• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권1호
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• pp.204-226
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• 2018

Big data processing applications have been migrated into cloud gradually, due to the advantages of cloud computing. Hadoop Distributed File System (HDFS) is one of the fundamental support systems for big data processing on MapReduce-like frameworks, such as Hadoop and Spark. Since HDFS is not aware of the co-location of virtual machines in the cloud, the default scheme of block allocation in HDFS does not fit well in the cloud environments behaving in two aspects: data reliability loss and performance degradation. In this paper, we present a novel location-aware data block allocation strategy (LDBAS). LDBAS jointly optimizes data reliability and performance for upper-layer applications by allocating data blocks according to the locations and different processing capacities of virtual nodes in the cloud. We apply LDBAS to two stages of data allocation of HDFS in the cloud (the initial data allocation and data recovery), and design the corresponding algorithms. Finally, we implement LDBAS into an actual Hadoop cluster and evaluate the performance with the benchmark suite BigDataBench. The experimental results show that LDBAS can guarantee the designed data reliability while reducing the job execution time of the I/O-intensive applications in Hadoop by 8.9% on average and up to 11.2% compared with the original Hadoop in the cloud.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권5호
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• pp.2310-2345
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• 2017

With the emergence of the Internet of Things (IoT) the world is projecting towards a scenario where every object in the world (including humans) acts as a sender and receiver of data and if we were to see that concept mature we would soon be talking of billions more users of the cloud networks. The cloud technology is a very apt alternative to permanent storage when it comes to bulk storage and reporting. It has however shown weaknesses concerning real-time data accessibility and processing. The bandwidth availability of the cloud networks is limited and combined with the highly centralized storage structure and geographical vastness of the network in terms of distance from the end user the cloud just does not seem like a friendly environment for real-time IOT data. This paper aims at highlighting the importance of Flavio Bonomi's idea of Fog Computing which has been glamorized and marketed by Cisco but has not yet been given a proper service architecture that would explain how it would be used in terms of various service models i-e IaaS, PaaS and SaaS, of the Cloud. The main contribution of the paper would be models for IaaS, PaaS and SaaS for Fog environments. The paper would conclude by highlighting the importance of the presented models and giving a consolidated overview of how they would work. It would also calculate the respective latencies for fog and cloud to prove that our models would work. We have used CloudSim and iFogSim to show the effectiveness of the paradigm shift from traditional cloud architecture to our Fog architecture.

• 천문학회보
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• 제36권2호
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• pp.131.1-131.1
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• 2011

We present applications of clustering methods to detect variability in massive astronomical time series data. Focusing on variability of bright stars, we use clustering methods to separate possible variable sources from other time series data, which include intrinsically non-variable sources and data with common systematic patterns. We already finished the analysis of the Northern Sky Variability Survey data, which include about 16 million light curves, and present candidate variable sources with their association to other data at different wavelengths. We also apply our clustering method to the light curves of bright objects in the SuperWASP Data Release 1. For the analysis of the SuperWASP data, we exploit a elastically configurable Cloud computing environments that the KISTI Supercomputing Center is deploying. Two quite different configurations are incorporated in our Cloud computing test bed. One system uses the Hadoop distributed processing with its distributed file system, using distributed processing with data locality condition. Another one adopts the Condor and the Lustre network file system. We present test results, considering performance of processing a large number of light curves, and finding clusters of variable and non-variable objects.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권3호
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• pp.971-989
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• 2015

With the development of cloud computing, more and more Web services are deployed on geo-distributed datacenters and are offered to cloud users all over the world. Through service composition technologies, these independent fine-grain services can be integrated to value-added coarse-grain services. During the composition, a number of Web services may provide the same function but differ in performance. In addition, the distribution of cloud datacenters presents a geographically dispersive manner, which elevates the impact of the network on the QoS of composite services. So it is important to select an optimal composition path in terms of QoS when many functionally equivalent services are available. To achieve this objective, we first present a graph model that takes both QoS of Web services and QoS of network into consideration. Then, a novel approach aiming at selecting the optimal composition path that fulfills the user's end-to-end QoS requirements is provided. We evaluate our approach through simulation and compare our method with existing solutions. Results show that our approach significantly outperforms existing solutions in terms of optimality and scalability.

