• Journal of KIISE:Computer Systems and Theory
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• v.37 no.3
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• pp.147-160
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• 2010

The system virtualization shows interest in the consolidation of servers for the efficient utilization of system resources. There are many various researches to utilize a server machine more efficiently through the system virtualization technique, and improve performance of the virtualization software. These researches have studied with the activity to control the resource allocation of virtual machines dynamically focused on CPU, or to manage resources in the cross-machine using the migration. However, the researches of the memory management have been wholly lacking. In this respect, the use of memory is limited to allocate the memory statically to virtual machine in server consolidation. Unfortunately, the static allocation of the memory causes a great quantity of the idle memory and decreases the memory utilization. The underutilization of the memory makes other side effects such as the load of other system resources or the performance degradation of services in virtual machines. In this paper, we suggest the dynamic allocation of the memory in Xen to control the memory allocation of virtual machines for the utilization without the performance degradation. Using AR model for the prediction of the memory usage and ACO (Ant Colony Optimization) algorithm for optimizing the memory utilization, the system operates more virtual machines without the performance degradation of servers. Accordingly, we have obtained 1.4 times better utilization than the static allocation.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.39-48
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• 2013

A cloud system has to deal with highly variable workloads resulting from dynamic usage patterns in order to keep the QoS within the predefined SLA. Aside from the aspects regarding services, another emerging concern is to keep the energy consumption at a minimum. This requires the cloud providers to consider energy and performance trade-off when allocating virtualized resources in cloud data centers. In this paper, we propose a resource provisioning approach based on dynamic thresholds to detect the workload level of the host machines. The VM selection policy uses utilization data to choose a VM for migration, while the VM allocation policy designates VMs to a host based on its service reputation. We evaluated our work through simulations and results show that our work outperforms non-power aware methods that don't support migration as well as those based on static thresholds and random selection policy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.9A
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• pp.888-897
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• 2007

In this paper, we propose an uplink dynamic resource allocation algorithm to increase sector throughput and fairness among users in 802.16e OFDMA TDD system. In uplink, we address the difference between uplink and downlink channel state information in 802.16e OFDMA TDD system. The simulation results show that not only an increment of 10% of sector throughput but higher level of fairness is achieved by round-robin using the FLR and the rate / margin adaptive inner closed-loop power control algorithm. The FLR algorithm determines the number of sub-channels to be allocated to the user according to the user's position. Also, we get 31.8% more sector throughput compared with the round-robin using FLR by FASA algorithm using uplink channel state information. User selection, sub-channel allocation, power allocation algorithms and simulation methodology are mentioned in Part I.

• IE interfaces
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• v.9 no.3
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• pp.202-213
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• 1996

Video-on-demand is an interactive service that provides programs (movie, home shopping, etc.) to users connected to a network. This service will require high bandwidth network and video servers with a large amount of storage capacity. From the viewpoint of system analysis, there are optimization problems to be solved. In this paper, we present a dynamic programming method for allocating the storage for programs being served in a multi-level video-on-demand network. In the optimization of the network resource, we consider the three kinds of costs: installation cost for video servers, program storage cost, and transmission (or communication) cost. The factors related to the costs are investigated. An example is shown to illustrate the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.11
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• pp.1138-1147
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• 2012

In this paper, an efficient power control based MF-TDMA resource allocation scheme is proposed for next generation military satellite communication systems. The proposed scheme has the flexibility is used to support heterogeneous terminals with differ in transmission capabilities. The method can be divided into two parts : burst size calculation and burst structure determination. At first, we estimate the link budget taken into account a dynamic satellite link state variation. Then, applicable ACM level and burst size is chosen. In burst structure determination phase, we reorganize the burst structure in time-frequency domain by controlling limited power, bandwidth, time resources. In particular, we compensate the power spectral density among different terminals to integrate them in same transponder, Furthermore, we increase the packing efficiency by controlling the ACM level of the burst in applicable power spectral density range. Simulation results show that the method increase the spectral efficiency and burst packing efficiency. In addition, slot allocation rejection ratio is successfully reduced.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.9B
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• pp.777-784
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• 2006

