• Journal of KIISE:Databases
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• v.28 no.2
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• pp.153-167
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• 2001

다차원 온라인 분석처리(Multidimensional On-Line Analytical Processing: MOLAP)에서 집계 연산은 중요한 기본 연산이다. 기존의 MOLAP 집계 연산은 다차원 배열 구조를 기반으로 한 파일 구조에 대해서 연구되어 왔다. 이러한 파일 구조는 편중된 분포를 갖는 데이터에서는 잘 동작하지 못한다는 단점이 있다. 본 논문에서는 편중된 분포에도 잘 동작하는 다차원 파일구조를 사용한 집계 알고리즘을 제안한다. 먼저, 새로운 분리-포함 분할이라는 개념을 사용한 집계 연산 처리 모델을 제안한다. 집계 연산 처리에서 분리-포함 분할 개념을 사용하면 페이지들의 액세스 순서를 미리 알아 낼 수 있다는 특징을 가진다. 그리고, 제안한 모델에 기반하여 원-패스 버퍼 크기(one-pass buffer size)를 사용하여 집계 연산을 처리하는 원-패스 집계 알고리즘을 제안한다. 원-패스 버퍼 크기란 페이지 당 한 번의 디스크 액세스를 보장하기 위해 필요한 최소 버퍼 크기이다. 또한, 제안한 집계 연산 처리 모델 하에서 제안된 알고리즘이 최소의 원-패스 버퍼 크기를 갖는다는 것을 증명한다. 마지막으로, 많은 실험을 통하여 이론적으로 구한 원-패스 버퍼 크기가 실제 환경에서 정확히 동작함을 실험적으로 확인하였다. 리 알고리즘은 미리 알려진 페이지 액세스 순서를 이용하는 버퍼 교체 정책을 사용함으로써 최적의 원-패스 버퍼 크기를 달성한다. 제안하는 알고리즘을 여 러 집계 질의가 동시에 요청되는 다사용자 환경에서 특히 유용하다. 이는 이 알고리즘이 정규화 된 디스크 액세스 횟수를 1.0으로 유지하기 위해 반드시 필요한 크기의 버퍼만을 사용하기 때문이다.

• Journal of Communications and Networks
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• v.1 no.2
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• pp.89-98
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• 1999

In a synchronization (sync) $network^1$containing N nodes, it is shown (Theorem 1c) that an arbitrarily connected sync network & is the union of a countable set of isolated connecting sync networks${&_i,i= 1,2,.., L}, I.E., & = \bigcup_{I=1}^L&_i$ It is shown(Theorem 2e) that aconnecting sync network is the union of a set of disjoint irreducible subnetworks having one or more nodes. It is further shown(Theorem 3a) that there exists at least one closed irreducible subnetwork in $&_i$. It is further demonstrated that a con-necting sync network is the union of both a master group and a slave group of nodes. The master group is the union of closed irreducible subnetworks in $&_i$. The slave group is the union of non-colsed irre-ducible subnetworks in $&_i$. The relationships between master-slave(MS), mutual synchronous (MUS) and hierarchical MS/MUS ent-works are clearly manifested [1]. Additionally, Theorem 5 shows that each node in the slave group is accessible by at least on node in the master group. This allows one to conclude that the synchro-nization information avilable in the master group can be reliably transported to each node in the slave group. Counting and combinatorial arguments are used to develop a recursive algorithm which counts the number $A_N$ of arbitrarily connected sync network architectures in an N-nodal sync network and the number $C_N$ of isolated connecting sync network in &. EXamples for N=2,3,4,5 and 6 are provided. Finally, network examples are presented which illustrate the results offered by the theorems. The notation used and symbol definitions are listed in Appendix A.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.143-152
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• 2013

Given weighted graph G=(V,E), n=|V|, m=|E|, the minimum cut problem is classified with source s and sink t or without s and t. Given undirected weighted graph without s and t, Stoer-Wagner algorithm is most popular. This algorithm fixes arbitrary vertex, and arranges maximum adjacency (MA)-ordering. In the last, the sum of weights of the incident edges for last ordered vertex is computed by cut value, and the last 2 vertices are merged. Therefore, this algorithm runs $\frac{n(n-1)}{2}$ times. Given graph with s and t, Ford-Fulkerson algorithm determines the bottleneck edges in the arbitrary augmenting path from s to t. If the augmenting path is no more exist, we determine the minimum cut value by combine the all of the bottleneck edges. This paper suggests minimum cut algorithm for undirected weighted graph with s and t. This algorithm suggests MA-merging and computes cut value simultaneously. This algorithm runs n-1 times and successfully divides V into disjoint S and V sets on the basis of minimum cut, but the Stoer-Wagner is fails sometimes. The proposed algorithm runs more than Ford-Fulkerson algorithm, but finds the minimum cut value within n-1 processing times.

• The Transactions of the Korea Information Processing Society
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• v.5 no.10
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• pp.2627-2640
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• 1998

In this paper, we analyze the performance of the virtual cell system[1] for the transmission of IP datagrams in mobile computer communications. A virtual cell consistsof a group of physical cells shose base stationsl are implemented b recote bridges and interconnected via high speed datagram packet switched networks. Host mobility is supported at the data link layer using the distributed hierachical location information of mobile hosts. Given mobility and communication ptems among physical cells, the problem of deploying virtual cells is equivalent to the optimization cost for the entire system where interclster communication is more expesive than intracluster communication[2]. Once an iptimal partitionof disjoint clusters is obtained, we deploy the virtual cell system according to the topology of the optimal partition such that each virtual cell correspods to a cluser. To analyze the performance of the virtual cell system, we adopt a BCMP open multipel class queueing network model. In addition to mobility and communication patterns, among physical cells, the topology of the virtual cell system is used to determine service transition probabilities of the queueing network model. With various system parameters, we conduct interesting sensitivity analyses to determine network design tradeoffs. The first application of the proposed model is to determine an adequate network bandwidth for base station networking such that the networks would not become an bottleneck. We also evaluate the network vlilization and system response time due to various types of messages. For instance, when the mobile hosts begin moving fast, the migration rate will be increased. This results of the performance analysis provide a good evidence in demonsratc the sysem effciency under different assumptions of mobility and communication patterns.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.5
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• pp.129-139
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• 2012

Given digraph network $D=(N,A),n{\in}N,a=c(u,v){\in}A$ with source s and sink t, the maximum flow from s to t is determined by cut (S, T) that splits N to $s{\in}S$ and $t{\in}T$ disjoint sets with minimum cut value. The Ford-Fulkerson (F-F) algorithm with time complexity $O(NA^2)$ has been well known to this problem. The F-F algorithm finds all possible augmenting paths from s to t with residual capacity arcs and determines bottleneck arc that has a minimum residual capacity among the paths. After completion of algorithm, you should be determine the minimum cut by combination of bottleneck arcs. This paper suggests maximum adjacency merging and compute cut value method is called by MA-merging algorithm. We start the initial value to S={s}, T={t}, Then we select the maximum capacity $_{max}c(u,v)$ in the graph and merge to adjacent set S or T. Finally, we compute cut value of S or T. This algorithm runs n-1 times. We experiment Ford-Fulkerson and MA-merging algorithm for various 8 digraph. As a results, MA-merging algorithm can be finds minimum cut during the n-1 running times with time complexity O(N).