Theory of finite automata with an introduction to formal languages
Theory of finite automata with an introduction to formal languages
The NAS parallel benchmarks—summary and preliminary results
Proceedings of the 1991 ACM/IEEE conference on Supercomputing
Computer benchmarks
The grid: blueprint for a new computing infrastructure
The grid: blueprint for a new computing infrastructure
Introduction to Automata Theory, Languages and Computability
Introduction to Automata Theory, Languages and Computability
A taxonomy and survey of grid resource management systems for distributed computing
Software—Practice & Experience
NAS Grid Benchmarks: A Tool for Grid Space Exploration
Cluster Computing
Basic Concepts and Taxonomy of Dependable and Secure Computing
IEEE Transactions on Dependable and Secure Computing
Grid benchmarking: vision, challenges, and current status: Research Articles
Concurrency and Computation: Practice & Experience
Grid'5000: A Large Scale And Highly Reconfigurable Experimental Grid Testbed
International Journal of High Performance Computing Applications
GridBench: A tool for the interactive performance exploration of Grid infrastructures
Journal of Parallel and Distributed Computing
Defining the grid: a snapshot on the current view
The Journal of Supercomputing
netWorker - Cloud computing: PC functions move onto the web
A break in the clouds: towards a cloud definition
ACM SIGCOMM Computer Communication Review
The Eucalyptus Open-Source Cloud-Computing System
CCGRID '09 Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid
Virtual Infrastructure Management in Private and Hybrid Clouds
IEEE Internet Computing
RSFDGrC'03 Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing
From infrastructure delivery to service management in clouds
Future Generation Computer Systems
The reservoir model and architecture for open federated cloud computing
IBM Journal of Research and Development
Finding order in chaos: a behavior model of the whole grid
Concurrency and Computation: Practice & Experience - Grid Computing, High Performance and Distributed Application
A reference model for grid architectures and its validation
Concurrency and Computation: Practice & Experience - Grid Computing, High Performance and Distributed Application
BlobSeer: Next-generation data management for large scale infrastructures
Journal of Parallel and Distributed Computing
Using Global Behavior Modeling to Improve QoS in Cloud Data Storage Services
CLOUDCOM '10 Proceedings of the 2010 IEEE Second International Conference on Cloud Computing Technology and Science
CSE '10 Proceedings of the 2010 13th IEEE International Conference on Computational Science and Engineering
Grid Global Behavior Prediction
CCGRID '11 Proceedings of the 2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing
GridARM: askalon's grid resource management system
EGC'05 Proceedings of the 2005 European conference on Advances in Grid Computing
Revealing the MAPE loop for the autonomic management of Cloud infrastructures
ISCC '11 Proceedings of the 2011 IEEE Symposium on Computers and Communications
An autonomic framework for enhancing the quality of data grid services
Future Generation Computer Systems
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Over the last decade, Grid computing paved the way for a new level of large scale distributed systems. This infrastructure made it possible to securely and reliably take advantage of widely separated computational resources that are part of several different organizations. Resources can be incorporated to the Grid, building a theoretical virtual supercomputer. In time, cloud computing emerged as a new type of large scale distributed system, inheriting and expanding the expertise and knowledge that have been obtained so far. Some of the main characteristics of Grids naturally evolved into clouds, others were modified and adapted and others were simply discarded or postponed. Regardless of these technical specifics, both Grids and clouds together can be considered as one of the most important advances in large scale distributed computing of the past ten years; however, this step in distributed computing has came along with a completely new level of complexity. Grid and cloud management mechanisms play a key role, and correct analysis and understanding of the system behavior are needed. Large scale distributed systems must be able to self-manage, incorporating autonomic features capable of controlling and optimizing all resources and services. Traditional distributed computing management mechanisms analyze each resource separately and adjust specific parameters of each one of them. When trying to adapt the same procedures to Grid and cloud computing, the vast complexity of these systems can make this task extremely complicated. But large scale distributed systems complexity could only be a matter of perspective. It could be possible to understand the Grid or cloud behavior as a single entity, instead of a set of resources. This abstraction could provide a different understanding of the system, describing large scale behavior and global events that probably would not be detected analyzing each resource separately. In this work we define a theoretical framework that combines both ideas, multiple resources and single entity, to develop large scale distributed systems management techniques aimed at system performance optimization, increased dependability and Quality of Service (QoS). The resulting synergy could be the key to address the most important difficulties of Grid and cloud management.