Adaptive Resource Management and Scheduling for Cloud Computing -

Adaptive Resource Management and Scheduling for Cloud Computing

Second International Workshop, ARMS-CC 2015, Held in Conjunction with ACM Symposium on Principles of Distributed Computing, PODC 2015, Donostia-San Sebastián, Spain, July 20, 2015, Revised Selected Papers
Buch | Softcover
XII, 187 Seiten
2016 | 1st ed. 2015
Springer International Publishing (Verlag)
978-3-319-28447-7 (ISBN)
42,80 inkl. MwSt

This book constitutes the thoroughly refereedpost-conference proceedings of the Second International Workshop on AdaptiveResource Management and Scheduling for Cloud Computing, ARMS-CC 2015, held inConjunction with ACM Symposium on Principles of Distributed Computing, PODC2015, in Donostia-San Sebastián, Spain, in July 2015.

The 12 revised full papers, including 1 invited paper,were carefully reviewed and selected from 24 submissions. The papers haveidentified several important aspects of the problem addressed by ARMS-CC:self-* and autonomous cloud systems, cloud quality management and service levelagreement (SLA), scalable computing, mobile cloud computing, cloud computingtechniques for big data, high performance cloud computing, resource managementin big data platforms, scheduling algorithms for big data processing, cloudcomposition, federation, bridging, and bursting, cloud resource virtualizationand composition, load-balancing and co-allocation, fault tolerance,reliability, and availability of cloud systems.

Competitive Analysis of Task Scheduling Algorithms on a Fault-Prone Machineand the Impact of Resource Augmentation.- Using Performance Forecasting toAccelerate Elasticity.- Parametric Analysis of Mobile Cloud ComputingFrameworks using Simulation Modeling.- Bandwidth Aware Resource Optimizationfor SMT Processors.- User-guided provisioning in federated clouds fordistributed calculations.- Compute on the go: A case of mobile-cloudcollaborative computing under mobility.- Impact of Virtual MachinesHeterogeneity on Datacenter Power Consumption in Data-Intensive Applications.- Implementingthe Cloud Software to Data approach for OpenStack environments.- Is CloudSelf-organization Feasible.- Cloud Services composition through Cloud Patterns.-An Eye on the Elephant in the Wild: A Performance Evaluation of Hadoop'sSchedulers Under Failures.- Partitioning graph databases by using accesspatterns.- Cloud Search Based Applications for Big Data - Challenges and Methodologiesfor Acceleration.

Erscheinungsdatum
Reihe/Serie Lecture Notes in Computer Science
Theoretical Computer Science and General Issues
Zusatzinfo XII, 187 p. 77 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Themenwelt Informatik Theorie / Studium Algorithmen
Mathematik / Informatik Mathematik Wahrscheinlichkeit / Kombinatorik
Schlagworte Big Data • client-server architectures • Cloud Computing • Computer Science, general • dependable and fault-tolerant systems and networks • distributed algorithms • distributed scheduling algorithms • Energy aware computing • foundational models • graph partitioning • grid computing • Integer linear programming • load-balancing and co-allocation • machine learning • many-task computing • mobile cloud computing • Modeling • n-tier architectures • online algorithms • Parallel Algorithms • Peer-to-peer architectures • Performance Prediction • resource optimization • Scalability modeling • Scheduling • scheduling algorithms • Self-Organization • Simulation • software functional properties • Streaming, sub-linear and near linear time algorithms • virtualization
ISBN-10 3-319-28447-9 / 3319284479
ISBN-13 978-3-319-28447-7 / 9783319284477
Zustand Neuware
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