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- 저자 : ( Keqiu Li ) (검색결과 2 건)
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A Kriging Based Forecasting and Scheduling System for Scientific Computing Cloud Applications
Zhaojun Li,Xinyu Wang,Zheng Li,Xicheng Wang,Keqiu Li 보안공학연구지원센터 2015 International Journal of Grid and Distributed Comp Vol.8 No.3
Regarding to the theories and techniques of cloud computing having been developed and applied in scientific computing field, tasks can be conveniently managed by the cloud platform on the basis of standardized scheduling system with cost (resources consumed) recorded. However, there are two issues which drag the customers’ attention: 1) When will the tasks expect for termination (response time) under a specific resource scheduling; 2) What is the best scheduling solution by considering cost. In order to reply these two questions, a Kriging based forecasting and scheduling system has been proposed in this paper. With the cooperation between the scientific designer and the cloud designer, the design variables for evaluating the cloud applications can be achieved; Kriging surrogate model is then introduced to simulate the approximate functional relationship between the design variables and the response time of the tasks; Sequential quadratic programming optimization algorithm then provides the best scheduling solution for the tasks if cost constraints are to be met. Two real scientific computing cloud applications have been testified on an OpenStack cloud platform, with consequences described in details. The work in this paper has put forward a novel way for the designers and the customers on predictable and reasonable scheduling strategies for the various resource-intensive scientific computing cloud applications with surrogate models and optimization algorithms.
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Multi-Attribute Data Fusion for Energy Equilibrium Routing in Wireless Sensor Networks
( Kai Lin ),( Lei Wang ),( Keqiu Li ),( Lei Shu ) 한국인터넷정보학회 2010 KSII Transactions on Internet and Information Syst Vol.4 No.1
Data fusion is an attractive technology because it allows various trade-offs related to performance metrics, e.g., energy, latency, accuracy, fault-tolerance and security in wireless sensor networks (WSNs). Under a complicated environment, each sensor node must be equipped with more than one type of sensor module to monitor multi-targets, so that the complexity for the fusion process is increased due to the existence of various physical attributes. In this paper, we first investigate the process and performance of multi-attribute fusion in data gathering of WSNs, and then propose a self-adaptive threshold method to balance the different change rates of each attributive data. Furthermore, we present a method to measure the energy-conservation efficiency of multi-attribute fusion. Based on our proposed methods, we design a novel energy equilibrium routing method for WSNs, viz., multi-attribute fusion tree (MAFT). Simulation results demonstrate that MAFT achieves very good performance in terms of the network lifetime.
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