Computer Performance Engineering
16th European Workshop, EPEW 2019, Milan, Italy, November 28-29, 2019, Revised Selected Papers
Published on 3. April 2020
XIII, 161 pages
978-3-030-44411-2 (ISBN)
Description
This book constitutes the refereed proceedings of the 16th European Workshop on Computer Performance Engineering, EPEW 2019, held in Milan, Italy, in November 2019.
The 10 papers presented in this volume together with one invited talk were carefully reviewed and selected from 13 submissions. The papers presented at the workshop reflect the diversity of modern performance engineering, with topics ranging from modeling and analysis of network/control protocols and high performance/BigData information systems, analysis of scheduling, blockchain technology, analytical modeling and simulation of computer/network systems.
More details
Series
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Product notice
Reflowable
Illustrations
XIII, 161 p. 164 illus., 34 illus. in color.
File size
11,64 MB
ISBN-13
978-3-030-44411-2 (9783030444112)
DOI
10.1007/978-3-030-44411-2
Schweitzer Classification
Other editions
Additional editions
Marco Gribaudo | Mauro Iacono | Tuan Phung-Duc
Computer Performance Engineering
16th European Workshop, EPEW 2019, Milan, Italy, November 28-29, 2019, Revised Selected Papers
Book
03/2020
Springer
€53.49
Shipment within 7-9 days
Content
Hybrid Petri Nets Featuring Multiple Random Variables.- Abandonment Attack on the LEACH Protocol.- Coherent Resolutions of Nondeterminism.- Emulating Self-adaptive Stochastic Petri Nets.- Design and Evaluation of an Edge Concurrency Control Protocol for Distributed Graph Databases.- A Novel Data-driven Algorithm for the Automated Detection of Unexpectedly High Traffic Flow in Uncongested Traffic States.- A Network Aware Resource Discovery Service.- EthExplorer: A Tool for Forensic Analysis of the Ethereum Blockchain.- A Queueing Model that Works Only on Biggest Jobs.- Performance Evaluation of Thermal-Constrained Scheduling Strategies in Multi-Core Systems.- Bounding the Rate of Convergence for One Class of Finite Capacity Time Varying Markov~Queues.
