• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.6
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• pp.672-677
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• 2010

Recently, the efficient management system for large-scale sensor data has been required due to the increasing deployment of large-scale sensor networks. In this paper, we propose a cloud-based sensor data management system with low cast, high scalability, and efficiency. Sensor data in sensor networks are transmitted to the cloud through a cloud-gateway. At this point, outlier detection and event processing is performed. Transmitted sensor data are stored in the Hadoop HBase, distributed column-oriented database, and processed in parallel by query processing module designed as the MapReduce model. The proposed system can be work with the application of a variety of platforms, because processed results are provided through REST-based web service.

• Convergence Security Journal
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• v.15 no.2
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• pp.63-68
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• 2015

Current ICT(Information & Communication Technology) infrastructures (Internet and server/client communication) are struggling for a wide variety of devices, services, and business and technology evolution. Cloud computing originated simply to request and execute the desired operation from the network of clouds. It means that an IT resource that provides a service using the Internet technology. It is getting the most attention in today's IT trends. In the distributed cloud environments, management costs for the network and computing resources are solved fundamentally through the integrated management system. It can increase the cost savings to solve the traffic explosion problem of core network via a distributed Micro DC. However, traditional flooding methods may cause a lot of traffic due to transfer to all the neighbor DCs. Restricted Path Flooding algorithms have been proposed for this purpose. In large networks, there is still the disadvantage that may occur traffic. In this paper, we developed Lightweight Path Flooding algorithm to improve existing flooding algorithm using hop count restriction.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.10
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• pp.259-268
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• 2018

Due to the development of cities and the increase of vehicles, effective control of parking space management service in cities is needed. However, the existing parking lot management system does not provide limited or convenient service in terms of space and time. In this paper, we propose distributed parking space management service based on large scale LPWA (Low-Power Wide-Area). The parking sensor collects parking space information from the parking lot and is transmitted over a low-power wide network. All parking data is processed and analyzed in the IoT cloud. Through a parking space management service system in all cities, users are given the temporal convenience of determining the parking space and the area efficiency of the parking space.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.2
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• pp.302-308
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• 2013

Internet is becoming more common with increasing cloud services have been spreading rapidly. A SLA is agreements between service providers and customers of service providers is how to ensure quality of service. SLA in cloud computing environments from the perspective of the IT service providers to customer satisfaction increase for service quality, it will need to differentiate between competing carriers QoS guarantees with SLA is a very important factor. However, the study of SLA in the cloud is staying in its infancy. In this paper, SLA indices for cloud services defining and use them SLA Management System for QoS guarantee has been implemented. The proposed system using monitoring-based migration policy an open source-based cloud computing platform which Cluster Nodes load distribution of virtual machines assigned to their availability, response time, throughput analysis of what affects and is compared with existing cloud.

• 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).

• Journal of Convergence Society for SMB
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• v.1 no.1
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• pp.29-37
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• 2011

As the area of informatization has been expanding followed by the development of information communication technology, cloud computing which can use infra sources like server, storage, and network in IT area as an efficient service whenever and wherever skyrockets. But users who use cloud computing technology may have some problems like exposure personal data, surveillance on person, and process on commercial purpose on their personal data. This paper proposes a security technique which protect user's privacy by creating imaginary user information not to be used by other people. The proposed technique virtualizes user's information as an anonymity value not to let other people know user's identity by combining PIN code with it and guarantees user's anonymity. Also it can manage and certificate personal information that is important in cloud computing, so that it can solve security problem of cloud computing which centers all informations. Therefore this paper can assist upgrading of the level of information of poor SMBs through safe use of cloud computing.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.07a
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• pp.337-340
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• 2014

클라우드 시스템이 큰 이슈로 떠오르면서 그 기반이 되는 분산 파일 시스템에 관한 연구가 계속되고 있다. 최근 제안된 분산파일 시스템은 대부분 확장 가능하며 신뢰성이 있는 시스템으로 구성되어 있으며 내고장성(Fault tolerance)과 높은 가용성을 위해 데이터 복제 기법을 사용하며 하둡 분산 파일 시스템에서는 블락의 복제수를 기본3개로 지정한다. 그러나 이 정책은 복제수가 많아지면 많아질수록 가용성은 높아지지만 스토리지 또한 증가한다는 단점이 있다. 본 논문에선 이러한 문제점을 해결하기 위해 최소한의 블락 복제수와 복제된 블락을 효율적으로 배치하여 더 좋은 성능과 부하분산(Load Balancing)하기 위한 기법을 제안한다.

