• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3171-3191
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• 2016

Due to growing demand on wireless data traffic, a large number of different types of base stations (BSs) have been installed. However, space-time dependent wireless data traffic densities can result in a significant number of idle BSs, which implies the waste of power resources. To deal with this problem, we propose an active state control algorithm based on semi-Markov decision process (SMDP) for a heterogeneous network. A MDP in discrete time domain is formulated from continuous domain with some approximation. Suboptimal on-line learning algorithm with a random policy is proposed to solve the problem. We explicitly include coverage constraint so that active cells can provide the same signal to noise ratio (SNR) coverage with a targeted outage rate. Simulation results verify that the proposed algorithm properly controls the active state depending on traffic densities without increasing the number of handovers excessively while providing average user perceived rate (UPR) in a more power efficient way than a conventional algorithm.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.1
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• pp.25-32
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• 2003

As one of a new generation of industries, biotechnology is currently spotlighted, and is creating new research and industrial areas that can be readily combined with information technology. Among them, virtual screening is a method for new drug design which uses computer simulation to virtually design active drug candidates for special disease. In this paper, we present a distributed system for virtual screening, called DVSF(Distributed Virtual Screening Facilities). DVSF is designed and developed to perform virtual screening efficiently on logically distributed idle or strategic resources in a small or medium scale laboratory.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.628-646
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• 2016

This paper proposes a novel channel assignment scheme that is based on finite projective plane (FPP) theory. The proposed scheme involves using a Markov chain model to allocate N channels to N users through intermixed channel group arrangements, particularly when channel resources are idle because of inefficient use. The intermixed FPP-based channel group arrangements successfully related Markov chain modeling to punch through ratio formulations proposed in this study, ensuring fair resource use among users. The simulation results for the proposed FPP scheme clearly revealed that the defined throughput increased, particularly under light traffic load conditions. Nevertheless, if the proposed scheme is combined with successive interference cancellation techniques, considerably higher throughput is predicted, even under heavy traffic load conditions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.4
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• pp.139-145
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• 2016

On the ICT healing platform designed to issue early disease alerts, TOS connected between the provider of personal health-related data and the service provider and relayed personalized health data. In the previous study, TOS proposed how to monitor the retrieval and management of document/measurement resources by taking mobile devices into account. Recently the healthcare field, however, defined the standard items needed for communication and data exchanges with a mobile device through HL7 FHIR. This study designed a data grid model between TOS and FHIR to provide personal health resources relayed through TOS in FHIR bundle search sets. The proposed design was organized as follows: first, it stated similarities between the method of TOS resource request and that of FHIR observation request. Then, it designed an eventbus module to process a retrieval request for FHIR service based on the imdb and cluster technologies. The proposed design can be used to expand the old service terminals of ICT healing platform to mobile health devices capable of using FHIR resources.

• KIISE Transactions on Computing Practices
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• v.23 no.9
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• pp.572-577
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• 2017

Virtualization allows multiple virtual machines to share the resources of a physical machine in order to utilize idle resources. The purpose of virtualization is the efficient allocation of resources among virtual machines. However, the efficient allocation of resources is difficult because the workload characteristics of each virtual machine cannot be understood in the current virtualization environment. This causes performance interference among virtual machines, which leads to performance degradation of the virtual machine. Previous works have been carried out to develop a method of solving such performance interference. This paper introduces a representative method, a CPU scheduling method that guarantees I/O performance by using feedback control to solve performance interference. In addition, we compare and analyze a model-based feedback control method and a dynamic feedback control method.

• Korean Journal of Plant Resources
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• v.21 no.1
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• pp.5-11
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• 2008

This study examined the characteristics of Pinus thunbergii community that forms a windbreak forest around the coast of Gwanmaedo located in Jodo-myeon, Jindo-gun, Jeollanamdo which is located in the south-western areas of Korea from December 2005 to April 2007 and to suggeste the ecological management methods of coastal windbreak areas. P. thunbergii community, a coastal windbreak forest of Gwanmaedo, was classified into disturbance, growth, mixture, stability, and back mountain vegetation according to major companions species and vegetation types. P. thunbergii community of disturbance and growth vegetation needs active management through tree thinning, mowing, weeding out, use of rest space, and felling sick pine trees. P. thunbergii community of mixture, stability, and back mountain vegetation needs active preservation of a coastal windbreak to restore natural vegetation by making a windbreak walk and a forest buffer zone and inducing vegetation succession. Accordingly, in this study, ecological management methods were suggested according to the actual state of distribution by habitat characteristics of coastal windbreak areas such as management of beaches and surrounding area of idle lands, restoration of back wetlands, inhibition of foreign plants, maintenance of diversity of species and habitats, and prevention of aging and spread of damage from insects.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.2821-2839
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• 2015

