• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권8호
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• pp.3182-3202
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• 2015

Flexibly expanding the storage capacity required to process a large amount of rapidly increasing unstructured log data is difficult in a conventional computing environment. In addition, implementing a log processing system providing features that categorize and analyze unstructured log data is extremely difficult. To overcome such limitations, we propose and design a MongoDB-based unstructured log processing system (MdbULPS) for collecting, categorizing, and analyzing log data generated from banks. The proposed system includes a Hadoop-based analysis module for reliable parallel-distributed processing of massive log data. Furthermore, because the Hadoop distributed file system (HDFS) stores data by generating replicas of collected log data in block units, the proposed system offers automatic system recovery against system failures and data loss. Finally, by establishing a distributed database using the NoSQL-based MongoDB, the proposed system provides methods of effectively processing unstructured log data. To evaluate the proposed system, we conducted three different performance tests on a local test bed including twelve nodes: comparing our system with a MySQL-based approach, comparing it with an Hbase-based approach, and changing the chunk size option. From the experiments, we found that our system showed better performance in processing unstructured log data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권12호
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• pp.5780-5802
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• 2017

Cloud computing system consists of distributed resources in a dynamic and decentralized environment. Therefore, using cloud computing resources efficiently and getting the maximum profits are still challenging problems to the cloud service providers and cloud service users. It is important to provide the efficient scheduling. To schedule cloud resources, numerous heuristic algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Cuckoo Search (CS) algorithms have been adopted. The paper proposes a Modified Particle Swarm Optimization (MPSO) algorithm to solve the above mentioned issues. We first formulate an optimization problem and propose a Modified PSO optimization technique. The performance of MPSO was evaluated against PSO, and GA. Our experimental results show that the proposed MPSO minimizes the task execution time, and maximizes the resource utilization rate.

• 인터넷정보학회논문지
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• 제22권5호
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• pp.57-67
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• 2021

Modern cloud computing is rapidly changing from traditional hypervisor-based virtual machines to container-based cloud-native environments. Due to limitations in I/O performance required for both virtual machines and containers, the use of high-speed storage (SSD, NVMe, etc.) is increasing, and in-memory computing using main memory is also emerging. Running a virtual environment on main memory gives better performance compared to other storage arrays. However, RAM used as main memory is expensive and due to its volatile characteristics, data is lost when the system goes down. Therefore, additional work is required to run the virtual environment in main memory. In this paper, we propose a hybrid in-memory storage that combines a block storage such as a high-speed SSD with main memory to safely operate virtual machines and containers on main memory. In addition, the proposed storage showed 6 times faster write speed and 42 times faster read operation compared to regular disks for virtual machines, and showed the average 12% improvement of container's performance tests.

• 사물인터넷융복합논문지
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• 제6권3호
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• pp.39-44
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• 2020

본 논문은 SDN 기반 네트워크에서 fog computing 서비스의 이동성을 제안하고자 한다. Fog computing 아키텍처는 컴퓨팅 및 배터리 자원의 제약이 있는 IoT(Internet of Things) 기기들에게 테스크 오프로딩을 가능하게 함으로써 IoT의 저지연/고성능 서비스를 위한 방안으로 연구되고 있다. 하지만 fog computing 아키텍처에서는 고정된 IoT 기기 뿐만 아니라 이동하는 IoT 기기도 서비스 대상 단말로 고려되어야 하기 때문에 이러한 기기의 이동성을 고려한 오프로딩 방안이 필요하다. 특히 저지연 응답 시간을 요구하는 IoT 서비스의 경우, 오프로딩 이후 단말이 이동했을 때 새로운 fog computing 노드와의 새로운 통신 연결 및 테스크 오프로딩 과정을 다시 수행해야 하기 때문에 지연시간이 발생하여 사용자의 QoS(Quality of Service) 저하가 발생할 수 있다. 그러므로 본 연구에서는 단말의 이동성을 고려하여 테스크 또는 테스크의 결과를 이동 후의 fog computing 노드로 미리 migration 시키고 데이터 전송을 위한 rule 또한 미리 배치시킴으로써 통신 지연 및 서비스 복구 지연 시간을 줄일 수 있는 방안을 제시하고자 한다.

• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.310-328
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• 2022

Internet of things (IoT) has emerged as the most popular technique that facilitates enhancing humans' quality of life. However, most time sensitive IoT applications require quick response time. So, processing these IoT applications in cloud servers may not be effective. Therefore, fog computing has emerged as a promising solution that addresses the problem of managing large data bandwidth requirements of devices and quick response time. This technology has resulted in processing a large amount of data near the data source compared to the cloud. However, efficient management of computing resources involving balancing workload, allocating resources, provisioning resources, and scheduling tasks is one primary consideration for effective computing-based solutions, specifically for time-sensitive applications. This paper provides a comprehensive review of the source management strategies considering resource limitations, heterogeneity, unpredicted traffic in the fog computing environment. It presents recent developments in the resource management field of the fog computing environment. It also presents significant management issues such as resource allocation, resource provisioning, resource scheduling, task offloading, etc. Related studies are compared indifferent mentions to provide promising directions of future research by fellow researchers in the field.