• Annual Conference of KIPS
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• 2015.10a
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• pp.174-177
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• 2015

최근 Social, Mobile, IoT 등에 기반한 비즈니스 데이터의 폭증과 함께 이를 저장하고 처리하기 위한 Big Data 플랫폼, 분산 스토리지 기술 등이 사용되고 있다. 최근 제안된 분산 스토리지들은 클라우드 기반 기술과 Scale-Out 아키텍처를 적용하여 데이터의 증가에 대응할 수 있는 구조를 갖추고 있다. 분산 스토리지의 노드가 수백 대 이상으로 증가하는 경우 수작업을 통한 관리방법으로는 운영관리는 불가능하며 자동화된 운영관리와 모니터링 방법이 필요하다. 본 논문에서는 GlusterFS 분산 스토리지를 대상으로 네트워크, 서버, 디스크, 스토리지 서비스 등 시스템 상태를 구간별로 모니터링할 수 있도록 설계하였다. 이를 통해 분산 스토리지 전체 인프라에 대한 모니터링과 스토리지 서비스 수준을 모니터링 할 수 있도록 하였다.

• Annual Conference of KIPS
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• 2013.05a
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• pp.68-70
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• 2013

대량의 데이터를 효과적으로 저장하고 관리하기 위해서 클라우드 스토리지 시스템에서는 분산 파일 시스템 기술이 이용되고 있다. 그러나 데이터가 증가함에 따라 분산 파일 시스템을 이용함에도 스토리지 확장 비용이 증가하게 된다. 본 논문에서는 분산 파일 시스템의 스토리지 확장 비용을 줄이기 위해서 우리는 중복제거 파일 시스템을 적용한 분산 파일 시스템에서의 청크 배치 기법을 제안한다. 오픈 소스 기반의 분산 파일 시스템인 MooseFS 에 중복제거 파일 시스템인 lessfs 를 적용함으로써 스토리지의 가용공간을 늘릴 수 있으며, 이는 스토리지 확장 비용을 줄이는 효과를 가져온다. 또한, 동일한 청크는 같은 청크 서버에 배치 시킴으로써 중복제거 기회를 높인다. 실험을 통해서 제안 시스템의 중복제거량과 성능에 대해서 평가한다.

• Journal of KIISE
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• v.41 no.9
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• pp.674-685
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• 2014

The Knowledge service system needs to infer a new knowledge from indicated knowledge to provide its effective service. Most of the Knowledge service system is expressed in terms of ontology. The volume of knowledge information in a real world is getting massive, so effective technique for massive data of ontology is drawing attention. This paper is to provide the method to infer massive data-ontology to the extent of RDFS, based on cloud computing environment, and evaluate its capability. RDFS inference suggested in this paper is focused on both the method applying MapReduce based on RDFS meta table, and the method of single use of cloud computing memory without using MapReduce under distributed file computing environment. Therefore, this paper explains basically the inference system structure of each technique, the meta table set-up according to RDFS inference rule, and the algorithm of inference strategy. In order to evaluate suggested method in this paper, we perform experiment with LUBM set which is formal data to evaluate ontology inference and search speed. In case LUBM6000, the RDFS inference technique based on meta table had required 13.75 minutes(inferring 1,042 triples per second) to conduct total inference, whereas the method applying the cloud computing memory had needed 7.24 minutes(inferring 1,979 triples per second) showing its speed twice faster.