Energy consumption by large computing systems has become an important research theme not only because the sources of energy are depleting fast but also due to the environmental concern. Computational grid is a huge distributed computing platform for the applications that require high end computing resources and consume enormous energy to facilitate execution of jobs. The organizations which are offering services for high end computation, are more cautious about energy consumption and taking utmost steps for saving energy. Therefore, this paper proposes a scheduling technique for Minimizing Energy consumption using Adapted Genetic Algorithm (MiE-AGA) for dependent tasks in Computational Grid (CG). In MiE-AGA, fitness function formulation for energy consumption has been mathematically formulated. An adapted genetic algorithm has been developed for minimizing energy consumption with appropriate modifications in each components of original genetic algorithm such as representation of chromosome, crossover, mutation and inversion operations. Pseudo code for MiE-AGA and its components has been developed with appropriate examples. MiE-AGA is simulated using Java based programs integrated with GridSim. Analysis of simulation results in terms of energy consumption, makespan and average utilization of resources clearly reveals that MiE-AGA effectively optimizes energy, makespan and average utilization of resources in CG. Comparative analysis of the optimization performance between MiE-AGA and the state-of-the-arts algorithms: EAMM, HEFT, Min-Min and Max-Min shows the effectiveness of the model.

• The KIPS Transactions:PartA
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• v.13A no.4 s.101
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• pp.363-370
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• 2006

Currently, many people have been researching diverse mechansmims related to a resource access control in Grid environment. Mostly Grid user's resource access control was designed to authorize according to their attributes and roles. But, to provide Grid with resources continuously, a resource access based on utility computing must be controlled. So, in this paper we propose and implement mechanism that intergrates Grid accounting concept with resource access control. This mechanism calcuates costs of Grid service on the basis of accounting, and determines based on user's fund availibility whether they continue to make use of site resources or not. Grid jobs will be controlled according to a site resource access control policy only if the amount of available fund is less than its costs. If Grid job completed, resource consumer pays for the costs generated by using provider's idle resources. Therefore, this paper provides mechansim to be able to control user's resource access by Grid accounting, so that it is evaluated as the research to realize utility computing environment corresponding to economic principle.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.137-142
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• 2021

The Internet of Things (IoT) paradigm is at the forefront of present and future research activities. The huge amount of sensing data from IoT devices needing to be processed is increasing dramatically in volume, variety, and velocity. In response, cloud computing was involved in handling the challenges of collecting, storing, and processing jobs. The fog computing technology is a model that is used to support cloud computing by implementing pre-processing jobs close to the end-user for realizing low latency, less power consumption in the cloud side, and high scalability. However, it may be that some resources in fog computing networks are not suitable for some kind of jobs, or the number of requests increases outside capacity. So, it is more efficient to decrease sending jobs to the cloud. Hence some other fog resources are idle, and it is better to be federated rather than forwarding them to the cloud server. Obviously, this issue affects the performance of the fog environment when dealing with big data applications or applications that are sensitive to time processing. This research aims to build a fog topology job scheduling (FTJS) to schedule the incoming jobs which are generated from the IoT devices and discover all available fog nodes with their capabilities. Also, the fog topology job placement algorithm is introduced to deploy jobs into appropriate resources in the network effectively. Finally, by comparing our result with the state-of-art first come first serve (FCFS) scheduling technique, the overall execution time is reduced significantly by approximately 20%, the energy consumption in the cloud side is reduced by 18%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.312-334
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• 2023

In large-scale computing, cloud computing plays an important role by sharing globally-distributed resources. The evolution of cloud has taken place in the development of data centers and numerous servers across the globe. But the cloud information centers incur huge operational costs, consume high electricity and emit tons of dioxides. It is possible for the cloud suppliers to leverage their resources and decrease the consumption of energy through various methods such as dynamic consolidation of Virtual Machines (VMs), by keeping idle nodes in sleep mode and mistreatment of live migration. But the performance may get affected in case of harsh consolidation of VMs. So, it is a desired trait to have associate degree energy-performance exchange without compromising the quality of service while at the same time reducing the power consumption. This research article details a number of novel algorithms that dynamically consolidate the VMs in cloud information centers. The primary objective of the study is to leverage the computing resources to its best and reduce the energy consumption way behind the Service Level Agreement (SLA)drawbacks relevant to CPU load, RAM capacity and information measure. The proposed VM consolidation Algorithm (PVMCA) is contained of four algorithms: over loaded host detection algorithm, VM selection algorithm, VM placement algorithm, and under loading host detection algorithm. PVMCA is dynamic because it uses dynamic thresholds instead of static thresholds values, which makes it suggestion for real, unpredictable workloads common in cloud data centers. Also, the Algorithms are adaptive because it inevitably adjusts its behavior based on the studies of historical data of host resource utilization for any application with diverse workload patterns. Finally, the proposed algorithm is online because the algorithms are achieved run time and make an action in response to each request. The proposed algorithms' efficiency was validated through different simulations of extensive nature. The output analysis depicts the projected algorithms scaled back the energy consumption up to some considerable level besides ensuring proper SLA. On the basis of the project algorithms, the energy consumption got reduced by 22% while there was an improvement observed in SLA up to 80% compared to other benchmark algorithms.