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Business, e-Services, and e-Society, Volume 2, Springer, Boston, pp. 597-604 [4] Eysenbach, G., (2000) Consumer Health Informatics, British Medical Journal, (320), pp. 1713-1716 [5] Fritch, J.W., (2003) Heuristics, Tools, and Systems for Evaluating Internet Information: Helping Users Assess a Tangled Web, Online Information Review, Vol.27(5), pp. 321-327 [6] Google, (2005) Google News Patent Application, In: http://www.webpronews.com/news/ebusinessnews/wpn- 45-20050503GoogleNewsPatentApplicationFullText.html. Accessed in 2010.3 [7] LaMar, J., (2007) Competitive Intelligence Survey Report, In: http://joshlamar.com/documents/CIT Survey Report.pdf [8] Metzger, M., (2007) Making Sense of Credibility on the Web: Models for Evaluating Online Information and Recommendations for Future Research, Journal of the American Society of Information Science and Technology, Vol. 58(13), pp. 2078-2091 [9] Mikroyannidis, A., Theodoulidis, B., Persidis, A., (2006) PARMENIDES: Towards Business Intelligence Discovery from Web Data, In Proc. Of WI, pp.1057-1060 [10] Rainie, L., Hitlin, P., (2007) The Use of Online Reputation and Rating Systems, In: http://www.pewinternet.org/ PPF/r/140/report_display.asp, Accessed in 2010.3 [11] Yamamoto, Y., Tanaka, K., (2009) Finding Comparative Facts and Aspects for Judging the Credibility of Uncertain Facts, Proc. Of WISE, , LNCS 5802, pp. 291-305 196
ISBN 978-952-5726-09-1 (Print) Proceedings of the Second International Symposium on Networking and Network Security (ISNNS ’10) Jinggangshan, P. R. China, 2-4, April. 2010, pp.197-200 Power Aware Job Scheduling with Quality of Service Guarantees: A Preliminary Study Congfeng Jiang 1 , Xianghua Xu 1 , Jian Wan 1 , Jilin Zhang 1 , and Yinghui Zhao 2 1 Grid and Service Computing Technology Lab, Hangzhou Dianzi University, Hangzhou, 310037, China Email :{cjiang,xuxh,wanjian,zhangjilin}@hdu.edu.cn 2 Department of Hydraulic Engineering and Agriculture, Zhejiang Tongji Vocational College of Science and Technology, Hangzhou, 311231, China Email: zhaoyinghuihust@gmail.com Abstract—In large scale server systems, Quality of Service (QoS) performance cannot be guaranteed if only the objective is to minimize the total power consumptions separately. In this paper a power aware feedback control based power aware job scheduling algorithm (PFM) is proposed to minimize power consumption in computing system and to provide QoS guarantees. Simulations and experiments show that the proposed algorithm can reduce power consumptions significantly while still providing QoS guarantees and the performance degradation is acceptable. The results also show that conventional hardware based per-component and system-wide power management methods can save more power consumptions if they are in assistance with job-level adaptation. Index Terms—power aware computing system; job scheduling; Quality of Service (QoS); feedback control I. INTRODUCTION Power consumption has been a major concern for not only large scale computing system but also mobile and embedded systems powered by batteries. With the scale of computing system increases, power consumption has become the major challenge to system performance and reliability [1, 2, 3, and 4]. With DFS/DVS support, processors are simply switched to a sleep mode while transitioning between frequencies and voltages and the system performance will be heavily deteriorated by the transition delay between various frequency and voltage levels in uniprocessors. This situation becomes even worse in multi core processor which does not support per-core DFS/DVS [5]. Conventional hardware based per-component and systemwide power management methods cannot save considerable power consumptions because they are coarse-grained and not adaptive to various fluctuating workloads in real scenarios. Moreover, the system performances, for example, availability, responsiveness, and throughput, do not scale with the number of processors but the power consumption does. Most unfortunately, the performance of the whole system can be deteriorated greatly if the objective is only to minimize the total power consumptions separately, despite of the violations of Quality of Service (QoS) requirements. In this paper, we investigate the feasibility of hardware-software joint regulation for a feedback control based power aware job scheduling algorithm and test the © 2010 ACADEMY PUBLISHER AP-PROC-CS-10CN006 197 algorithm by simulations and real workload. In the proposed algorithm, the feedback based power-aware job scheduler regulates the job dispatching and system performance dynamically for different workload characteristics. A testbed for investigating this scheme is implemented on a web server using Intel quad core processor. The performance and overhead of the algorithm are assessed under different workload. The results show the potential of power consumption reductions for hardware-software joint adaptations. We use a multimeter with USB connection cable to measure the real time power consumption of the system and the measurement results show that fine-grained job-level power aware scheduling can reduce considerable power consumptions. The results also show that the best algorithm varies for different experiment settings and real workload scenarios. In particular, feedback control based power aware job scheduling algorithm is not always better than other algorithms in all the performance dimensions. The performance depends on many factors such as the accuracy of workload characterization, the arrival rate of jobs, frequency-voltage transition delays in specific processors, the frequency/voltage levels available, etc. The remainder of this paper is organized as follows: In section 2 we propose the controlling framework