• 천문학회지
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• 제34권3호
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• pp.157-166
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• 2001

The molecular cloud associated with the H II region S301 has been mapped in the J = 1-0 transitions of $^{12}CO$ and $^{13}CO$ using the 13.7 m radio telescope of Taeduk Radio Astronomy Observatory. The cloud is elongated along the north-south direction with two strong emission components facing the H II region. Its total mass is $8.7 {\times} 10^3 M{\bigodot}$. We find a velocity gradient of the molecular gas near the interface with the optical H II region, which may be a signature of interaction between the molecular cloud and the H II region. Spectra of CO, CS, and HCO+ exhibit line splitting even in the densest part of the cloud and suggests the clumpy structure. The radio continuum maps show that the ionzed gas is distributed with some asymmetry and the eastern part of the H II region is obscured by the molecular cloud. We propose that the S301 H II region is at the late stage of the champagne phase, but the second generation of stars has not yet been formed in the postshock layer.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권9호
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• pp.4165-4187
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• 2016

As an emerging technology, cloud computing is a revolution in information technology that attracts significant attention from both public and private sectors. In this paper, we proposed a dynamic approach for live migration to obviate overloaded machines. This approach is applied on OpenStack, which rapidly grows in an open source cloud computing platform. We conducted a cost-aware dynamic live migration for virtual machines (VMs) at an appropriate time to obviate the violation of service level agreement (SLA) before it happens. We conducted a preemptive migration to offload physical machine (PM) before the overload situation depending on the predictive method. We have carried out a distributed model, a predictive method, and a dynamic threshold policy, which are efficient for the scalable environment as cloud computing. Experimental results have indicated that our model succeeded in avoiding the overload at a suitable time. The simulation results from our solution remarked the very efficient reduction of VM migrations and SLA violation, which could help cloud providers to deliver a good quality of service (QoS).

• International Journal of Contents
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• 제10권1호
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• pp.62-67
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• 2014

Usually, cloud storage systems are developed based on DFS (Distributed File System) for scalability and reliability reasons. DFSs are designed to improve throughput than IO response time, and therefore, they are appropriate for batch processing jobs. Recently, cloud storage systems have been used for update intensive applications such as OLTP and so on. However, in DFSs, in-place update operations are not carefully considered. Therefore, when updates are frequent, I/O performance of DFSs are degraded significantly. DFSs with RAID techniques have been proposed to improve their performance and reliability. Their performance degradation caused by frequent update operations can be more significant. In this paper, we propose an in-place update method for DFS RAID exploiting a differential logging technique. The proposed method reduces the I/O costs, network traffic and XOR operation costs for RAID. We demonstrate the efficiency of our proposed in-place update method through various experiments.

• 한국전자통신학회논문지
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• 제5권6호
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• pp.672-677
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• 2010

최근 대규모 센서 네트워크의 구축이 증가하면서 대규모의 센서 데이터를 효율적으로 관리하는 시스템이 요구되고 있다. 본 논문에서는 저비용, 높은 확장성 그리고 고 효율성을 지닌 클라우드 기반의 센서 데이터 관리 시스템을 제안한다. 제안된 시스템에서는 센서 데이터는 클라우드 게이트웨이를 통해 클라우드로 전송되며 이때 이상상황 검출과 이벤트 처리가 수행된다. 클라우드로 전송된 센서 데이터는 분산 컬럼 지향 데이터 베이스인 하둡 HBase에 저장되며 맵리듀스 모델 기반의 질의처리 모듈을 통해 병렬 처리된다. 처리된 결과는 REST 기반의 웹서비스를 통해 제공되므로 다양한 플랫폼의 응용프로그램과 연동이 가능하다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권1호
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• pp.1-20
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• 2018

Service composition in the Inter-Cloud raises new challenges that are caused by the different Quality of Service (QoS) requirements of the users, which are served by different geo-distributed Cloud providers. This paper aims to explore how to select and compose such services while considering how to reach high efficiency on cost and response time, low network latency, and high reliability across multiple Cloud providers. A new hybrid multi-objective evolutionary algorithm to perform the above task called LS-NSGA-II-DE is proposed, in which the differential evolution (DE) algorithm uses the adaptive mutation operator and crossover operator to replace the those of the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) to get the better convergence and diversity. At the same time, a Local Search (LS) method is performed for the Non-dominated solution set F{1} in each generation to improve the distribution of the F{1}. The simulation results show that our proposed algorithm performs well in terms of the solution distribution and convergence, and in addition, the optimality ability and scalability are better compared with those of the other algorithms.

• 한국통신학회논문지
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• 제38B권10호
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• pp.775-784
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• 2013

이동통신 사업자들은 자신의 망 총소유비용을 줄이면서 데이터 폭증에 대처하기 위한 다양한 기술적인 대책 들을 강구하고 있다. 이 논문에서는 그러한 기술적인 대책의 하나로써 클라우드 기지국이란 새로운 기지국 구조에서 조정 다중점 송수신 운용에 따른 시스템 용량 및 이동성 성능에 관련된 모의실험 결과를 도출한다. 그 결과는 조정 다중점 송수신이 적용되는 클라우드 기지국의 규모 및 적용 영역에 따라 시스템 용량 및 이동성 성능도 개선될 수 있다는 것을 관찰할 수 있었으며 이러한 상호 인과 관계들은 실제 이동통신 사업자의 망 운용에 있어서 하나의 실용적 지침을 제공할 수 있다.