Adaptive Resource Management and Scheduling for Cloud Computing
Beschreibung:
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.