Karlsruhe Institute of Technology

Displaying 1-40 of 93 results

  • White Papers // Jan 2014

    Interacting with Statistical Linked Data via OLAP Operations

    On-Line Analytical Processing (OLAP) promises an interface to analyze Linked Data containing statistics going beyond other interaction paradigms such as follow-your-nose browsers, faceted-search interfaces and query builders. As a new way to interact with statistical Linked Data the authors define common OLAP operations on data cubes modelled in RDF and...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Nov 2013

    Scalable and Live Trace Processing with Kieker Utilizing Cloud Computing

    Knowledge of the internal behavior of applications often gets lost over the years. This paper can arise, for example, from missing documentation. Application-level monitoring, e.g., provided by the researcher, can help with the comprehension of such internal behavior. However, it can have large impact on the performance of the monitored...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Oct 2013

    Future Challenges for Linked APIs

    A number of approaches combine the principles and technologies of linked data and RESTful services. Services and APIs are thus enriched by, and contribute to, the web of data. These resource-centric approaches, referred to as linked APIs, focus on flexibility and the integration capabilities of linked data. The authors use...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Oct 2013

    Knowledge Discovery meets Linked APIs

    Knowledge Discovery and Data Mining (KDD) is a very well-established research field with useful techniques that explore patterns and regularities in large relational, structured and unstructured datasets. Theoretical and practical development in this field have led to useful and scalable solutions for the tasks of pattern mining, clustering, graph mining,...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Sep 2013

    Towards Online Performance Model Extraction in Virtualized Environments

    Virtualization increases the complexity and dynamics of modern software architectures making it a major challenge to manage the end-to-end performance of applications. Architecture-level performance models can help here as they provide the modeling power and analysis flexibility to predict the performance behavior of applications under varying workloads and configurations. However,...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Sep 2013

    Model-Based Throughput Prediction in Data Center Networks

    In this paper, the authors address the problem of performance analysis in computer networks. They present a new meta-model designed for the performance modeling of network infrastructures in modern data centers. Instances of their meta-model can be automatically transformed into stochastic simulation models for performance prediction. They evaluate the approach...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Jul 2013

    Vectorizing Database Column Scans with Complex Predicates

    The performance of the full table scan is critical for the overall performance of column-store database systems such as the SAP HANA database. Compressing the underlying column data format is both an advantage and a challenge, because it reduces the data volume involved in a scan on one hand and...

    Provided By Karlsruhe Institute of Technology

  • White Papers // May 2013

    Elasticity in Cloud Computing: What It Is, and What It Is Not

    Originating from the field of physics and economics, the term elasticity is nowadays heavily used in the context of cloud computing. In this context, elasticity is commonly understood as the ability of a system to automatically provision and deprovision computing resources on demand as workloads change. However, elasticity still lacks...

    Provided By Karlsruhe Institute of Technology

  • White Papers // May 2013

    A Method for Simulating Cloud Business Models: A Case Study on Platform as a Service

    Cloud computing has changed how software is produced, distributed, consumed, and priced. The cloud paradigm has had a disruptive effect on existing business models and elicited a need for more thoroughly defined business models as well as the tools to represent and compare business models. In this paper, the authors...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Dec 2012

    Towards Truthful Resource Reservation in Cloud Computing

    Prudent capacity planning to meet their clients future computational needs is one of the major issues cloud computing providers face today. By offering resource reservations in advance, providers gain insight into the projected demand of their customers and can act accordingly. However, customers need to be given an incentive, e.g....

    Provided By Karlsruhe Institute of Technology

  • White Papers // Dec 2012

    Decentralized Control Based on Globally Optimal Estimation

    A new method for globally optimal estimation in decentralized sensor-networks is applied to the decentralized control problem. The resulting approach is proven to be optimal when the nodes have access to all information in the network. More precisely, the authors utilize an algorithm for optimal distributed estimation in order to...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Nov 2012

    A Social Content Delivery Network for Scientific Cooperation: Vision, Design, and Architecture

    Data volumes have increased so significantly that the authors need to carefully consider how they interact with, share, and analyze data to avoid bottlenecks. In contexts such as e-Science and scientific computing, a large emphasis is placed on collaboration, resulting in many well-known challenges in ensuring that data is in...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Oct 2012

