As different Cloud Management Frameworks and resource providers are settling in the market there is the need to grasp the interoperability problems present in current infrastructures, and study how existing and emerging standards could enhance user experience in the cloud ecosystem.In this paper we will review the current open challenges in Infrastructure as a Service cloud interoperability and federation, as well as point to the potential standards that should alleviate these problems.

The biggest overhead for the instantiation of a virtual machine in a cloud infrastructure is the time spent in transferring the image of the virtual machine into the physical node that executes it. This overhead becomes larger for requests composed of several virtual machines to be started concurrently, and the illusion of flexibility and elasticity usually associated with the cloud computing model may vanish. This poses a problem for both the resource providers and the software developers, since tackling those overheads is not a trivial issue. In this work we implement and evaluate several improvements for virtual machine image distribution problem in a cloud infrastructure and propose a method based on BitTorrent and local caching of the virtual machine images that reduces the transfer time when large requests are mad

The analysis of the complex LHC data usually follows a standard path that aims at minimizing not only the amount of data but also the number of observables used. After a number of steps of slimming and skimming the data, the remaining few terabytes of ROOT files hold a selection of the events and a flat structure for the variables needed that can be more easily inspected and traversed in the final stages of the analysis. PROOF arises at this point as an efficient mechanism to distribute the analysis load by taking advantage of all the cores in modern CPUs through PROOF Lite, or by using PROOF Cluster or PROOF on Demand tools to build dynamic PROOF cluster on computing facilities with spare CPUs. However using PROOF at the level required for a serious analysis introduces some difficulties that may scare new adopters. We have developed the PROOF Analysis Framework (PAF) to facilitate the development of new analysis by uniformly exposing the PROOF related configurations across technologies and by taking care of the routine tasks as much as possible. We describe the details of the PAF implementation as well as how we succeeded in engaging a group of CMS physicists to use PAF as their daily analysis framework.

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