Treffer: 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 Sebasti n, Spain, July 20, 2015, Revised Selected Papers / edited by Florin Pop, Maria Potop-Butucaru.

Title:
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 Sebasti n, Spain, July 20, 2015, Revised Selected Papers / edited by Florin Pop, Maria Potop-Butucaru.
Publisher Information:
Cham : Springer International Publishing : Imprint: Springer, 2015. 2015
Document Type:
Electronic Resource<br />Electronic Resource
Availability:
Open access content. Open access content
Other Numbers:
PYCED oai:dspace.conacyt.gov.py:123456789/16610
9783319284484
10.1007/978-3-319-28448-4
978-3-319-28448-4
1154418466
Contributing Source:
CONACYT EDUCA
From OAIster®, provided by the OCLC Cooperative.
Accession Number:
edsoai.on1154418466
Database:
OAIster

Weitere Informationen

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 Sebasti n, 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.