• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1299-1319
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• 2017

This paper presents a scalable multiple camera collaboration strategy for active tracking applications in large areas. The proposed approach is based on distributed mechanism but emulates the master-slave mechanism. The master and slave cameras are not designated but adaptively determined depending on the object dynamic and density distribution. Moreover, the number of cameras emulating the master is not fixed. The collaboration among the cameras utilizes global and local sectors in which the visual correspondences among different cameras are determined. The proposed method combines the local information to construct the global information for emulating the master-slave operations. Based on the global information, the load balancing of active tracking operations is performed to maximize active tracking coverage of the highly dynamic objects. The dynamics of all objects visible in the local camera views are estimated for effective coverage scheduling of the cameras. The active tracking synchronization timing information is chosen to maximize the overall monitoring time for general surveillance operations while minimizing the active tracking miss. The real-time simulation result demonstrates the effectiveness of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.9
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• pp.2739-2763
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• 2024

In wide area SDP networks, the failure of SDP components caused by malicious attacks will be accompanied by different deployment locations, profoundly affecting network service latency. However, traditional deployment methods based on prior knowledge are no longer applicable to dynamic SDP networks. This article proposes a dynamic and dimensionally variable deployment mechanism DDPG-SDPCR for SDP components based on DDPG, which enhances the network's endogenous security capability and improves attack tolerance. Based on this, we constructed corresponding mathematical models for latency, load balancing, and attack tolerance. The DDPG-SDPCR mechanism dynamically deploys new SDP nodes to replace faulty nodes based on the real-time status of the network, thereby achieving imperceptible attack tolerance for users. We have implemented a wide area SDP prototype with endogenous security capabilities and evaluated it under different network topologies, traffic sizes, and network attacks. The evaluation results indicate that under high traffic conditions, our proposed redeployment mechanism outperforms the baseline by 36.42% in latency, and only increases by 19.24% compared to the non attacked situation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.4
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• pp.491-508
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• 2010

In peer-to-peer (P2P) on-demand streaming networks, the alleviation of server load depends on reciprocal stream sharing among peers. In general, on-demand video services enable clients to watch videos from beginning to end. As long as clients are able to buffer the initial part of the video they are watching, on-demand service can provide access to the video to the next clients who request to watch it. Therefore, the key challenge is how to keep the initial part of a video in a peer's buffer for as long as possible, and thus maximize the availability of a video for stream relay. In addition, to address the issues of delivering data on lossy network and providing scalable quality of services for clients, the adoption of multiple description coding (MDC) has been proven as a feasible resolution by much research work. In this paper, we propose a novel caching scheme for P2P on-demand streaming, called Dynamic Buffering. The proposed Dynamic Buffering relies on the feature of MDC to gradually reduce the number of cached descriptions held in a client's buffers, once the buffer is full. Preserving as many initial parts of descriptions in the buffer as possible, instead of losing them all at one time, effectively extends peers’ service time. In addition, this study proposes a description distribution balancing scheme to further improve the use of resources. Simulation experiments show that Dynamic Buffering can make efficient use of cache space, reduce server bandwidth consumption, and increase the number of peers being served.

• The KIPS Transactions:PartC
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• v.19C no.2
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• pp.135-144
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• 2012

All the servers in a traditional server cluster environment are kept On. If the request load reaches to the maximum, we exploit its maximum possible performance, otherwise, we exploit only some portion of maximum possible performance so that the efficiency of server power consumption becomes low. We can improve the efficiency of power consumption by controlling power mode of servers according to load situation, that is, by making On only minimum number of servers needed to handle current load while making Off the remaining servers. In the existing power mode control method, they used a static policy to decide server power mode at a fixed time interval so that it cannot adapt well to the dynamically changing load situation. In order to improve the existing method, we propose a dynamic server power control algorithm. In the proposed method, we keep the history of server power consumption and, based on it, predict whether power consumption increases in the near future. Based on this prediction, we dynamically change the time interval to decide server power mode. We performed experiments with a cluster of 30 PCs. Experimental results show that our proposed method keeps the same performance while reducing 29% of power consumption compared to the existing method. In addition, our proposed method allows to increase the average CPU utilization by 66%.

• Journal of KIISE:Databases
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• v.29 no.3
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• pp.180-192
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• 2002

We investigate the effect of the data skew of join attributes on the performance of a pipelined multi-way hash join method, and propose two new harsh join methods in the shared-nothing multiprocessor environment. The first proposed method allocates buckets statically by round-robin fashion, and the second one allocates buckets dynamically via a frequency distribution. Using harsh-based joins, multiple joins can be pipelined to that the early results from a join, before the whole join is completed, are sent to the next join processing without staying in disks. Shared nothing multiprocessor architecture is known to be more scalable to support very large databases. However, this hardware structure is very sensitive to the data skew. Unless the pipelining execution of multiple hash joins includes some dynamic load balancing mechanism, the skew effect can severely deteriorate the system performance. In this parer, we derive an execution model of the pipeline segment and a cost model, and develop a simulator for the study. As shown by our simulation with a wide range of parameters, join selectivities and sizes of relations deteriorate the system performance as the degree of data skew is larger. But the proposed method using a large number of buckets and a tuning technique can offer substantial robustness against a wide range of skew conditions.

