Pietro Ruiu

Data as a Service (DaaS) for Sharing and Processing of Large Data Collections in the Cloud

Data as a Service (DaaS) is among the latest kind of services being investigated in the Cloud computing community. The main aim of DaaS is to overcome limitations of state-of-the-art approaches in data technologies, according to which data is stored and accessed from repositories whose location is known and is relevant for sharing and processing. Besides limitations for the data sharing, current approaches also do not achieve to fully separate/decouple software services from data and thus impose limitations in inter-operability. In this paper we propose a DaaS approach for intelligent sharing and processing of large data collections with the aim of abstracting the data location (by making it relevant to the needs of sharing and accessing) and to fully decouple the data and its processing. The aim of our approach is to build a Cloud computing platform, offering DaaS to support large communities of users that need to share, access, and process the data for collectively building knowledge from data. We exemplify the approach from large data collections from health and biology domains.

Container-Based Orchestration in Cloud: State of the Art and Challenges

How to effectively manage increasingly complex enterprise computing environments is one of the hardest challenges that most organizations have to face in the era of cloud computing, big data and IoT. Advanced automation and orchestration systems are the most valuable solutions helping IT staff to handle large-scale cloud data centers. Containers are the new revolution in the cloud computing world, they are more lightweight than VMs, and can radically decrease both the start up time of instances and the processing and storage overhead with respect to traditional VMs. The aim of this paper is to provide a comprehensive description of cloud orchestration approaches with containers, analyzing current research efforts, existing solutions and presenting issues and challenges facing this topic.

Power comparison of cloud data center architectures

Power consumption is a primary concern for cloud computing data centers. Being the network one of the non-negligible contributors to energy consumption in data centers, several architectures have been designed with the goal of improving network performance and energy-efficiency. In this paper, we provide a comparison study of data center architectures, covering both classical two- and three-tier design and state-of-art ones as Jupiter, recently disclosed by Google. Specifically, we analyze the combined effect on the overall system performance of different power consumption profiles for the IT equipment and of different resource allocation policies. Our experiments, performed in small and large scale scenarios, unveil the ability of network-aware allocation policies in loading the the data center in a energy-proportional manner and the robustness of classical two- and three-tier design under network-oblivious allocation strategies.

First observations of GNSS ionospheric scintillations from DemoGRAPE project

The Istituto Nazionale di Geofisica e Vulcanologia leads an international project funded by the Italian National Program for Antarctic Research, called Demonstrator of Global Navigation Satellite System (GNSS) Research and Application for Polar Environment (DemoGRAPE), in partnership with Politecnico di Torino, Istituto Superiore Mario Boella, and with South African National Space Agency and the Brazilian National Institute of Space Physics, as key collaborators. DemoGRAPE is a new prototype of support for the satellite navigation in Antarctica. Besides the scientific interest, the accuracy of satellite navigation in Antarctica is of paramount importance since there is always the danger that people and vehicles can fall into a crevasse during a snowstorm, when visibility is limited and travel is restricted to following specified routes using satellite navigation systems. The variability of ionospheric delay and ionospheric scintillation are two of the primary factors which affect the accuracy of satellite navigation. The project will provide a demonstrator of cutting edge technology for the empirical assessment of the ionospheric delay and ionospheric scintillations in the polar regions. The scope of the project includes new equipment for the recording and dissemination of GNSS data and products installed at the South African and Brazilian bases in Antarctica. The new equipment will facilitate the exchange of software and derived products via the Cloud computing technology infrastructure. The project portal is accessible at www.demogrape.net. We report the first Global Navigation Satellite System (GNSS) signal scintillations observed in Antarctica.

Grid Infrastructure for Domain Decomposition Methods in Computational ElectroMagnetics

The accurate and efficient solution of Maxwells equation is the problem addressed by the scientific discipline called Computational ElectroMagnetics (CEM). Many macroscopic phenomena in a great number of fields are governed by this set of differential equations: electronic, geophysics, medical and biomedical technologies, virtual EM prototyping, besides the traditional antenna and propagation applications. Therefore, many efforts are focussed on the development of new and more efficient approach to solve Maxwells equation. The interest in CEM applications is growing on. Several problems, hard to figure out few years ago, can now be easily addressed thanks to the reliability and flexibility of new technologies, together with the increased computational power. This technology evolution opens the possibility to address large and complex tasks. Many of these applications aim to simulate the electromagnetic behavior, for example in terms of input impedance and radiation pattern in antenna problems, or Radar Cross Section for scattering applications. Instead, problems, which solution requires high accuracy, need to implement full wave analysis techniques, e.g., virtual prototyping context, where the objective is to obtain reliable simulations in order to minimize measurement number, and as consequence their cost. Besides, other tasks require the analysis of complete structures (that include an high number of details) by directly simulating a CAD Model. This approach allows to relieve researcher of the burden of removing useless details, while maintaining the original complexity and taking into account all details. Unfortunately, this reduction implies: (a) high computational effort, due to the increased number of degrees of freedom, and (b) worsening of spectral properties of the linear system during complex analysis. The above considerations underline the needs to identify appropriate information technologies that ease solution achievement and fasten required elaborations. The authors analysis and expertise infer that Grid Computing techniques can be very useful to these purposes. Grids appear mainly in high performance computing environments. In this context, hundreds of off-the-shelf nodes are linked together and work in parallel to solve problems, that, previously, could be addressed sequentially or by using supercomputers. Grid Computing is a technique developed to elaborate enormous amounts of data and enables large-scale resource sharing to solve problem by exploiting distributed scenarios. The main advantage of Grid is due to parallel computing, indeed if a problem can be split in smaller tasks, that can be executed independently, its solution calculation fasten up considerably. To exploit this advantage, it is necessary to identify a technique able to split original electromagnetic task into a set of smaller subproblems. The Domain Decomposition (DD) technique, based on the block generation algorithm introduced in Matekovits et al. (2007) and Francavilla et al. (2011), perfectly addresses our requirements (see Section 3.4 for details). In this chapter, a Grid Computing infrastructure is presented. This architecture allows parallel block execution by distributing tasks to nodes that belong to the Grid. The set of nodes is composed by physical machines and virtualized ones. This feature enables great flexibility and increase available computational power. Furthermore, the presence of virtual nodes allows a full and efficient Grid usage, indeed the presented architecture can be used by different users that run different applications.