of the power aware job scheduling scheme. In section 3 we present the feedback control based power aware job scheduling algorithm model with QoS guarantees. Then, in Section 4, we present simulation results and real platform experiment results of the proposed scheduling algorithm. We also compare the performance data with conventional power-unaware job scheduling algorithms or job scheduling algorithms without QoS guarantees. Finally, we summarize the work in Section 5. II. FEEDBACK CONTROL MODEL There has been increasing research effort in applying control-theoretic approaches to power and performance management for computer systems such as internet web servers, databases and storage systems. Since today's large scale servers and applications are highly dynamical and change load conditions frequently, feedback control designs may provide desired performance guarantees. In the power aware feedback mechanism, at the beginning of a job scheduling round, the scheduler
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Proceedings The Second Internationa
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Table of Contents Message from the
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Zuming Xiao, Zhan Guo, Bin Tan, and
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Message from the Symposium Chairs T
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Second International Symposium on N
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model that can deal with time serie
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training for the Wushu competition
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information, called weak uncertain
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Student side Student side Student s
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If we define element of student as
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QoS, each frame data is divided int
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for Imaging Two and Three Phase Flo
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A. Profiling&following control algo
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Research and Realization about Conv
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ubber according to the mass ratio o
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Ⅲ. AN IMPROVED DNA ALGORITHM FOR
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Ⅴ.CONCLUSION REMARKS DNA computer
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its first child q 1 on the left, th
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chains can greatly improve efficien
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II. RELATED WORK A. Mobile Service
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special services. SOAP is used to b
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detection methods of DDoS attacks m
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Step4 calculate the new subordinate
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Figure 1. An analysis of the partit
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And the decay speed of buffer seque
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distance of view point. Given that
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Ⅳ. EVALUATION OF BLENDED LEARNING
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symmetric with respect to the origi
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each sample belongs to each categor
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A. Data Preparing To generate our t
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Strong earthquake 0.1< M L
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indirect causes, and the logical re
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egression. Granger causality test i
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B. Evaluation We have evaluated thi
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used as a source and neighboring ce
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Figure 3. Drainage networks generat
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under the endorsement of both the m
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TABLE I. DESCRIPTION OF PROPOSITION
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Figure 2. The process of the invers
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Figure 9. (a)the original image.(b)
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In order to reduce to the number of
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that studying being going to be to
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Reference[10] analyzed the evolutio
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module, communication module, apper
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After the comprehensive performance
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system testing can be seen that the
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output, so BP network has been wide
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Architecture (AMBA) a new bus archi
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In this paper, we adopt two Sobel o
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four layers.The far right of the gr
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TABLE II. OPERATIONAL EMPLOYEE TABL
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A. Object-relational Type To audit
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to execution time. Also, DBA would
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Liping Chen .......................
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