Middleware strategies for clouds and grids in e‐Science

This special issue focuses on middleware strategies for the use of Clouds and Grids in e-Science applications, and is based on selected papers from the Seventh International Workshop on Middleware for Grid, Clouds and e-Science (MGC 2009) and on the Third Latin American Grid workshop (LAGrid 2009). The authors were invited to provide extended versions of their original papers taking into account comments and suggestions raised during the peer review process and comments from the audience during the workshops. Relevant contributions have been provided by McEvoy et al. [1], Eyers et al. [2], Kim et al. [3], Pinheiro et al. [4], Gomes and Costa [5], Futrelle et al. [6], and Ferro et al. [7]. These contributions focus on: • performance and deployment evaluation of a parallel application on a private Cloud; • configuring large-scale storage using a middleware applying machine learning (ML); • power-aware provisioning of virtual machines for real-time Cloud services; • an adaptive fault tolerance mechanism for opportunistic environments with a mobile agent approach; • an approach to enhance the efficiency of opportunistic grids; • use of semantic content management to create knowledge spaces for e-Science; and • a proposal to apply inductive logic programming (ILP) to self-healing problem in grids.