    Network Virtualization for QoS-Aware Resource Management in Cloud Data Centers: A Survey

    The increasing popularity of Cloud Computing is leading to the emergence of large virtualized data centers hosting increasingly complex and dynamic IT systems and services. Over the past decade, the efficient sharing of computational resources through virtualization has been subject to intensive research, while network management in cloud data centers...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Sep 2012

    Optimal Point Estimates for Multi-Target States Based on Kernel Distances

    Almost all multi-target tracking systems have to generate point estimates for the targets, e.g., for displaying the tracks. The novel idea in this paper is to consider point estimates for multi-target states that are optimal according to a kernel distance measure. Because the kernel distance is a metric on point...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Sep 2012

    Stochastic Nonlinear Model Predictive Control Based on Progressive Density Simplification

    Increasing demand for nonlinear model predictive control with the ability to handle highly noise-corrupted systems has recently given rise to stochastic control approaches. Besides providing high-quality results within a noisy environment, these approaches have one problem in common, namely a high computational demand and, as a consequence, generally a short...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Sep 2012

    Sequence-Based Control for Networked Control Systems Based on Virtual Control Inputs

    In this paper, the authors address the problem of controlling a system over an unreliable UDP-like network that is affected by time-varying delays and randomly occurring packet losses. A major challenge of this setup is that the controller just has uncertain information about the control inputs actually applied by the...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Sep 2012

    Optimal Kalman Gains for Combined Stochastic and Set-Membership State Estimation

    In state estimation theory, two directions are mainly followed in order to model disturbances and errors. Either uncertainties are modeled as stochastic quantities or they are characterized by their membership to a set. Both approaches have distinct advantages and disadvantages making each one inherently better suited to model different sources...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Aug 2012

    A Conceptual Framework for Simulating Autonomic Cloud Markets

    One of the major challenges facing the Cloud paradigm is the emergence of suitable economic platforms for the trading of Cloud services. Today, many researchers investigate how specific Cloud market platforms can be conceived and in some cases implemented. However, such endeavours consider only specific types of actors, business models,...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Jul 2012

    Control Over Unreliable Networks Based on Control Input Densities

    Time delays and data losses arising from an unreliable communication between the components of a control loop decrease the quality of control and thus, have to be incorporated explicitly in the control decision. In this paper, a novel concept, the so-called virtual control inputs, is presented, which extends the well-established...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Jul 2012

    Combined Stochastic and Set-Membership Information Filtering in Multisensor Systems

    In state estimation theory, stochastic and set membership approaches are generally considered separately from each other. Both concepts have distinct advantages and disadvantages making each one inherently better suited to model different sources of estimation uncertainty. In order to better utilize the potentials of both concepts, the core element of...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Jun 2012

    Tightly Secure Signatures and Public-Key Encryption

    The authors construct the first public-key encryption scheme whose chosen-ciphertext (i.e., INDCCA) security can be proved under a standard assumption and does not degrade in either the number of users or the number of ciphertexts. In particular, their scheme can be safely deployed in unknown settings in which no a-priori...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Jun 2012

    Spectral Estimation-Based OFDM Radar Algorithms for IEEE 802.11a Signals

    Recently, OFDM radar has gained attention as new algorithms for range and Doppler estimation specific to OFDM signals have been developed. The major advantage of OFDM is that it is both well-suited for radar processing as well as being suitable for communication. In previous work, the authors have proposed parametrizations...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Jun 2012

    Collision-Balancing Frequency Hopping in Single-Hop Mobile Ad Hoc Networks

    The authors consider a single-hop Frequency Hopping (FH) Mobile Ad hoc NETwork (MANET). To increase throughput Orthogonal FH (O-FH) with hop-synchronous hopping can be used, thereby allowing collision-free transmissions under certain circumstances. However, as the MANET grows, hopping sequences must be re-used. As a result, nodes sharing the same sequence...

    Provided By Karlsruhe Institute of Technology

  • White Papers // May 2012

    Hopping Strategies for Adaptive FH-CDMA Ad Hoc Networks Under External Interference

    The authors discuss the performance of an adaptive FHCDMA ad hoc network under the influence of external interference where node positions are modeled by a homogeneous Poisson point process. The optimum channel assignment that balances internal network interference due to spatial reuse and external interference is derived analytically for a...

