• Journal of Advanced Navigation Technology
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• v.23 no.2
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• pp.158-165
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• 2019

The existing web page was downloaded and provided to the user every time the user requested the page. Therefore, if the same page is repeatedly requested by the user, only the download for the same resource is repeated. This is a factor that causes unnecessary consumption of data. We focus on reducing data consumption caused by unnecessary requests between users and servers, and improving content delivery speed. Therefore, in this paper, we propose a caching system and an algorithm that can reduce the data consumption while maintaining the latest cache by comparing the hash value using the hash function that can detect the change of the file requested by the user.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2496-2512
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• 2021

The requirements for powerful computing capability, high capacity, low latency and low energy consumption of emerging services, pose severe challenges to the fifth-generation (5G) network. As a promising paradigm, mobile edge networks can provide services in proximity to users by deploying computing components and cache at the edge, which can effectively decrease service delay. However, the coexistence of heterogeneous services and the sharing of limited resources lead to the competition between various services for multiple resources. This paper considers two typical heterogeneous services: computing services and content delivery services, in order to properly configure resources, it is crucial to develop an effective offloading and caching strategies. Considering the high energy consumption of 5G base stations, this paper considers the hybrid energy supply model of traditional power grid and green energy. Therefore, it is necessary to design a reasonable association mechanism which can allocate more service load to base stations rich in green energy to improve the utilization of green energy. This paper formed the joint optimization problem of computing offloading, caching and resource allocation for heterogeneous services with the objective of minimizing the on-grid power consumption under the constraints of limited resources and QoS guarantee. Since the joint optimization problem is a mixed integer nonlinear programming problem that is impossible to solve, this paper uses deep reinforcement learning method to learn the optimal strategy through a lot of training. Extensive simulation experiments show that compared with other schemes, the proposed scheme can allocate resources to heterogeneous service according to the green energy distribution which can effectively reduce the traditional energy consumption.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.4
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• pp.135-140
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• 2015

The WDSS improves defensive capacity against web application layer DDoS attack by using web cache server and L7 switch which are added on the DDoS shelter system. When web DDoS attack occurs, security agents divert traffic from backbone network to sub-network of the WDSS and then DDoS protection device and L7 switch block abnormal packets. In the meantime, web cache server responds only to requests of normal clients and maintains stable web service. In this way, the WDSS can counteract the web DDoS attack which generates small traffic and depletes server-client session resource. Furthermore, the WDSS does not require IP tunneling because it is not necessary to retransfer the normal requests to original web server. In this paper, we validate operation of the WDSS and verify defensive capability against web application layer DDoS attacks. In order to do this, we built the WDSS on backbone network of an ISP. And we performed web DDoS tests by using a testing system that consists of zombie PCs. The tests were performed by three types and various amounts of web DDoS attacks. Test results suggest that the WDSS can detect small traffic of the web DDoS attacks which do not have repeat flow whereas the formal DDoS shelter system cannot.

• IEMEK Journal of Embedded Systems and Applications
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• v.1 no.2
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• pp.90-103
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• 2006

There are many file systems in various operating systems. Those are usually designed for server environments, where the common cases are usually 'multiple active users', 'great many small files' And they assume a big main memory to be used as buffer cache. So the existing file systems are not suitable for resource hungry embedded systems that process multimedia data streams. In this study, we designed and implemented a new file system which efficiently stores and retrieves multimedia data steams. The proposed file system has a very simple disk layout, which guarantees a quick disk initialization and file system recovery. And we introduced a new indexing-scheme, called the time-based indexing scheme, with the file system. With the indexing scheme, the file system maintains the relation between time and the location for all the multimedia streams. The scheme is useful in searching and playing the compressed multimedia streams by locating exact frame position with given time, resulting in reduction of CPU processing and power consumption. The proposed file system and its APIs utilizing the time-based indexing schemes were implemented firstly on a Linux environment, though it is operating system independent. In the performance evaluation on a real DVR system, which measured the execution time of multi-threaded reading and writing, we found the proposed file system is maximum 38.7% faster than EXT2 file system.