In this paper, we propose the PON-based access network based on conventional TDM-PON architecture, which utilizes WDM wavelength channel and bandwidth dynamically. It is also described a dynamic MAC protocol in order to increase the number of subscribers and efficiency of resource utilization. Of particular importance in the proposed approach for MAC protocol is that the wavelength channel and time slot for up/downlink is dynamically allocated according to the required QoS level and the amount of data in data transmission, through the dedicated control channel between OLT and ONU. We evaluate the performance of average packet end-to-end delay in a statistical analysis and numerical analysis. In addition, through simulations with various traffic models, we verified the superior performance of the proposed approach by comparing with the results of other E-PONs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.4
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• pp.1192-1207
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• 2014

Dynamic spectrum sharing is a key technology to improve spectrum utilization in wireless networks. The elastic spectrum management provides a new opportunity for licensed primary users and unlicensed secondary users to efficiently utilize the scarce wireless resource. In this paper, we present a game-theoretic framework for dynamic spectrum allocation where the primary users rent the unutilized spectrum to the secondary users for a monetary profit. In reality, due to the ON-OFF behavior of the primary user, the quantity of spectrum that can be opportunistically shared by the secondary users is limited. We model this situation with the renewal theory and formulate the spectrum pricing scheme with the Bertrand game, taking into account the scarcity of the spectrum. By the Nash-equilibrium pricing scheme, each player in the game continually converges to a strategy that maximizes its own profit. We also investigate the impact of several properties, including channel quality and spectrum substitutability. Based on the equilibrium analysis, we finally propose a decentralized algorithm that leads the primary users to the Nash-equilibrium, called DST. The stability of the proposed algorithm in terms of convergence to the Nash equilibrium is also studied.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1532-1553
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• 2014

Radio spectrum is a precious resource and characterized by fixed allocation policy. However, a large portion of the allocated radio spectrum is underutilized. Conversely, the rapid development of ubiquitous wireless technologies increases the demand for radio spectrum. Cognitive Radio (CR) methodologies have been introduced as a promising approach in detecting the white spaces, allowing the unlicensed users to use the licensed spectrum thus realizing Dynamic Spectrum Access (DSA) in an effective manner. This paper proposes a generalized framework for DSA between the licensed (primary) and unlicensed (secondary) users based on Continuous Time Markov Chain (CTMC) model. We present a spectrum access scheme in the presence of sensing errors based on CTMC which aims to attain optimum spectrum access probabilities for the secondary users. The primary user occupancy is identified by spectrum sensing algorithms and the sensing errors are captured in the form of false alarm and mis-detection. Simulation results show the effectiveness of the proposed spectrum access scheme in terms of the throughput attained by the secondary users, throughput optimization using optimum access probabilities, probability of interference with increasing number of secondary users. The efficacy of the algorithm is analyzed for both imperfect spectrum sensing and perfect spectrum sensing.

• Journal of Communications and Networks
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• v.10 no.3
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• pp.258-267
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• 2008

In this paper, we examine what changes the next-generation wireless communication systems will experience in terms of the technologies, services, and networks and, based on that, we investigate how the inter-cell interference management should evolve in various aspects. We identify that the main driving forces of the future changes involve the data-centric services, new dynamic service scenarios, all-IP core access networks, new physical-layer technologies, and heavy upload traffic. We establish that in order to cope with the changes, the next-generation inter-cell interference management should evolve to 1) set the objective of providing a maximal data rate, 2) take the form of joint management of power allocation and user scheduling, 3) operate in a fully distributed manner, 4) handle the time-varying channel conditions in mobile environment, 5) deal with the changes in interference mechanism triggered by the new physical-layer technologies, and 6) increase the spectral efficiency while avoiding centralized coordination of resource allocation of the users in the uplink channel.

• Journal of the Korea Society for Simulation
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• v.19 no.2
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• pp.81-89
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• 2010

Biological data mining has been noticed as an issue as the volume of biological data is increasing extremely. Grid technology can share and utilize computing data and resources. In this paper, we propose a hybrid system that combines biological data mining with grid technology. Especially, we propose a decision range adjustment algorithm for processing efficiency of biological data mining. We obtain a reliable data mining recognition rate automatically and rapidly through this algorithm. And communication loads and resource allocation are key issues in grid environment because the resources are geographically distributed and interacted with themselves. Therefore, we propose a dynamic load balancing algorithm and apply it to the grid-based biological data mining method. For performance evaluation, we measure average processing time, average communication time, and average resource utilization. Experimental results show that this method provides many advantages in aspects of processing time and cost.