• Journal of KIISE:Databases
• /
• v.33 no.4
• /
• pp.409-422
• /
• 2006

In general, there can be many reusable intermediate results due to the overlapped windows and periodic execution intervals among Multiple Continuous Queries (MCQ) on data streams. In this regard, we propose an efficient greedy algorithm for a global query plan construction, called GAGPC. GAGPC first decides an execution cycle and finds the maximal Set(s) of Related execution Points (SRP). Next, GAGPC constructs a global execution plan to make MCQ share common join-fragments with the highest benefit in each SRP. The algorithm suggests that the best plan of the same continuous queries may be different according to not only the existence of common expressions, but the size of overlapped windows related to them. It also reflects to reuse not only the whole but partial intermediate results unlike previous work. Finally, we show experimental results for the validation of GAGPC.

• The KIPS Transactions:PartC
• /
• v.9C no.1
• /
• pp.97-106
• /
• 2002

In 3GPP2 standard, MIP is used and a PDSN performs the function of FA to support macro mobility. When a MS is roaming from a PDSN area to another, the mobility supported is called macro mobility, while it is called micro mobility when a MS is roaming from a RN area to another in a PDSN area. Since a PDSN performs the function of FA in 3GPP2 standard, it is possible to support mobility but its mechanism is actually for supporting macro mobility, not for micro mobility, thus it is weak in processing fast and seamless handoff to support micro mobility. In this paper, we suggest the seamless handoff algorithm barred on multicast group mechanism to support micro mobility. Depending on the moving direction and velocity of a MS, the suggested algorithm constructs a multicast group of RNs on the forecasted MS's moving path, and maximally delays RNs'joining to a multicast group to increase the network efficiency. Moreover, to resolve the buffer overhead problem of the existent multicast scheme, the algorithm suggests that each RN buffers data only after the forecasted handoff time. To prove deadlock freeness and liveness of the algorithm. we use state transition diagrams, a Petri-net modeling and its reachability tree. Then, we evaluate the performance by simulation.

• Journal of the Korean Society of Safety
• /
• v.32 no.3
• /
• pp.141-150
• /
• 2017

A rapid increase in traffic accidents involving senior vehicle occupants has been an issue in Korea because of the aging of the population occurring at one of the fastest rates in the world; unfortunately, few studies beyond several looking at the effect of senior occupants on the level of accident injury severity can be found in the literature. A Multinomial logit model was estimated with Newton-Raphson algorithm to perform bias-reducing penalized likelihood optimization. Model covariates integral to developing the model were included, but the main focus was on the interaction of seating position and injury to senior vehicle occupants. It was found that the likelihood of an accident resulting in a fatality increased: 2.2 times for the driver seat, 2.7 times for the front passenger seat, and even 6.7 times for the rear seat. A mandatory seatbelt law to be extended to the rear seat needs to pass the assembly as soon as possible, and government, industry, and safety groups should be encouraged to join forces to strongly carry out targeted campaigns for the wearing of seatbelts in all vehicle seats to enhance the safety of senior occupants as well as other occupants who are vulnerable to road traffic accidents.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.11
• /
• pp.5489-5511
• /
• 2019

The performance of evolutionary algorithms can be seriously weakened when constraints limit the feasible region of the search space. In this paper we present a constrained multi-objective optimization algorithm based on adaptive ε-truncation (ε-T-CMOA) to further improve distribution and convergence of the obtained solutions. First of all, as a novel constraint handling technique, ε-truncation technique keeps an effective balance between feasible solutions and infeasible solutions by permitting some excellent infeasible solutions with good objective value and low constraint violation to take part in the evolution, so diversity is improved, and convergence is also coordinated. Next, an exponential variation is introduced after differential mutation and crossover to boost the local exploitation ability. At last, the improved crowding density method only selects some Pareto solutions and near solutions to join in calculation, thus it can evaluate the distribution more accurately. The comparative results with other state-of-the-art algorithms show that ε-T-CMOA is more diverse than the other algorithms and it gains better in terms of convergence in some extent.

• Journal of KIISE:Computer Systems and Theory
• /
• v.28 no.1_2
• /
• pp.1-10
• /
• 2001

본 논문에서는 부쉬 트리를 할당 트리로 변환한 후 결합 연산을 수행하면서 실제 실행시간을 동적으로 계산하고 그 결과에 의해 실시간에 프로세서를 할당하는 동적 프로세서 할당 기법을 이용한 파이프라인 해쉬 결합 알고리즘을 제안하였다. 프로세서를 할당하는 과정에서 초기 릴레이션의 기본 정보만을 이용하여 미리 프로세서를 할당하는 기존의 정적 프로세서 할당 기법은 정확한 실행시간을 예측할 수 없었다. 따라서 본 논문에서는 할당 트리 각 노드의 실행결과를 포함한 결합 과정 중의 정보를 다음 노드의 실행시간에 충분히 반영하는 동적 프로세서 할당 기법을 제안하였으며, 이로써 프로세서를 효율적으로 분배하고 전체적인 실행시간을 최소화하였다. 또한 전체적인 질의 실행시간을 줄이기 위하여 결합 가능성이 없는 튜플들을 제거한 후 결합 연산을 수행할 수 있도록 해쉬 필터 기법을 이용하였다. 결합 연산을 수행하기에 앞서 모든 결합 속성 값에 대해 해쉬 필터를 생성하는 정적 필터 기법은 모든 결합 연산의 중간 결과로 발생할 수 있으나 최종 결과 릴레이션의 튜플이 될 수 없는 튜플들까지도 모두 추출이 가능하다. 따라서 각각의 결합 연산 직전에 해쉬 필터를 생성하는 동적 필터 기법에 비해 결합 가능성이 없는 튜플을 최대한 제거할 수 있으며 이로써 결합 연산의 실행비용을 크게 줄일 수 있었다.

