• ETRI Journal
• /
• v.34 no.2
• /
• pp.199-209
• /
• 2012

In transport networks, a multi-ring architecture is very useful to facilitate network planning and to design and provide more resilient services for customers. Unlike traditional synchronous optical network multi-rings, the service resiliency of Ethernet-based multi-rings is significantly impacted by the ring hierarchy because a link or node failure in a certain level ring triggers filtering database flush actions in all higher level rings as well as in the ring with the failure, and consequently a large amount of duplicated data frames may be flooded. In this paper, we investigate how the ring hierarchy impacts the service resiliency of multi-ring networks. Based on extensive experiments on various single- and multiple-link failures, we suggest two effective inter-ring connection rules to minimize the transient traffic and to ensure more resilient multi-ring networks. In addition, we consider a flush optimization technique called e-ADV, and show that the combination of e-ADV and multi-ring structures satisfying our inter-ring connection rules results in a more attractive survivability performance.

• Industrial Engineering and Management Systems
• /
• v.15 no.4
• /
• pp.374-384
• /
• 2016

The efficiency of a supply chain can be extremely affected by its design which includes determining the flow pattern of material from suppliers to costumers, selecting the suppliers, and defining the opened facilities in network. In this paper, a multi-objective multi-echelon multi-product supply chain design model is proposed in which several suppliers, several manufacturers, several distribution centers as different stages of supply chain cooperate with each other to satisfy various costumers' demands. The multi-objectives of this model which considered simultaneously are 1-minimize the total cost of supply chain including production cost, transportation cost, shortage cost, and costs of opening a facility, 2-minimize the transportation time from suppliers to costumers, and 3-maximize the service level of the system by minimizing the maximum level of shortages. To configure this model a graph theoretic approach is used by considering channels among each two facilities as links and each facility as the nodes in this configuration. Based on complexity of the proposed model a multi-objective Pareto-based vibration damping optimization (VDO) algorithm is applied to solve the model and finally non-dominated sorting genetic algorithm (NSGA-II) is also applied to evaluate the performance of MOVDO. The results indicated the effectiveness of the proposed MOVDO to solve the model.

• Journal of Internet of Things and Convergence
• /
• v.9 no.4
• /
• pp.9-14
• /
• 2023

Recently, resource optimization research has been actively conducted in enterprises and data centers to manage the rapid growth of big data. In particular, thin provisioning, which allocates a large number of resources compared to fixedly allocated storage resources, has the effect of reducing initial costs, but as the number of resources actually used increases, the cost effectiveness decreases and the management cost for allocating resources increases. In this paper, we propose a technique that divides the physical blocks of flash memory into single-bit cells and multi-bit cells, formats them with a hybrid technique, and manages them by dividing frequently used hot data and infrequently used cold data. The proposed technique has the advantage that the physical and allocated resources are the same, such as thick provisioning, and can be used without additional cost increase, and the underutilized resources can be managed in multi-bit cell blocks, such as thin provisioning, which can allocate more resources than typical storage devices. Finally, we estimated the resource optimization effectiveness of the proposed technique through experiments based on simulations.

• International Journal of Naval Architecture and Ocean Engineering
• /
• v.10 no.5
• /
• pp.651-659
• /
• 2018

A multi-level overtopping wave energy converter was designed according to the large tidal range and small wave heights in China. It consists of two reservoirs with sloping walls at different levels. The reservoirs share a common outflow duct and a low-head axial turbine. The experimental study was carried out in a laboratory wave-flume to investigate the overtopping performance of the device. The depth-gauges were used to measure the variation of the water level in the reservoirs. The data was processed to derive the time-averaged overtopping discharges. It was found that the lower reservoir can store wave waters at the low water level and break the waves which try to climb up to the upper reservoir. The upper sloping angle and the opening width of the lower reservoir both have significant effects on the overtopping discharges, which can provide more information to the design and optimization of this type of device.

