% on average.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.4
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• pp.1208-1222
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• 2014

Due to the low utilization and scarcity of frequency spectrum in current spectrum allocation methodology, cognitive radio networks (CRNs) have been proposed as a promising method to solve the problem, of which spectrum sensing is an important technology to utilize the precious spectrum resources. In order to protect the primary user from being interfered, most of the related works focus only on the restriction of the missed detection probability, which may causes over-protection of the primary user. Thus the interference probability is defined and the interference-aware sensing model is introduced in this paper. The interference-aware sensing model takes the spatial conditions into consideration, and can further improve the network performance with good spectrum reuse opportunity. Meanwhile, as so many fading factors affect the spectrum channel, errors are inevitably exist in the reporting channel in cooperative sensing, which is improper to be ignored. Motivated by the above, in this paper, we study the throughput tradeoff for interference-aware cognitive radio networks over imperfect reporting channel. For the cooperative spectrum sensing, the K-out-of-N fusion rule is used. By jointly optimizing the sensing time and the parameter K value, the maximum throughput can be achieved. Theoretical analysis is given to prove the feasibility of the optimization and computer simulations also shows that the maximum throughput can be achieved when the sensing time and the parameter of K value are both optimized.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3412-3432
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• 2019

Recent advances in radio frequency (RF) power transfer provide a promising technology to power sensor nodes. Adoption of mobile chargers to replenish the nodes' energy has recently attracted a lot of attention and the mobility assisted energy replenishment provides predictable and sustained power service. In this paper, we study the joint optimization of mobile charging and data gathering in sensor networks. A wireless multi-functional vehicle (WMV) is employed and periodically moves along specified trajectories, charge the sensors and gather the sensed data via one-hop communication. The objective of this paper is to maximize the uplink throughput by optimally allocating the time for the downlink wireless energy transfer by the WMV and the uplink transmissions of different sensors. We consider two scenarios where the WMV moves in a straight line and around a circle. By time discretization, the optimization problem is formulated as a 0-1 programming problem. We obtain the upper and lower bounds of the problem by converting the original 0-1 programming problem into a linear programming problem and then obtain the optimal solution by using branch and bound algorithm. We further prove that the network throughput is independent of the WMV's velocity under certain conditions. Performance of our proposed algorithm is evaluated through extensive simulations. The results validate the correctness of our proposed theorems and demonstrate that our algorithm outperforms two baseline algorithms in achieved throughput under different settings.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2A
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• pp.121-127
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• 2010

In this paper, we propose a computationally efficient scheduling algorithm that can arbitrarily control the throughput-fairness tradeoff in a multiuser wireless communication environment. As a new scheduling criterion, we combine linearly two well-known scheduling criteria such as one of achieving the maximum sum throughput and the other of achieving the maximum fairness, so as to control the relative proportion of the throughput and the fairness according to a control factor. For linear combining two different criteria, their optimization directivenesses and the units should be unified first. To meet these requirements, we choose an instantaneous channel capacity as a scheduling criterion for maximizing the sum throughput and the average serving throughput for maximizing the fairness. Through a unified linear combining of two optimization objectives with the control factor, it can provide various throughput-fairness tradeoffs according to the control factors. For further simplification, we exploit a high signal-to-noise ratio (SNR) approximation of the instantaneous channel capacity. Through computer simulations, we evaluate the throughput and fairness performances of the proposed algorithm according to the control factors, assuming an independent Rayleigh fading multiuser channel. We also evaluate the proposed algorithm employing the high SNR approximation. From simulation results, we could see that the proposed algorithm can control arbitrarily the throughput-fairness performance between the performance of the scheduler aiming to the maximum sum throughput and that of the scheduler aiming to the maximum fairness, finally, we see that the high SNR approximation can give a satisfactory performance in this situation.

• Journal of electromagnetic engineering and science
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• v.12 no.1
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• pp.1-7
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• 2012

In this paper, we investigated the throughput of a cognitive radio network where two primary frequency channels (PCs) are sensed and opportunistically accessed by N secondary users. The sharing sensing member (SSM) protocol is introduced to sense both PCs simultaneously. According to the SSM protocol, N SUs (Secondary User) are divided into two groups, which allows for the simultaneous sensing of two PCs. With a frame structure, after determining whether the PCs are idle or active during a sensing slot, the SUs may use the remaining time to transmit their own data. The throughput of the network is formulated as a convex optimization problem. We then evaluated an iterative algorithm to allocate the optimal sensing time, fusion rule and the number of members in each group. The computer simulation and numerical results show that the proposed optimal allocation improves the throughput of the SU under a misdetection constraint to protect the PCs. If not, its initial date of receipt shall be nullified.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.3110-3125
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• 2014

Network coding improves TCP's performance in lossy wireless networks. However, the complex congestion window evolution of network coded TCP (TCP-NC) makes the analysis of end-to-end throughput challenging. This paper analyzes the evolutionary process of TCP-NC against lossy links. An analytic model is established by applying a two-dimensional Markov chain. With maximum window size, end-to-end erasure rate and redundancy parameter as input parameters, the analytic model can reflect window evolution and calculate end-to-end throughput of TCP-NC precisely. The key point of our model is that by the novel definition of the states of Markov chain, both the number of related states and the computation complexity are substantially reduced. Our work helps to understand the factors that affect TCP-NC's performance and lay the foundation of its optimization. Extensive simulations on NS2 show that the analytic model features fairly high accuracy.