Download Computer Performance Engineering: 13th European Workshop, by Dieter Fiems, Marco Paolieri, Agapios N. Platis PDF

By Dieter Fiems, Marco Paolieri, Agapios N. Platis

This booklet constitutes the refereed lawsuits of the thirteenth ecu Workshop on desktop functionality Engineering, EPEW 2016, held in Chios, Greece, in October 2016. The 14 papers awarded including 2 invited talks during this quantity have been rigorously reviewed and chosen from 25 submissions. The papers awarded on the workshop mirror the range of contemporary functionality engineering, with subject matters starting from the research of queueing networks and stochastic strategies, to functionality research of desktops and networks, or even modeling of human behavior.

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Additional info for Computer Performance Engineering: 13th European Workshop, EPEW 2016, Chios, Greece, October 5-7, 2016, Proceedings

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541–546, May 2015 Analytic Solution of Fair Share Scheduling in Layered Queueing Networks 17 17. : A performance experiment system supporting fast mapping of system issues. In: Proceedings of the 4th International ICST Conference on Performance Evaluation Methodologies and Tools (VALUETOOLS 2009), Pisa, Italy, 20–22 October 2009, pp. 246–255 (2009) 18. : On packet switches with infinite storage. IEEE Trans. Commun. 35(4), 435–438 (1987) 19. : PARASOL Users Manual. ) 20. : Completely fair scheduler.

An performed during the generation of the events; each activity ai = αi , τi , δi for i = 1, . . , n includes an activity type αi from a finite set A = {act1 , . . , actN }, a start time τi ≥ 0 (such that τ1 ≤ · · · ≤ τn ) and an activity duration δi ≥ 0. As in [4,16], the underlying assumption of this problem is that distinct activities take place in the system and a statistical characterization is derived taking into account: (i) the duration of each activity; (ii) the time between subsequent events; (iii) the types of event occurred within each activity; (iv) the transition probabilities among activities.

Sometimes Toileting occurs at the same time as Sleeping or Preparing dinner ), opportunely removed in order to be cast into the shape of the semi-Markov process. Activities were annotated by the subject himself using a Bluetooth headset, resulting in a stream of activities a1 , a2 , . . , an , each characterized, as described in Sect. 2, by a tuple ai = αi , τi , δi . As described in [4], events were converted from a raw sensor representation (which holds a high signal when the sensor is firing, and a low signal otherwise) into a dual change-point sensor representation, which emits a time-point signal when the sensor starts to fire and when it switches off, distinguishing activation/deactivation actions and, consequently, doubling the number of event types and instances, from 14 to 28 and from 1 319 to 2 638, respectively.

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