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
Paperback Engels 2016 9783319284477Samenvatting
This book constitutes the thoroughly refereed
post-conference proceedings of the Second International Workshop on Adaptive
Resource Management and Scheduling for Cloud Computing, ARMS-CC 2015, held in
Conjunction with ACM Symposium on Principles of Distributed Computing, PODC
2015, 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 have
identified several important aspects of the problem addressed by ARMS-CC:
self-* and autonomous cloud systems, cloud quality management and service level
agreement (SLA), scalable computing, mobile cloud computing, cloud computing
techniques for big data, high performance cloud computing, resource management
in big data platforms, scheduling algorithms for big data processing, cloud
composition, federation, bridging, and bursting, cloud resource virtualization
and composition, load-balancing and co-allocation, fault tolerance,
reliability, and availability of cloud systems.
Specificaties
Lezersrecensies
Inhoudsopgave
and the Impact of Resource Augmentation.- Using Performance Forecasting to
Accelerate Elasticity.- Parametric Analysis of Mobile Cloud Computing
Frameworks using Simulation Modeling.- Bandwidth Aware Resource Optimization
for SMT Processors.- User-guided provisioning in federated clouds for
distributed calculations.- Compute on the go: A case of mobile-cloud
collaborative computing under mobility.- Impact of Virtual Machines
Heterogeneity on Datacenter Power Consumption in Data-Intensive Applications.- Implementing
the Cloud Software to Data approach for OpenStack environments.- Is Cloud
Self-organization Feasible.- Cloud Services composition through Cloud Patterns.-
An Eye on the Elephant in the Wild: A Performance Evaluation of Hadoop's
Schedulers Under Failures.- Partitioning graph databases by using access
patterns.- Cloud Search Based Applications for Big Data - Challenges and Methodologies
for Acceleration.</p>
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