Biometric Authentication and Data Security in Cloud Computing

Two important topics related to the cloud security are discussed in this chapter: the authentication of logical users accessing the cloud, and the security of data stored on public cloud servers. A real cloud platform is used as example; it is designed and implemented to support basic web applications, and to be shared by small and medium companies. Such platform is built using the OpenStack architecture. The user authentication is based on an original biometric approach exploiting fingerprints and open to multimodal improvements. The platform guarantees secure access of multiple users and complete logical separation of computational and data resources, related to different companies. High level of protection of the data, stored in the cloud, is ensured by adopting a peculiar data fragmentation approach.

Reconfigurable antenna system for wireless applications

Nowadays wireless applications are widespread, and the demand for smart antenna technology grows exponentially. Although there are a large variety of effective algorithms to control antennas, they lack in the requirements of the next generation smart devices for industrial and societal applications which demand integration in compact, low cost and low power architectures. In this work we present a Wi-Fi device coupled with an antenna, where the receiver is able to adapt to a changing signal environment by providing a constant and reliable connectivity. Design criterion follows a strong low power approach, single front-end USB powered connected to an embedded low energy consumption platform. In addition, we come up in a low cost solution that does not require any external hardware. Decoding and antenna control algorithm are software-defined, while antenna beam steering is obtained by means of varactor diodes, voltage biased, used in a suitable way through hybrid couplers in phase shift configuration.

Simulation, Modeling, and Performance Evaluation Tools for Cloud Applications

As cloud computing adoption and deployment increase, the performance evaluation of the cloud environments is becoming very important. Cloud applications have different composition, configuration, and deployment requirements. Simulation and modeling techniques are suitable to quantify the performance of resource allocation policies and application scheduling algorithms in Cloud computing environments for different application and service models according to different work loads, energy performance and system size. In this paper, we give an overview of the existing distributed systems simulation and modeling tools in order to outline the main characteristics and peculiarities. We then present an outlook on new requirements to be addressed for performance evaluation of cloud applications through simulation and modeling.

DemoGRAPE: Managing Scientific Applications in a Cloud-Federated Environment

There is a strong relationship between scientific research and technology advancement. The former generally focuses on studying phenomena happening in the real world, the latter improves tools that are at the basis of this research. From this perspective, information and communication technologies allow the implementation of ever faster tools for analyzing data generated by experiments. The aim of DemoGRAPE project is to study the interaction of the upper earth atmosphere and the GNSS (Global Navigation Satellite Systems) signals received at ground, in critical environments such as the polar regions. This paper describes the ICT infrastructure used to manage the software applications used to analyzed data collected during project experimental campaigns, taking into account the following constraints: (i) the intellectual property of the applications must be protected, (ii) the underlying infrastructure resembles a cloud-federation, (iii) data are over-sized, (iv) provide a unified vision of the available resources to the user (i.e., what are the available applications, and where experimental data reside). Leveraging on a lightweight virtualization system, we proposed a management system that copes with all these four constraints. A case study is used to show the process of deploying an application through the proposed system on a specific node where data of interest reside.

Accessing Cloud Services through Biometrics Authentication

The adoption of Cloud computing involves many advantages in terms of flexibility, scalability and reliability, but also implies new challenges on security, data privacy and protection of personal data. Since more and more sensitive applications and data are moved to the cloud, the verification of the digital identity of the participants in the electronic communication has become a crucial challenge. Currently, the use of biometric techniques can be considered as an effective solution to ensure a significant increase of security in the authentication protocols managed by modern authentication servers. However the use of biometric data for the logical access to IT services is a more challenging and still unsolved problem. The project Cloud for SME integrates a biometric authentication based on fingerprints with a cloud computing platform, investigating how highly secure authentication methods can increase the adoption of cloud computing technologies among small and medium enterprises.