• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.9
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• pp.1802-1807
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• 2015

The cloud computing service provides physical IT resources to VM instances to users using virtual technique and the users pay cost of VM instances to service provider. The auction model based on cloud computing provides available resources of service provider to users through auction mechanism. The users bid spot instances to process their a job until its deadline time. If the bidding price of users is higher than the spot price, the user will be provided the spot instances by service provider. In this paper, we propose a new bidding strategy to minimize the total cost for job completion. Typically, the users propose bidding price as high as possible to get the spot instances and the spot price get high. we lower the spot price using proposed strategy and minimize the total cost for job completion. To evaluate the performance of our strategy, we compare the spot price and the total cost for job completion with real workload data.

• Journal of Digital Contents Society
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• v.19 no.3
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• pp.453-460
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• 2018

Virtualization technology is characterized by the ability to isolate the user's system environment and to support the computing resources flexibly and extensively on demand. However, virtualization technology of cloud computing, which is already well known, must overload the guest OS and the hypervisor to manage it. Container technology is emerging to solve such OS-based virtualization problems. This technology can isolate the processes under which the application is running, thus creating a virtualization-like environment with minimal overhead. In this work, we construct a container-based education practice system using Docker instead of the existing cloud-based environment. To do this, we analyze the requirements for the establishment of the training practice environment. We also analyze the functions of the container and study the method to meet the requirements. This can take advantage of the existing flexible and scalable cloud computing. Also, it maximizes the availability of limited resources by minimizing the performance load.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.3
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• pp.81-84
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• 2015

Cloud service is one of major technologies in modern IT business. Due to the dynamics of user demands, service providers need VM(Virtual Machine) provisioning mechanism to predict the amount of resources demanded by cloud users for the next service and to prepare the resources. VM provisioning provides the QoS to cloud user and maximize the revenue of a service provider by minimizing the expense. In this paper, we propose a new VM provisioning technique to minimize the total expense of a service provider by minimizing the expected value of the expense based on the predicted demands of users. To evaluate the effectiveness of our prediction technique, we compare the total expense of our technique with these of the other prediction techniques with a series of real trace data.

• Journal of Information Processing Systems
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• v.14 no.3
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• pp.569-589
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• 2018

Cloud computing, also known as "country as you go", is used to turn any computer into a dematerialized architecture in which users can access different services. In addition to the daily evolution of stakeholders' number and beneficiaries, the imbalance between the virtual machines of data centers in a cloud environment impacts the performance as it decreases the hardware resources and the software's profitability. Our axis of research is the load balancing between a data center's virtual machines. It is used for reducing the degree of load imbalance between those machines in order to solve the problems caused by this technological evolution and ensure a greater quality of service. Our article focuses on two main phases: the pre-classification of tasks, according to the requested resources; and the classification of tasks into levels ('odd levels' or 'even levels') in ascending order based on the meta-heuristic "Bat-algorithm". The task allocation is based on levels provided by the bat-algorithm and through our mathematical functions, and we will divide our system into a number of virtual machines with nearly equal performance. Otherwise, we suggest different classes of virtual machines, but the condition is that each class should contain machines with similar characteristics compared to the existing binary search scheme.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.11
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• pp.377-386
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• 2020

Mobile cloud computing involves mobile or embedded devices as clients, and features small devices with constrained resource and low availability. Due to the fast expansion of smart phones and smart peripheral devices, researches on mobile cloud computing attract academia's interest more than ever. Computation offloading, or code offloading, enhances the performance of computation by migrating a part of computation of a mobile system to nearby cloud servers with more computational resources through wired or wireless networks. Code offloading is considered as one of the best approaches overcoming the limited resources of mobile systems. In this paper, we analyze the factors and the performance of code offloading, especially focusing on static program partitioning and data protection. We survey state-of-the-art researches on analyzed topics. We also describe directions for future research.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.99-106
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• 2023

