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This article presents the design and implementation of a reliable computing virtual container‐based model with integrity verification for data processing strategies named the reliability and integrity verification (RIV) scheme. It has been integrated into a system construction model as well as existing workflow engines (e.g., Kulla and Makeflow) for composing in‐memory systems. In the RIV scheme, the reliability (R) component is in charge of providing an implicit fault tolerance mechanism for the processes of data acquisition and storage that take place in a data processing system. The integrity verification (IV) component is in charge of ensuring that data transmitted/received between two processing stages are correct and are not modified during the transmission process. To show the feasibility of using the RIV scheme, real‐world applications were created by using different distributed and parallel systems to solve use cases of satellite and medical imagery processing. This evaluation revealed encouraging results as some solutions that assumed the cost (overhead) of using the RIV scheme, for example, Kulla (the Kulla‐RIV solution), achieve better response times than others without the RIV scheme (e.g., Makeflow) that remain exposed to the risks caused by to the lack of RIV strategies. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper presents AES4SeC, a security scheme fully constructed over cryptographic pairings. The main building blocks of AES4SeC are attribute-based encryption (ABE) and short signatures (SSign), with generalized constructions for the Type 3 pairing. AES4SeC was developed as an end-to-end storage service for hybrid cloud models and integrated to a file-sharing application for scenarios where data owners upload content to the cloud and selectively decide who is able to access that content. An experimental evaluation of AES4SeC was conducted by testing different security levels, recommended key sizes, and cryptographic engine constructions. This led to a wide experimental evaluation in terms of the running times of the primitive operations (encrypt, decrypt, sign, verify) and the space complexity of the ciphertexts, private and public keys, and the signatures. The implementation results revealed the feasibility and flexibility of AES4SeC in real scenarios, whereas a fine-tuning evaluation revealed that the best results in terms of performance and memory requirements are obtained using Type 3 pairings over type F elliptic curves. This is a relevant result because most of the ABE and SSign schemes in the literature are provided for the Type 1 pairing (symmetric) over type A curves, which exhibited poorer results. [ABSTRACT FROM AUTHOR]

Earth observation satellites produce large amounts of images/data that not only must be processed and preserved in reliable geospatial platforms but also efficiently disseminated among partners/researchers for creating derivative products through collaborative workflows. Organizations can face up this challenge in a cost-effective manner by using cloud services. However, outages and violations of integrity/confidentiality associated to this technology could arise. This article presents FedIDS, a suite of cloud-based components for building dependable geospatial platforms. The Fed component enables organizations to build shared geospatial data infrastructure through federation of independent cloud resources to withstand outages, whereas IDS avoids violations of integrity/confidentiality of images/data in sharing information and collaboration workflows. A FedIDS prototype, deployed in Spain and Mexico, was evaluated through a study case based on a satellite imagery captured by a Mexican antenna and another based on a satellite imagery of a European observation mission. The acquisition, storage and sharing of images among users of the federation, the exchange of images between Mexican and Spanish sites and outage scenarios were evaluated. The evaluation revealed the feasibility, reliability and efficiency of FedIDS, in comparison with available solutions, in terms of performance, storage consume and integrity/confidentiality when sharing images/data in collaborative scenarios. [ABSTRACT FROM AUTHOR]

Two novel techniques based on term expansion for domain-specific Word Sense Disambiguation are presented in this paper. A list of terms correlated with the ambiguous word is obtained by means of correlation methods such as Pointwise Mutual Information and Chi-square. The list of correlated terms is used for expanding the context in which an ambiguous word occurs, thus leading to a better number of terms which may be further used for determining the correct sense of the target ambiguous word. The proposed method has been tested in domain-specific corpora (Finance and Sports) and in one balanced corpus, the British National Corpus (BNC). The obtained results for domain-specific corpora are competitive (Finance) and ever better (Sports and BNC) than those reported in previous works. [ABSTRACT FROM PUBLISHER]