• The KIPS Transactions:PartA
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• v.14A no.5
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• pp.269-278
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• 2007

Caching in a cache sorrel cluster environment has an advantage that minimizes the request and response tine of internet traffic and web user. Then, one of the methods that increases the hit ratio of cache is using the hash function with cooperative caching. It is keeping a fixed size of the total cache memory regardless of the number of cache servers. On the contrary, if there is no cooperative caching, the total size of cache memory increases proportional to the number of cache sowers since each cache server should keep all the cache data. The disadvantage of hashing method is that clients' requests stress a few servers in all the cache servers due to the characteristics of hashing md the overall performance of a cache server cluster depends on a few servers. In this paper, we propose the method that distributes uniformly client requests between cache servers using dynamic server information. We performed experiments using 16 PCs. Experimental results show the uniform distribution o

• Journal of Internet Computing and Services
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• v.8 no.3
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• pp.131-143
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• 2007

The current trends in information technology and intelligent systems use data mining techniques to discover patterns and extract rules from distributed databases. In distributed environment, the extracted rules from data mining techniques can be used in dynamic replications, adaptive load balancing and other schemes. However, transmission of large data through the system can cause errors and unreliable results. This paper proposes the intelligent distributed platform based on dynamic group binding using mobile agents which addresses the use of intelligence in distributed environment. The proposed grouping service implements classification scheme of objects. Data compressor agent and data miner agent extracts rules and compresses data, respectively, from the service node databases. The proposed algorithm performs preprocessing where it merges the less frequent dataset using neuro-fuzzy classifier before sending the data. Object group classification, data mining the service node database, data compression method, and rule extraction were simulated. Result of experiments in efficient data compression and reliable rule extraction shows that the proposed algorithm has better performance compared to other methods.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.05a
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• pp.37-44
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• 2005

최근 들어 개인 휴대 단말기가 보편화되고 GPS와 같은 위치 측정 기술이 발달하면서 이동체의 위치 데이타를 활용한 위치 기반 서비스에 대한 관심이 급증하고 있다. 이러한 위치기반 서비스에서 이용되는 위치 데이타를 관리하기 위해서 일반적으로 단일 노드의 디스크기반 GIS 서버를 사용한다. 그러나, 이동체의 경우 위치의 변화가 매우 빈번하며 대용량이기 때문에 기존의 GIS 서버로는 관리가 어렵다. 그러므로 위치 기반 서비스에서는 이동체의 대용량 위치 데이타를 효율적으로 관리 할 수 있는 위치 데이타 관리 시스템이 요구된다. 따라서 본 논문에서는 이동체의 위치 데이타를 관리하기 위해 제안된 클러스터 기반 분산 컴퓨팅 구조를 갖는 GALIS 아키텍처의 서브 시스템인 SLDS를 확장하여 동적 부하 분산을 지원하는 확장 SLDS를 설계 및 구현하였다. 또한, 실험을 통하여 확장 SLDS가 기존 SLDS에 비하여 더욱 효율적으로 부하 분산을 수행한다는 것을 검증하였다. 본 논문에서 구현한 확장 SLDS는 노드들을 주기적으로 감시하여 위치 데이타를 다수의 노드에 적절히 분산시킴으로써 대용량의 데이타를 효율적으로 관리할 수 있고 시스템의 가용성을 높일 수 있다.

• Journal of KIISE:Information Networking
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• v.28 no.2
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• pp.196-206
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• 2001

네트워크의 보편화와 개인용 컴퓨터의 고급화를 통한 가용 자원의 확장은 분산 컴퓨팅환경에서 작업 부하 균형의 성능 향상을 기대할수 있게 되었다. 하지만 이를 현실화시키기 위해서 다음과 같은 제약 사항을 극복해야 한다. 첫째 네트워크 연결된 각각의 시스템은 이질적인 하드웨어와 운영체제로 구성되어있다. 둘째 네트웍 대역폭의 격심한 변화가 존재하며 상이한 시스템 성능 차이가 존재한다. 셋째 어플리케이션의 요구조건이 상이하다. 본 논문에서는 작업부하 균형에 이동 에이전트 패러다임을 적용하며 위의 문제점을 해결하기 위하여세가지의 사항을 추가한다. 1)이질적인 분산 컴퓨팅 환경에 어플리케이션을 동적으로이식하기 위하여 분산 객체 지향 미들웨어인 CORBA[1] 기반 MASIF[2]를 이용한다. 2)유휴 자원정보에 기반한 어플리케이션의 동적배치를 위하여 지원 감지 모니터링을 실행한다. 3) 다양한 어플리케이션의 요구 조건을 만족시키기 위하여 다양한 모니터링 알고리즘을 동적으로 로드하는 자바 객체, MonitorHandler를 제안한다. 제안한 프레임워크의 실효성을 검증하기 위하여 프로토타입 어플리케이션을 구현하였다. 실험 결과 유휴 자원을 고려한 동적 배치가 정적배치나 초기 정보에 의한 단 한번의 배치보다 각각 57% 와 26%의 성능 향상을 보였다. 제안하는 프레임워크는 작업부하 균형 어플리케이션의 개발을 용이하게 하며 범용성과 확장성을 제공한다.

• Journal of Electrical Engineering and Technology
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• v.8 no.1
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• pp.20-30
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• 2013

An intelligent grid computing architecture is proposed and developed for transient stability constrained total transfer capability evaluation of future smart grid. In the proposed intelligent grid computing architecture, a model of generalized compute nodes with 'able person should do more work' feature is presented and implemented to make full use of each node. A timeout handling strategy called conditional resource preemption is designed to improve the whole system computing performance further. The architecture can intelligently and effectively integrate heterogeneous distributed computing resources around Intranet/Internet and implement the dynamic load balancing. Furthermore, the robustness of the architecture is analyzed and developed as well. The case studies have been carried out on the IEEE New England 39-bus system and a real-sized Chinese power system, and results demonstrate the practicability and effectiveness of the intelligent grid computing architecture.