In this paper, we propose subregion-based area of interest management techniques for MMORPG(massively multiplayer online role playing games) integrating P2P(peer-to-peer) networking and cloud computing. For the crowded region, the proposed techniques partition it into several subregions and assign a player to manage each subregion as a coordinator. These techniques include a load balancing mechanism which regulates communication and computation overhead of such player below the specified threshold. We also provide a mechanism for satisfying the criterion, where subregions overlapped with each player's view must be switched quickly and seamlessly as the view moves around in the game world. In the proposed techniques where an efficient provisioning of resources is realized, they relieve a lot of computational power and network traffic, the load on the servers in the cloud by exploiting the capacity of the players effectively. Simulation results show that the MMORPG based on cloud and P2P architecture can reduce the considerable bandwidth at the server compared to the client server architecture as the available resources grow with the number of players in crowding or hotspots.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5694-5711
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• 2017

The technology of cloud computing is growing very quickly, thus it is required to manage the process of resource allocation. In this paper, load balancing algorithm based on honey bee behavior (LBA_HB) is proposed. Its main goal is distribute workload of multiple network links in the way that avoid underutilization and over utilization of the resources. This can be achieved by allocating the incoming task to a virtual machine (VM) which meets two conditions; number of tasks currently processing by this VM is less than number of tasks currently processing by other VMs and the deviation of this VM processing time from average processing time of all VMs is less than a threshold value. The proposed algorithm is compared with different scheduling algorithms; honey bee, ant colony, modified throttled and round robin algorithms. The results of experiments show the efficiency of the proposed algorithm in terms of execution time, response time, makespan, standard deviation of load, and degree of imbalance.

• International journal of advanced smart convergence
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• v.1 no.2
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• pp.12-15
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• 2012

Energy costs for operating and cooling computing resources in Cloud infrastructure have increased significantly up to the point where they would surpass the hardware purchasing costs. Thus, reducing the energy consumption can save a significant amount of management cost. One of major approach is removing hardware over-provisioning. In this paper, we propose a technique that facilitates power saving through reducing resource over provisioning based on virtualization technology. To this end, we use dynamic workload shaping to reschedule and redistribute job requests considering overall power consumption. In this paper, we present our approach to shape workloads dynamically and distribute them on virtual machines and physical machines through virtualization technology. We generated synthetic workload data and evaluated it in simulating and real implementation. Our simulated results demonstrate our approach outperforms to when not using no workload shaping methodology.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.2
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• pp.73-79
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• 2013

Cloud computing is a form which provides IT resources through network and pays the cost as much as you used. And it has advantages that it doesn't need to construct infrastructure and can be offered a variety of environments. The main core of these computing is virtualization technology. Security mechanism about attacks using vulnerabilities of virtualization technology isn't provided right and existing security tools can't be applied as it is. In this paper, we proposed honeyVM structure that can cope actively by collecting the information about attacks using virtualization vulnerability. Mamdani fuzzy inference is used to adjust dynamically the number of formed honeyVM depending on the load of system. Security structure to protect actual virtual machine from attacks and threats is proposed. The performance of the proposed structure in this paper measured occurred attack detection rate and resource utilization rate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4950-4966
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• 2015

Cloud providers now face the problem of estimating the amount of computing resources required to satisfy a future workload. In this paper, a virtual machine provisioning (VMP) mechanism is designed to adapt workload fluctuation. The arrival rate of forthcoming jobs is predicted for acquiring the proper service rate by adopting an exponential smoothing (ES) method. The proper service rate is estimated to guarantee the service level agreement (SLA) constraints by using a diffusion approximation statistical model. The VMP problem is formulated as a facility location problem. Furthermore, it is characterized as the maximization of submodular function subject to the matroid constraints. A greedy-based VMP algorithm is designed to obtain the optimal virtual machine provision pattern. Simulation results illustrate that the proposed mechanism could increase the average profit efficiently without incurring significant quality of service (QoS) violations.