Car-to-Cloud Communication Traffic Analysis Based on the Common Vehicle Information Model

Although connectivity services have been introduced already today in many of the most recent car models, the potential of vehicles serving as highly mobile sensor platform in the Internet of Things (IoT) has not been sufficiently exploited yet. The European AutoMat project has therefore defined an open Common Vehicle Information Model (CVIM) in combination with a cross-industry, cloud-based big data marketplace. Thereby, vehicle sensor data can be leveraged for the design of entirely new services even beyond traffic-related applications (such as localized weather forecasts). This paper focuses on the prediction of the achievable data rate making use of an analytical model based on empirical measurements. For an in-depth analysis, the CVIM has been integrated in a vehicle traffic simulator to produce CVIM-complaint data streams as a result of the individual behavior of each vehicle (speed, brake activity, steering activity, etc.). In a next step, a simulation of vehicle traffic in a realistically modeled, large-area street network has been used in combination with a cellular Long Term Evolution (LTE) network to determine the cumulated amount of data produced within each network cell. As a result, a new car-to-cloud communication traffic model has been derived, which quantifies the data rate of aggregated car-to-cloud data producible by vehicles depending on the current traffic situations (free flow and traffic jam). The results provide a reference for network planning and resource scheduling for car-to-cloud type services in the context of smart cities

Wyner VAE: Joint and Conditional Generation with Succinct Common Representation Learning

A new variational autoencoder (VAE) model is proposed that learns a succinct common representation of two correlated data variables for conditional and joint generation tasks. The proposed Wyner VAE model is based on two information theoretic problems---distributed simulation and channel synthesis---in which Wyner's common information arises as the fundamental limit of the succinctness of the common representation. The Wyner VAE decomposes a pair of correlated data variables into their common representation (e.g., a shared concept) and local representations that capture the remaining randomness (e.g., texture and style) in respective data variables by imposing the mutual information between the data variables and the common representation as a regularization term. The utility of the proposed approach is demonstrated through experiments for joint and conditional generation with and without style control using synthetic data and real images. Experimental results show that learning a succinct common representation achieves better generative performance and that the proposed model outperforms existing VAE variants and the variational information bottleneck method.Comment: 24 pages, 18 figure

Extending the Globus Information Service with the Common Information Model

This is a post-peer-review, pre-copyedit version. The final authenticated version is available online at: http://dx.doi.org/10.1109/ISPA.2011.62[Abstract] The need of task-adapted and complete information for the management of resources is a well known issue in Grid computing. Globus Toolkit 4 (GT4) includes the Monitoring and Discovery System component (MDS4) to carry out resource management. The Common Information Model (CIM) provides a standard conceptual view of the managed environment. This work improves the MDS4 functionality through the use of CIM, with the aim of providing a unified, standard representation of the Grid resources. Since a practical CIM model may contain a large volume of information, a new Index Service that represents the CIM information through Java instances is presented. In addition, a solution that keeps data in persistent storage has also been implemented. The evaluation of the proposed solutions achieves encouraging results, with an important reduction in memory consumption, a good scalability when the number of instances increases, and with a reasonable response time.Ministerio de Ciencia e Innovación; TIN2007-67537-C03Ministerio de Ciencia e Innovación; TIN2010-1637

A critical comparison of approaches to resource name management within the IEC common information model

Copyright @ 2012 IEEEElectricity network resources are frequently identified within different power systems by inhomogeneous names and identities due to the legacy of their administration by different utility business domains. The IEC 61970 Common Information Model (CIM) enables network modeling to reflect the reality of multiple names for unique network resources. However this issue presents a serious challenge to the integrity of a shared CIM repository that has the task of maintaining a resource manifest, linking network resources to master identities, when unique network resources may have multiple names and identities derived from different power system models and other power system applications. The current approach, using CIM 15, is to manage multiple resource names within a singular CIM namespace utilizing the CIM “IdentifiedObject” and “Name” classes. We compare this approach to one using additional namespaces relating to different power systems, similar to the practice used in CIM extensions, in order to more clearly identify the genealogy of a network resource, provide faster model import times and a simpler means of supporting the relationship between multiple resource names and identities and a master resource identity.This study is supported by the UK National Grid and Brunel University

Smart grid interoperability use cases for extending electricity storage modeling within the IEC Common Information Model

Copyright @ 2012 IEEEThe IEC Common Information Model (CIM) is recognized as a core standard, supporting electricity transmission system interoperability. Packages of UML classes make up its domain ontology to enable a standardised abstraction of network topology and proprietary power system models. Since the early days of its design, the CIM has grown to reflect the widening scope and detail of utility information use cases as the desire to interoperate between a greater number of systems has increased. The cyber-physical nature of the smart grid places even greater demand upon the CIM to model future scenarios for power system operation and management that are starting to arise. Recent developments of modern electricity networks have begun to implement electricity storage (ES) technologies to provide ancillary balancing services, useful to grid integration of large-scale renewable energy systems. In response to this we investigate modeling of grid-scale electricity storage, by drawing on information use cases for future smart grid operational scenarios at National Grid, the GB Transmission System Operator. We find current structures within the CIM do not accommodate the informational requirements associated with novel ES systems and propose extensions to address this requirement.This study is supported by the UK National Grid and Brunel Universit

Increasing Competition and the Winner's Curse: Evidence from Procurement

We assess empirically the effects of the winner's curse which, in common-value auctions, counsels more conservative bidding as the number of competitors increases. First, we construct an econometric model of an auction in which bidders' preferences have both common- and private-value components, and propose a new monotone quantile approach which facilitates estimation of this model. Second, we estimate the model using bids from procurement auctions held by the State of New Jersey. For a large subset of these auctions, we find that median procurement costs rise as competition intensifies. In this setting, then, asymmetric information overturns the common economic wisdom that more competition is always desirable