• Industrial Engineering and Management Systems
• /
• v.14 no.1
• /
• pp.1-10
• /
• 2015

In this paper, we consider multi-item inventory management. When managing a multi-item inventory, we coordinate replenishment orders of items supplied by the same supplier. The associated problem is called the joint replenishment problem (JRP). One often-used approach to the JRP is to apply a can-order policy. Under a can-order policy, some items are re-ordered when their inventory level drops to or below their re-order level, and any other item with an inventory level at or below its can-order level can be included in this order. In the present paper, we propose a method for finding the optimal parameter of a can-order policy, the can-order level, for each item in a lost-sales model. The main objectives in our model are minimizing the number of ordering, inventory, and shortage (i.e., lost-sales) respectively, compared with the conventional JRP, in which the objective is to minimize total cost. In order to solve this multi-objective optimization problem, we apply a genetic algorithm. In a numerical experiment using actual shipment data, we simulate the proposed model and compare the results with those of other methods.

• Journal of Advanced Marine Engineering and Technology
• /
• v.38 no.8
• /
• pp.1004-1009
• /
• 2014

The redundancy allocation problem has usually considered only the component redundancy at the lowest-level for the enhancement of system reliability. A system can be functionally decomposed into system, module, and component levels. Modular redundancy can be more effective than component redundancy at the lowest-level because in modular systems, duplicating a module composed of several components can be easier, and requires less time and skill. We consider a multi-level redundancy allocation problem in which all cases of redundancy for system, module, and component levels are considered. A tabu search of memory-based mechanisms that balances intensification with diversification via the short-term and long-term memory is proposed for its solution. To the best of our knowledge, this is the first attempt to use a tabu search for this problem. Our tabu search algorithm is compared with the previous genetic algorithm for the problem on the new composed test problems as well as the benchmark problems from the literature. Computational results show that the proposed method outstandingly outperforms the genetic algorithm for almost all test problems.

• IE interfaces
• /
• v.21 no.4
• /
• pp.444-455
• /
• 2008

In the present manufacturing environment, the appropriate decision making strategy has a significance and it should count on the fast-changing demand of customers. This research derives the optimal levels of the decision variables affecting the inventory related performance in multi-stage supply chain by using simulation and genetic algorithm. Simulation model helps analyze the customer service level of the supply chain computationally and the genetic algorithm searches the optimal solutions by interaction with the simulation model. Our experiments show that the integration approach of the genetic algorithm with a simulation model is effective in finding the solutions that achieve predefined target service levels.

• Proceedings of the Korean Information Science Society Conference
• /
• 2012.06d
• /
• pp.297-299
• /
• 2012

In this paper, we introduce a joint flow control and scheduling algorithm for multi-hop cognitive radio networks with spectrum underlay. Our proposed algorithm maximizes the total utility of secondary users while stabilizing the cognitive radio network and still satisfies the total interference from secondary users to primary network is less than an accepted level. Based on Lyapunov optimization technique, we show that our scheme is arbitrarily close to the optimal.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.15 no.3
• /
• pp.111-118
• /
• 2020

We investigate the optimization problem of transmit power control and MMSE Receiver filter for multi access points environment. Previous work showed that increasing the number of access points decreases the transmit power consumption. Accordingly, transmit power control algorithm was developed in such a way that the transmit power is minimized, while each terminal meets Signal to Interference and Noise Ratio Requirement. In this work, we further reduce the transmit power consumption by optimizing the transmit power level and the MMSE receiver filter together. We showed that the proposed joint optimization algorithm satisfies the necessary and sufficient conditions to be standard interference function, which guarantees convergence and minimum transmit power consumption. We observed that the proposed algorithm outperforms the algorithm which only optimizes the transmit power.

• ETRI Journal
• /
• v.32 no.4
• /
• pp.634-637
• /
• 2010

This letter presents a model for a dynamic collaboration (DC) platform among cloud providers (CPs) that prevents adverse business impacts, cloud vendor lock-in and violation of service level agreements with consumers, and also offers collaborative cloud services to consumers. We consider two major challenges. The first challenge is to find an appropriate market model in order to enable the DC platform. The second is to select suitable collaborative partners to provide services. We propose a novel combinatorial auction-based cloud market model that enables a DC platform among CPs. We also propose a new promising multi-objective optimization model to quantitatively evaluate the partners. Simulation experiments were conducted to verify both of the proposed models.