Entanglement Verification in Quantum Networks with Tampered Nodes

In this paper, we consider the problem of entanglement verification across the quantum memories of any two nodes of a quantum network. Its solution can be a means for detecting (albeit not preventing) the presence of intruders that have taken full control of a node, either to make a denial-of-service attack or to reprogram the node. Looking for strategies that only require local operations and classical communication (LOCC), we propose two entanglement verification protocols characterized by increasing robustness and efficiency.Comment: 14 pages, 7 figure

Review of Elements of Parallel Computing

As the title clearly states, this book is about parallel computing. Modern computers are no longer characterized by a single, fully sequential CPU. Instead, they have one or more multicore/manycore processors. The purpose of such parallel architectures is to enable the simultaneous execution of instructions, in order to achieve faster computations. In high performance computing, clusters of parallel processors are used to achieve PFLOPS performance, which is necessary for scientific and Big Data applications. Mastering parallel computing means having deep knowledge of parallel architectures, parallel programming models, parallel algorithms, parallel design patterns, and performance analysis and optimization techniques. The design of parallel programs requires a lot of creativity, because there is no universal recipe that allows one to achieve the best possible efficiency for any problem. The book presents the fundamental concepts of parallel computing from the point of view of the algorithmic and implementation patterns. The idea is that, while the hardware keeps changing, the same principles of parallel computing are reused. The book surveys some key algorithmic structures and programming models, together with an abstract representation of the underlying hardware. Parallel programming patterns are purposely not illustrated using the formal design patterns approach, to keep an informal and friendly presentation that is suited to novices

A Computational Field Framework for Collaborative Task Execution in Volunteer Clouds

The increasing diffusion of cloud technologies is opening new opportunities for distributed and collaborative computing. Volunteer clouds are a prominent example, where participants join and leave the platform and collaborate by sharing their computational resources. The high dynamism and unpredictability of such scenarios call for decentralized self-* approaches to guarantee QoS. We present a simulation framework for collaborative task execution in volunteer clouds and propose one concrete instance based on Ant Colony Optimization, which is validated through a set of simulation experiments based on Google workload data

A cooperative approach for distributed task execution in autonomic clouds

Virtualization and distributed computing are two key pillars that guarantee scalability of applications deployed in the Cloud. In Autonomous Cooperative Cloud-based Platforms, autonomous computing nodes cooperate to offer a PaaS Cloud for the deployment of user applications. Each node must allocate the necessary resources for customer applications to be executed with certain QoS guarantees. If the QoS of an application cannot be guaranteed a node has mainly two options: to allocate more resources (if it is possible) or to rely on the collaboration of other nodes. Making a decision is not trivial since it involves many factors (e.g. the cost of setting up virtual machines, migrating applications, discovering collaborators). In this paper we present a model of such scenarios and experimental results validating the convenience of cooperative strategies over selfish ones, where nodes do not help each other. We describe the architecture of the platform of autonomous clouds and the main features of the model, which has been implemented and evaluated in the DEUS discrete-event simulator. From the experimental evaluation, based on workload data from the Google Cloud Backend, we can conclude that (modulo our assumptions and simplifications) the performance of a volunteer cloud can be compared to that of a Google Cluster

Where Is the Power? Transnational Networks, Authority and the Dispute over the Xayaburi Dam on the Lower Mekong Mainstream

Accounts of hydro-hegemony and counter hydro-hegemony provide state-based conceptions of power in international river basins. However, authority should be seen as transnationalized as small states develop coping strategies to augment their authority over decision-making processes. The article engages Rosenau’s spheres of authority concept to argue that hydro-hegemony is exercised by actors embedded in spheres of authority that reshape actor configurations as they emerge. These spheres consist of complex networks challenging customary notions of the local-global dichotomy and hydro-hegemony. Hydro-hegemony is therefore not fixed. The article examines these processes by analysing the dispute over the Xayaburi Dam in the Mekong Basin

Advanced statistical and machine learning methods for multi-step multivariate time series forecasting in predictive maintenance

The accurate prediction of failure events is of central interest to the field of predictive maintenance, where the role of forecasting is of paramount importance. In this paper, we present and compare some advanced statistical and machine learning methods for multi-step multivariate time series forecasting. Regarding statistical methods, we considered VAR, VMA, VARMA and Theta. The machine learning approaches we selected are variants of the Recurrent Neural Network model, namely ERNN, LSTM and GRU. All the considered methods have been evaluated in terms of accuracy, using 5 public datasets. As an extra contribution, we have implemented the multivariate version of the Theta method