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A complex and important task in the cloud resource management is the efficient allocation of virtual machines (VMs), or containers, in physical machines (PMs). The evaluation of VM placement techniques in real-world clouds can be tedious, complex and time-consuming. This situation has motivated an increasing use of cloud simulators that facilitate this type of evaluations. However, most of the reported VM placement techniques based on simulations have been evaluated taking into account one specific cloud resource (e.g., CPU), whereas values often unrealistic are assumed for other resources (e.g., RAM, awaiting times, application workloads, etc.). This situation generates uncertainty, discouraging their implementations in real-world clouds. This paper introduces CloudBench, a methodology to facilitate the evaluation and deployment of VM placement strategies in private clouds. CloudBench considers the integration of a cloud simulator with a real-world private cloud. Two main tools were developed to support this methodology, a specialized multi-resource cloud simulator (CloudBalanSim), which is in charge of evaluating VM placement techniques, and a distributed resource manager (Balancer), which deploys and tests in a real-world private cloud the best VM placement configurations that satisfied user requirements defined in the simulator. Both tools generate feedback information, from the evaluation scenarios and their obtained results, which is used as a learning asset to carry out intelligent and faster evaluations. The experiments implemented with the CloudBench methodology showed encouraging results as a new strategy to evaluate and deploy VM placement algorithms in the cloud. This work was partially funded by the Spanish Ministry of Economy, Industry and Competitiveness under the Grant TIN2016-79637-P “Towards Unifcation of HPC and Big Data Paradigms” and by the Mexican Council of Science and Technology (CONACYT) through a Ph.D. Grant (No. 212677).

Cloud-based storage is becoming a cost-effective solution for agencies, hospitals, government instances and scientific centers to deliver and share contents to/with a set of end-users. However, reliability, privacy and lack of control are the main problems that arise when contracting content delivery services with a single cloud storage provider. This paper presents the implementation of a storage system for content delivery and sharing in federated cloud storage networks. This system virtualizes the storage resources of a set of organizations as a single federated system, which is in charge of the content storage. The architecture includes a metadata management layer to keep the content delivery control in-house and a storage synchronization worker/monitor to keep the state of storage resources in the federation as well as to send contents near to the end-users. It also includes a redundancy layer based on a multi-threaded engine that enables the system to withstand failures in the federated network. We developed a prototype based on this scheme as a proof of concept. The experimental evaluation shows the benefits of building content delivery systems in federated cloud environments, in terms of performance, reliability and profitability of the storage space. The work presented in this paper has been partially supported by EU under the COST programme Action IC1305, Network for Sustainable Ultrascale Computing (NESUS).