• International Journal of Contents
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• v.8 no.4
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• pp.7-11
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• 2012

Cloud Computing can be viewed as a dynamically-scalable pool of resources. Virtualization is one of the key technologies enabling Cloud Computing functionalities. Virtual machines (VMs) scheduling and allocation is essential in Cloud Computing environment. In this paper, two dynamic VMs scheduling and allocating schemes are presented and compared. One dynamically on-demand allocates VMs while the other deploys optimal threshold to control the scheduling and allocating of VMs. The aim is to dynamically allocate the virtual resources among the Cloud Computing applications based on their load changes to improve resource utilization and reduce the user usage cost. The schemes are implemented by using SimPy, and the simulation results show that the proposed adaptive scheme with one threshold can be effectively applied in a Cloud Computing environment both performance-wise and cost-wise.

• Journal of Internet Computing and Services
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• v.18 no.4
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• pp.51-59
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• 2017

With the growth of Cloud computing, it is important to consider resource management techniques to minimize the overall costs of management. In cloud environments, each host's utilization and virtual machine's request based on user preferences are dynamic in nature. To solve this problem, efficient allocation method of virtual machines to hosts where the classification of virtual machines and hosts is undetermined should be studied. In reducing the number of active hosts to reduce energy consumption, thresholds can be implemented to migrate VMs to other hosts. By using Fuzzy logic in classifying resource requests of virtual machines and resource utilization of hosts, we proposed an adaptive VM allocation and migration approach. The allocation strategy classifies the VMs according to their resource request, then assigns it to the host with the lowest resource utilization. In migrating VMs from overutilized hosts, the resource utilization of each host was used to create an upper threshold. In selecting candidate VMs for migration, virtual machines that contributed to the high resource utilization in the host were chosen to be migrated. We evaluated our work through simulations and results show that our approach was significantly better compared to other VM allocation and Migration strategies.

• International Journal of Contents
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• v.7 no.2
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• pp.1-5
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• 2011

Allocation of computing resources is a crucial issue when dealing with a huge number of tasks to be completed according to a given deadline and cost constraints. The task scheduling to several resources (e.g. grid, cloud or a supercomputer) with different characteristics is not trivial, especially if a trade-off in terms of time and cost is considered. We propose an allocation approach able to fulfill the given requirements about time and cost through the use of optimizing techniques and an adaptive behavior. Simulated productions of tasks have been run in order to evaluate the characteristics of the proposed approach.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.3A
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• pp.221-228
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• 2009

We consider distributed resource allocation among the links in a wireless network to minimize the total transmit power of the network while meeting the target rate required by each link. The problem to be solved is how to change the amount of wireless resource allocated and the number of links sharing the resource according to the interference environment so that the following distributed power control game converges to a stable point. To provide a distributed method with less complexity and lower information exchange than the centralized optimal method, we define the resource sharing level among the links from which the size of resource allocated and the links sharing the resource are determined distributively. It is shown that the performance of the proposed method is better than that of the conventional methods, orthogonal resource allocation only and resource sharing only, as well as it approaches to that of the optimal method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.7C
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• pp.624-632
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• 2005

We consider an adaptive bit-loading technique for bit interleaved coded modulation-orthogonal frequency division multiplexing(BICM-OFDM) systems. By adjusting transmission parameter of each subcarrier adaptively depending on the subchannel state, the performance of OFDM system can be improved dramatically. In this paper, the number of bits for each subcarrier is allocated to minimize bit error rate keeping the constant throughput for the adaptive transmission technique of BICM-OFDM system which can be applied to real time transmission. Also, We use the discrete Lagrange multiplier method to get the optimum solution under the integer bit allocation constraint. Simulation results show that computational amount of the proposed bit allocation technique is not high and BICM-OfDM system using the proposed technique can get the SNR gain by 2$\~$3 dB over nonadaptive one.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.11A
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• pp.1113-1119
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• 2006

For a multi-user OFDM system in mobile channels which requires low-complexity in adaptive resource allocations, resource allocation algorithm using multi-threshold is proposed. The allocation scheme, which is performed by the multi-threshold values in descending order, considers only subcarriers over each threshold level. Moreover, some subcarriers with the lowest channel gain can be· removed in the present threshold level within the constraint of satisfaction of the required data rate, in order to allocate them to the other users when the allocation process of next threshold is executed. As a result, the proposed bandwidth and subcarrier algorithm has better system performances than the conventional allocation schemes in terms of required power and processing time, which is expected as a technique that improves the spectral efficiency of OFDM systems in a mobile environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.8A
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• pp.760-768
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• 2006

In this paper, an novel resource allocation scheme is proposed for adaptive multiuser OFDM-TDD systems in multiuser, multicell and frequency-selective time-varying channels. The optimal frame size and mode switching level of each user is determined by maximizing the spectrum efficiency. In multi-cell environment, the allocation scheme must consider the cochannel interference of other cells. The measured SINR is changed in one frame size because the interference is changed. The frame size is determined to consider both the optimal frame size and cochannel user's frame size of other cells. we propose the efficient resource allocation scheme which is satisfied the target BER.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.555-566
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• 2012

The cloud environment makes it possible to analyze large data sets in a scalable computing infrastructure. In the bioinformatics field, the applications are composed of the complex workflow tasks, which require huge data storage as well as a computing-intensive parallel workload. Many approaches have been introduced in distributed solutions. However, they focus on static resource provisioning with a batch-processing scheme in a local computing farm and data storage. In the case of a large-scale workflow system, it is inevitable and valuable to outsource the entire or a part of their tasks to public clouds for reducing resource costs. The problems, however, occurred at the transfer time for huge dataset as well as there being an unbalanced completion time of different problem sizes. In this paper, we propose an adaptive resource-provisioning scheme that includes run-time data distribution and collection services for hiding the data transfer time. The proposed adaptive resource-provisioning scheme optimizes the allocation ratio of computing elements to the different datasets in order to minimize the total makespan under resource constraints. We conducted the experiments with a well-known sequence alignment algorithm and the results showed that the proposed scheme is efficient for the cloud environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.7
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• pp.580-591
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• 2013

The Orthogonal Frequency Division Multiple Access (OFDMA) is considered as a novel modulation and multiple access technique for 4th generation wireless systems. In this paper, we formulate a base station's power allocation algorithm for each user to maximize the user's sum rate, subject to constraints on total power, bit error rate, and rate proportionality among the users for a better proportional rate adaptive (RA) resource allocation method for OFDMA based system. We propose a novel power allocation method based on the proportion of subcarrier allocation and the user's normalized proportionality constant. We adapt a greedy algorithm and waterfilling technique for allocating the subcarriers among the users. In an end-to-end simulation, we validate that the proposed technique has higher system capacity and lower CPU execution times, while maintaining the acceptable rate proportionality among users.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.10
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• pp.2382-2388
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• 2014

To provide network reliability in indoor wireless communication systems, we should resolve the problem of unexpected network failure rapidly. In this paper, we propose an adaptive resource management (ARM) scheme to support seamless connectivity to users. In consideration of system throughput and user fairness simultaneously, the ARM scheme adaptively determines the set of healing channels, and performs scheduling and power allocation iteratively based on a constrained non-convex optimization technique. Through intensive simulations, we demonstrate the superior performance results of the proposed ARM scheme in terms of the average cell capacity and user fairness.