• 인터넷정보학회논문지
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• 제17권5호
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• pp.9-16
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• 2016

Pervasive computing and Internet of Things (IoT) have recently received considerable interest to deploy solutions for the future Internet. Smart environments are integrated with Semantic Web to provide context-awareness to the processed information. Self-learning techniques have been adopted within smart solutions for efficient retrieval of data but do not process data with privacy parameters for in-place authorization. To overcome this issue, we present a novel approach of deploying access control as a service mechanism within Semantic Web based smart environment by using eXtensible Access Control Markup Language (XACML). The proposed XACML as a Service (XACMLaaS) approach offers fine-grained access control for protecting information within smart environment. In this paper, we have defined mathematical rules for each components of proposed access control service layer. These rules are for implementation of access control using XACML. The proposed approach allows the adaptation of authorization of information at component level and provides scalable solution for authorization policies and rule enforcement within smart environment.

• 융합보안논문지
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• 제12권3호
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• pp.59-65
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• 2012

IT와 네트워크 기술의 발전으로 새롭게 소개된 클라우드 컴퓨팅은 개인의 인터넷 환경뿐만 아니라 기업들의 서비스 환경에도 많은 변화를 가져다주었다. 특히 저렴한 비용으로 IT 자원을 빌려 쓸 수 있고, 인프라를 구축할 필요가 없으며, 가상화를 이용한 다양한 컴퓨팅 환경을 제공받을 수 있는 것은 클라우드 컴퓨팅 환경이 인기를 얻을 수밖에 없는 이유이기도 하다. 이러한 클라우드 컴퓨팅에서는 다양한 접속 방법과 서비스 제공 범위가 넓어지고 있는 것과 비례하여 공격 위협의 범위 또한 넓어지고 있다. 따라서 악의적인 의도를 갖는 다양한 공격으로부터 자원을 보호해 줄 수 있는 침입탐지시스템이 반드시 필요하다. 본 논문에서는 자원의 공유와 가상화가 갖는 특성으로 인해 침입이 발생하였을 때 다른 컴퓨팅 환경에 비해 그 피해가 매우 큰 클라우드 컴퓨팅 환경에서 침입탐지시스템이 가져야할 특징에 대하여 분석하였다.

• 인터넷정보학회논문지
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• 제16권5호
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• pp.75-86
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• 2015

최근 주목 받고 있는 정보기술분야 중 하나인 IoT(Internet of Things) 환경은 센서와 액츄에이터로 구성된 다양한 디바이스들이 네트워크에 연결되어 정보를 수집 및 공유하면서 상호작용이 가능한 컴퓨팅 환경이다. 하드웨어, 네트워크 기술의 발전으로 인한 IoT 디바이스의 보편화와 IoT 서비스에 대한 사회적인 요구의 증가에 따라, IoT 애플리케이션의 사용성이 증대될 것으로 기대하고 있다. 그러나 IoT 환경에서는 전통적인 소프트웨어 연구에서 다루어지지 않았던 다양한 종류의 결함이 발생할 수 있어, 신뢰성 있는 IoT 애플리케이션을 개발하는 데에 어려움이 있다. 이러한 문제를 해결하기 위하여, 본 논문에서는 IoT 결함을 분류하고, 분류된 결함들의 원인과 증상을 분석한다. 그리고 분석 결과를 기반으로 서비스 실행 시에 발생 할 수 있는 결함을 관리하기 위한 프로세스와 그 프로세스 안에서 수행되는 기법을 제안한다. 본 연구에서 제안하는 프로세스와 관리 기법을 활용하여 결함 관리가 필요한 IoT 애플리케이션의 개발 비용을 줄일 수 있다.

• 정보처리학회지
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• 제17권2호
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• pp.18-29
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• 2010

In this paper, we surveyed SSO based security management including the knowledge domain of the area of cloud and its relevant components. Cloud computing refers to the delivery of software and other technology services over the Internet by a service provider. SSO refers to the ability to log on to a single security system once, rather than logging on separately to multiple security systems. Existing SSO solutions in cloud computing environment suggest several methods. SSO-based security Issues illustrate these key items in cloud computing environment such as risks and security vulnerabilities of SSO. SSO supports for multiple and different domains in cloud computing environment.

• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.89-100
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• 2022

With the advancement in the Internet of things Technology (IoT) cloud computing, billions of physical devices have been interconnected for sharing and collecting data in different applications. Despite many advancements, some latency - specific application in the real world is not feasible due to existing constraints of IoT devices and distance between cloud and IoT devices. In order to address issues of latency sensitive applications, fog computing has been developed that involves the availability of computing and storage resources at the edge of the network near the IoT devices. However, fog computing suffers from many limitations such as heterogeneity, storage capabilities, processing capability, memory limitations etc. Therefore, it requires an adequate task scheduling method for utilizing computing resources optimally at the fog layer. This work presents a comprehensive review of different task scheduling methods in fog computing. It analyses different task scheduling methods developed for a fog computing environment in multiple dimensions and compares them to highlight the advantages and disadvantages of methods. Finally, it presents promising research directions for fellow researchers in the fog computing environment.