• The KIPS Transactions:PartA
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• v.9A no.2
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• pp.231-240
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• 2002

This paper proposes balancing scheduling effort more evenly between the compiler and the processor, by introducing independently scheduled VLIW instructions. Aggressively Packed VLIW (APVLIW) processor is aimed specifically at independent scheduling Very Long Instruction Word(VLIW) instructions with dependency information. The APVLIW processor independently schedules earth instruction within long instructions using functional unit and dynamic scheduler pairs. Every dynamic scheduler dynamically checks far data dependencies and resource collisions while scheduling each instruction. This scheduling is especially effective in applications containing loops. We simulate the architecture and show that the APVLIW processor performs significantly better than the VLIW processor for a wide range of cache sizes and across various numerical benchmark applications.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.3
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• pp.127-143
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• 2022

Recently, many attempts to run numerical ocean models in cloud computing environments have been tried actively. A cloud computing environment can be an effective means to implement numerical ocean models requiring a large-scale resource or quickly preparing modeling environment for global or large-scale grids. Many commercial and private cloud computing systems provide technologies such as virtualization, high-performance CPUs and instances, ether-net based high-performance-networking, and remote direct memory access for High Performance Computing (HPC). These new features facilitate ocean modeling experimentation on commercial cloud computing systems. Many scientists and engineers expect cloud computing to become mainstream in the near future. Analysis of the performance and features of commercial cloud services for numerical modeling is essential in order to select appropriate systems as this can help to minimize execution time and the amount of resources utilized. The effect of cache memory is large in the processing structure of the ocean numerical model, which processes input/output of data in a multidimensional array structure, and the speed of the network is important due to the communication characteristics through which a large amount of data moves. In this study, the performance of the Regional Ocean Modeling System (ROMS), the High Performance Linpack (HPL) benchmarking software package, and STREAM, the memory benchmark were evaluated and compared on commercial cloud systems to provide information for the transition of other ocean models into cloud computing. Through analysis of actual performance data and configuration settings obtained from virtualization-based commercial clouds, we evaluated the efficiency of the computer resources for the various model grid sizes in the virtualization-based cloud systems. We found that cache hierarchy and capacity are crucial in the performance of ROMS using huge memory. The memory latency time is also important in the performance. Increasing the number of cores to reduce the running time for numerical modeling is more effective with large grid sizes than with small grid sizes. Our analysis results will be helpful as a reference for constructing the best computing system in the cloud to minimize time and cost for numerical ocean modeling.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.968-972
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• 2009

The multi-core processors are being widely exploited by many high-end systems. With significant advances in processor architecture, the network band-width required on the high-end systems is increasing drastically. It is therefore highly desirable to manage multiple cores efficiently to achieve high network band-width with minimum resource requirements. Modern operating systems, however, still have significant design and optimization space to leverage the network performance over multi-core systems. In this paper, we suggest a novel networking process scheduling scheme, which decides the best processor affinity of networking processes based on the processor cache layout, communication intensiveness, and processor loads. The experimental results show that the scheduling scheme implemented in the Linux kernel can improve the network bandwidth and the effectiveness of processor utilization by 20% and 59%, respectively.

• Journal of Digital Contents Society
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• v.18 no.1
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• pp.167-173
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• 2017

As the increasing use of the cloud computing, virtualization technology have been combined and applied a variety of requirements. Cloud computing has the advantage that the support computing resource by a flexible and scalable to users as they want and it utilized in a variety of distributed computing. To do this, it is especially important to ensure the stability of the cloud computing. In this paper, we analyzed a variety of component measurement using open-source tools for ensuring the performance of the system on the education system to build cloud testbed environment. And we extract the performance that may affect the virtualization environment from processor, memory, cache, network, etc on each of the host machine(Host Machine) and a virtual machine (Virtual Machine). Using this result, we can clearly grasp the state of the system and also it is possible to quickly diagnose the problem. Furthermore, the cloud computing can be guaranteed the SLA(Service Level Agreement).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.8
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• pp.674-680
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• 2014

In this paper, as one of the fusion of IT and ocean technology, we propose a scheme to support NEMO in a harbor area network to provide network mobility for passengers, distribution as well as give a connection to an MN from an outside network. In a harbor area under PMIPv6 with NEMO support, a problem could be occurred due to overlapping HA/LMA tunnels and duplicate BCE fields. To Solve these problems, we consider the existing mobility option and add an optional field in the PBU message, which can notify the LMA and HA for either an initial connection or handover request. This procedure can reduce some overlapped steps of binding procedure. Hence, our proposed scheme could reduce an amount of delay and save the processing resource in the harbor area under PMIPv6 with NEMO support.

• KIISE Transactions on Computing Practices
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• v.22 no.9
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• pp.473-478
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• 2016

Server virtualization provides abstraction of physical resources to users and thus accomplishes high resource utilization and flexibility. However, the characteristics of server virtualization, such as the limited number of physical resources shared by virtual machines, can cause problems, mainly performance interference. The performance interference is caused by the fact that the CPU scheduler running on the host operating system schedules virtual machines without considering the characteristics of the virtual machine's internal process. To address performance interference, a number of research activities to improve performance interference have been conducted, but do not deal with the fundamental analysis of performance interference. In this paper, in order to analyze the cause of performance interference, we carry out profiling in a variety of scenarios in a virtualized environment based on KVM. As a result, we analyze the phenomenon of the performance interference in terms of CPU scheduling and propose an efficient scheduling solution.