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Adaptive Continuous Query Reoptimization over Data Streams
PARK, Hong Kyu,LEE, Won Suk The Institute of Electronics, Information and Comm 2009 IEICE transactions on information and systems Vol.92 No.7
<P>A data stream is a series of massive unbounded tuples continuously generated at a rapid rate. Continuous queries for data streams should be processed continuously, so that a strict time constraint is required. In most previous research studies, in order to guarantee this constraint, the evaluation order of join predicates in a continuous query is optimized using a greedy strategy. However, because a greedy strategy traces only the first promising plan, it often finds a suboptimal plan. To reduce the possibility of producing a suboptimal plan, in this paper, we propose an improved scheme, <I>k-Extended Greedy Algorithm (k-EGA)</I>, that simultaneously examines a set of promising plans and reoptimize an execution plan adaptively. The number of promising plans is flexibly controlled by a user-defined range variable. The scheme verifies the performance of the current plan periodically. If the plan is no longer efficient, a newly optimized plan is generated. The performance of the proposed scheme is verified through various experiments to identify its various characteristics.</P>
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AUTOMATIC TRANSMISSION SHIFT STRATEGY BASED ON GREEDY ALGORITHM USING PREDICTED VELOCITY
Dongwon Jeoung,Kyunghan Min,선우명호 한국자동차공학회 2020 International journal of automotive technology Vol.21 No.1
Control strategies for the vehicle equipped with an automatic transmission greatly affects the fuel economy and drivability. In general, the gear shift of automatic transmission is controlled based on the two-dimensional lookup tables. The lookup tables are calibrated based on the experimental results at a steady state condition. However, this method has a limitation on improving the fuel efficiency in a dynamic driving environment like an urban condition. In order to improve the fuel efficiency, this study proposes an optimal gear shift strategy based on the greedy control method using the predicted velocity. Since future driving conditions can be estimated using predicted velocity, optimal gear shifting is searched using a greedy algorithm based on the predicted velocity. A PI-type driver model and powertrain model are designed to calculate the forecasting vehicle states after gear shifting with predicted velocity. The proposed strategy was validated through the simulation of the urban driving cycle using various time period predicted velocity. Results show fuel efficiency was improved by up to 1.6 % while shiftbusyness is prevented compared with the shift pattern which focused on fuel economy. As a result, the proposed strategy is affordable for improving not only the fuel economy but also the drivability in the dynamic driving environment.
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Mobile Robot Path Planning Based on Improved Q Learning Algorithm
Jiansheng Peng 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.7
For path planning of mobile robot, the traditional Q learning algorithm easy to fall into local optimum, slow convergence etc. issues, this paper proposes a new greedy strategy, multi-target searching of Q learning algorithm. Don't need to create the environment model, the mobile robot from a single-target searching transform into multi-target searching an unknown environment, firstly, by the dynamic greedy strategy exploring interim to use unknown environment, improve learning ability that mobile robot learn the environment, improve the convergence of the mobile robot speed. And a large number of improved Q-learning algorithms are applied to mobile robot optimization simulation in unknown environment, by comparing with traditional Q algorithm, theory and experiment proved that improved Q-learning algorithm speed up the convergence rate of the robot, improve collision avoidance capability and learning efficiency.
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Integrate Advantage of Geographic Routing and Reactive Mechanism for Aeronautical Ad Hoc Networks
Xiaoheng Tan,Xiaonan Hu,Pengfei Qu,Zhengnan Zhu,Yan Zhang 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.7
Large scale range and high dynamic topology are the two major features of Aeronautical Ad Hoc Networks (AANETs), which present severe challenges to provide efficient and reliable data packet delivery in aviation communication networks. Geographic routing has been studied as an attractive option for routing in aeronautical networks due to its simplicity and scalability. However there are still some problems such as low packet delivery ratio and less reliability for long dynamic links. In this paper, we improve the greedy forwarding strategy and start with the idea of integrating reactive routing mechanism with geographic routing protocol, referred to as IRG (Improved Reactive and Geographic) routing protocol. Variety simulations have been performed to evaluate the performance of the proposed routing protocol, and the results show that it can increase the packet delivery ratio efficiently.
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Temperature Parameter Control of Q value-based Dynamic Programming with Boltzmann Distribution
Shanqing Yu,Shingo Mabu,Manoj Kanta Mainali,Shinji Eto,Kaoru Shimada,Kotaro Hirasawa 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
In order to improve the efficiency of traffic systems in the global perspective, we proposed a dynamic routing strategy, where the optimal traveling time for each Origin-Destination (OD) pair is calculated by extended Q value-based Dynamic Programming and the global optimum routes are produced by adjusting the temperature parameter in Boltzmann distribution. In this paper, how to control the temperature parameter is discussed in detail depending on the dynamic traffic conditions. What’s more, various temperature parameter control strategies of the Q value-based Dynamic Programming with Botzmann distribution are tested in the simulations. The results show that adopting suitable temperature parameter control strategy could improve the efficiency of the traffic systems effectively.
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정동원(Dongwon Jeong) 한국정보과학회 2014 정보과학회 컴퓨팅의 실제 논문지 Vol.20 No.3
이 논문에서는 빠른 근거리 예측 환경을 위한 사용자 이동 경로 예측 알고리즘을 제안한다. 지금까지 경로 예측 문제에 대한 많은 연구가 진행되어 왔다. 그러나 대부분 사용자의 최종 목적지 예측에 초점을 두고 있으며, 실시간으로 빠른 근거리 예측이 요구되는 응용에 적합하지 않다. 또한 기존 연구는 현재 사용자 정보를 이용하여 패턴 추출 및 학습이 불가능한 경우에 적용하기 어렵다. 따라서 이 논문에서는 이러한 기존 연구의 한계 극복을 위한 새로운 경로 예측 알고리즘을 제안한다. 제안 알고리즘에 적합한 정보 관리 구조를 정의하고 제안 알고리즘의 장점을 보이기 위해 성능 평가 결과를 보인다. This paper proposes a novel algorithm to predict user paths for fast and close-range prediction environments. Until now, much research has been conducted on the path prediction issue. However, most of this research focuses on prediction of the final destination of users and is not suitable for an application that requires a fast and close-range prediction in real time. The existing works also cannot be applied to a situation where a pattern extraction and reasoning with the current user information is not available. Therefore, this paper proposes a novel path prediction algorithm to overcome the limitations of the existing approaches. This paper defines a proper information management structure for the proposed algorithm, and a performance evaluation is conducted to show the contributions of the proposed algorithm.
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