By Vittorio Cortellessa (auth.), Maria Simonetta Balsamo, William J. Knottenbelt, Andrea Marin (eds.)
This booklet constitutes the refereed post-proceedings of the tenth ecu functionality Engineering Workshop, EPEW 2013, held in Venice, Italy, in September 2013.
The sixteen commonplace papers offered including eight brief papers and a couple of invited talks have been rigorously reviewed and chosen from 33 submissions. The Workshop goals to assemble educational and commercial researchers engaged on all features of functionality engineering.
Original papers regarding theoretical and methodological concerns in addition to case experiences and automatic device aid are solicited within the following parts: functionality modeling and assessment, method and community functionality engineering, and software program functionality engineering.
Read or Download Computer Performance Engineering: 10th European Workshop, EPEW 2013, Venice, Italy, September 16-17, 2013. Proceedings PDF
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Extra resources for Computer Performance Engineering: 10th European Workshop, EPEW 2013, Venice, Italy, September 16-17, 2013. Proceedings
We notice also that when the number of classes increases, the used methods gives a closer results to the exact ones. c illustrates well that the HBSP method does not provide bounds. 2 F. A¨ıt-Salaht et al. Queueing Network In this section, we study a tandem queueing network with the MAWI traﬃc trace (Figure 2) as input arrival histogram. 5 Mb/s. The buﬀers sizes are set to B1 =2 Mb, B2 =1 Mb and B3 =1 Mb. The analysis of the network is performed for two reductions 100 and 500 respectively on the input histogram of each queue (see Table 1).
Conf. Networking, Sensing and Control, pp. 355–359. IEEE (2010) 12. : Optimized pre-copy live migration for memory intensive applications. In: Proc. 2011 Intl. Conf. High Performance Computing, Networking, Storage and Analysis, p. 40. ACM (2011) 13. : Predicting the performance of virtual machine migration. In: 2010 IEEE Intl. Symp. Modeling, Analysis & Simulation of Computer and Telecommunication Systems, pp. 37–46. IEEE (2010) 14. : An automatic machine scaling solution for cloud systems. In: 19th Intl.
1 − ρeﬀ (20) The total number of pages migrated is PTotalMig = Ps 1 − ρn+1 eﬀ +α 1 − ρeﬀ . (21) Therefore, the gain G in this case is computed G= 1 . ρn+1 eﬀ (22) The network utilization due to VM migration is Unet = ρeﬀ − ρn+2 eﬀ + α(1 − ρeﬀ ) . 1 − ρn+2 eﬀ (23) Note that the utilization Unet depends on β through ρeﬀ , which depends on Deﬀective . Also, as in the uniform dirtying rate case, Unet does not depend on Ps . 2 Model of Copying Hot Pages during the Downtime Phase In this case, we can adapt the results in the previous section as follows.