• The KIPS Transactions:PartD
• /
• v.13D no.6 s.109
• /
• pp.797-806
• /
• 2006

In the data warehouse environment, materialized views are typically used to support efficient query processing. Materialized views need to be updated when source data change. Since the update of the views need impose a significant overhead, it is essential to update the views efficiently. Though various view maintenance strategies have been discussed in the past, the efficient maintenance of SPJ materialized views has not been sufficiently investigated. In this paper, we propose an efficient incremental view maintenance method for SPJ materialized views that minimizes the total accesses to data sources. The proposed method finds an optimal view maintenance strategy using a dynamic programming algorithm. We also present various experimental results that shows the efficiency of our proposed method.

• Journal of Communications and Networks
• /
• v.10 no.1
• /
• pp.79-88
• /
• 2008

In this paper, we propose efficient peer assignment algorithms for low-latency transmission of scalable coded images in peer-to-peer networks, in which peers may dynamically join and leave the networks. The objective of our algorithm is to minimize the transmission time of a requested image that is scalable coded. When an image is scalable coded in different bit rates, the bit stream encoded in a lower bit rate is a prefix subset of the one encoded in a higher bit rate. Therefore, a peer with the same requested image coded in any bit rate, even when it is different from the requested rate, may work as a supplying peer. As a result, when a scalable coded image is requested, more supplying peers can be found in peer-to-peer networks to help with the transfer. However, the set of supplying peers is not static during transmission, as the peers in this set may leave the network or finish their transmission at different times. The proposed peer assignment algorithms have taken into account the above constraints. In this paper, we first prove the existence of an optimal peer assignment solution for a simple identity permutation function, and then formulate peer assignment with this identity permutation as a mixed-integer programming problem. Next, we discuss how to address the problem of dynamic peer departures during image transmission. Finally, we carry out experiments to evaluate the performance of proposed peer assignment algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.5
• /
• pp.1554-1566
• /
• 2014

Cloud Computing allows application providers seamlessly scaling their services and enables users scaling their usage according to their needs. In this paper, using queuing game model, we present service scheduling schemes which are used in software as a service (SaaS). The object is maximizing the Cloud Computing platform's (CCP's) payoff via controlling the service requests whether to join or balk, and controlling the value of CCP's admission fee. Firstly, we treat the CCP as one virtual machine (VM) and analyze the optimal queue length with a fixed admission fee distribution. If the position number of a new service request is bigger than the optimal queue length, it balks. Otherwise, it joins in. Under this scheme, the CCP's payoff can be maximized. Secondly, we extend this achievement to the multiple VMs situation. A big difference between single VM and multiple VMs is that the latter one needs to decide which VM the service requests turn to for service. We use a corresponding algorithm solve it. Simulation results demonstrate the good performance of our schemes.

• International Journal of Internet, Broadcasting and Communication
• /
• v.7 no.1
• /
• pp.42-48
• /
• 2015

Generally, the current commercial cloud system is hosted by the centralization large datacenter. However, the other clouding forms existed and one of them is the P2P cloud. The P2P Cloud is a distributed systems, is freedom to join and leave and is possible to provide the IaaS. Commonly, P2P Cloud System is based on Pure-P2P System. Since a number of connection paths exist, it has a high reliability and easily scalability of the network. However, there are disadvantages of the slow rate of route because of looking up the all peers in order to search for the peer. In this paper, it proposes the P2P cloud system based on super-peer P2P. Super-peer P2P system has fast routing time, because of searching for cluster unit and it also can has high reliability and high scalability. We designs the super Peer cloud service and proposes the system model and Resource Allocation Algorithm for IaaS in Super peer P2P environment.

• The Journal of Korea Robotics Society
• /
• v.1 no.1
• /
• pp.25-35
• /
• 2006

Improving practicality of SLAM requires various sensors to be fused effectively in order to cope with uncertainty induced from both environment and sensors. In this case, combining sonar and vision sensors possesses numerous advantages of economical efficiency and complementary cooperation. Especially, it can remedy false data association and divergence problem of sonar sensors, and overcome low frequency SLAM update caused by computational burden and weakness in illumination changes of vision sensors. In this paper, we propose a SLAM method to join sonar sensors and stereo camera together. It consists of two schemes, extracting robust point and line features from sonar data and recognizing planar visual objects using multi-scale Harris corner detector and its SIFT descriptor from pre-constructed object database. And fusing sonar features and visual objects through EKF-SLAM can give correct data association via object recognition and high frequency update via sonar features. As a result, it can increase robustness and accuracy of SLAM in indoor environment. The performance of the proposed algorithm was verified by experiments in home -like environment.