    Provided By Karlsruhe Institute of Technology

  • White Papers // May 2012

    Adaptive Frequency Hopping in Ad Hoc Networks With Rayleigh Fading and Imperfect Sensing

    A probabilistic model for Adaptive Frequency Hopping (AFH) based wireless ad hoc networks with Rayleigh fading, where interference is due to self - and to slow-varying external interference, is proposed. Different AFH sensing techniques are studied in terms of Area Spectral Efficiency (ASE) and it is shown that self-interference can...

    Provided By Karlsruhe Institute of Technology

  • White Papers // May 2012

    Increasing the One-Hop Progress of Nearest Neighbor Forwarding

    Wireless networks have recently gained much attraction due to several reasons: research on hardware has achieved considerable advances in the development of small and inexpensive communications devices. A fundamental property of these networks is that communication does not rely on a wired backbone. Hence, nodes additionally have to function as...

    Provided By Karlsruhe Institute of Technology

  • White Papers // May 2012

    Tracking 3D Shapes in Noisy Point Clouds With Random Hypersurface Models

    State of the art depth-sensors such as range cameras (time-of-flight, structured light, stereo) or laser rangefinder obtain three-dimensional point cloud data of a given real-world scene. Recently, multi-sensor setups have received increasing attention. Point clouds have become highly relevant for many real world applications, such as surveillance, target tracking, 3D...

    Provided By Karlsruhe Institute of Technology

  • White Papers // May 2012

    Interference and Throughput in Aloha-based Ad Hoc Networks With Isotropic Node Distribution

    The authors study the interference and outage statistics in a slotted Aloha ad hoc network, where the spatial distribution of nodes is non-stationary and isotropic. In such a network, outage probability and local throughput depend on both the particular location in the network and the shape of the spatial distribution....

    Provided By Karlsruhe Institute of Technology

  • White Papers // May 2012

    Modeling the Target Extent With Multiplicative Noise

    Extended target tracking deals with simultaneously tracking the shape and the kinematic parameters of a target. In this paper, the authors formulate the extended target tracking problem as a state estimation problem with both multiplicative and additive measurement noise. In case of extended targets with known orientation, they show that...

    Provided By Karlsruhe Institute of Technology

  • White Papers // May 2012

    State Estimation in Networked Control Systems

    The authors consider the problem of state estimation in a Networked Control System, where measurements and control inputs are transmitted via a communication network. The network is subject to time-varying delays and stochastic data losses and does not provide acknowledgments of successfully transmitted data packets. A challenge that arises in...

    Provided By Karlsruhe Institute of Technology

  • White Papers // May 2012

    A Robust Computational Test for Overlap of Two Arbitrary-Dimensional Ellipsoids in Fault-Detection of Kalman Filters

    On-line fault-detection in uncertain measurement and estimation systems is of particular interest in many applications. In certain systems based on the Kalman filter, this test can be performed by checking whether hyper-ellipsoids overlap. This test can be applied to detecting failure in the system itself or in the sensors used...

    Provided By Karlsruhe Institute of Technology

  • White Papers // May 2012

    Recursive Bayesian Calibration of Depth Sensors With Non-Overlapping Views

    Setting up a network of multiple depth sensors introduces several issues that need to be addressed. For example, the popular Microsoft Kinect TM device acquires depth information using an active measurement system which projects an infrared pattern. This has important consequences in setups with overlapping fields of view, where the...

    Provided By Karlsruhe Institute of Technology

  • White Papers // May 2012

    On Optimal Distributed Kalman Filtering in Non-Ideal Situations

    The distributed processing of measurements and the subsequent data fusion is called Track-to-Track fusion. Although a solution for the Track-to-Track fusion that is equivalent to a central processing scheme has been proposed, this algorithm suffers from strict requirements regarding the local availability of knowledge about utilized models of the remote...

    Provided By Karlsruhe Institute of Technology

  • White Papers // May 2012

    Group Activity Recognition Using Mobile Devices

    Group activities are more than the sum of the activities of the individuals in them, but are rather generated by those activities and interactions between group members. This paper proposes Group Activity Recognition (GAR) using collaborative mobile user devices for sensing, processing and recognition. The contribution is a thorough evaluation...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Apr 2012

    CloudGenius: Decision Support for Web Server Cloud Migration

    Cloud computing is the latest computing paradigm that delivers hardware and software resources as virtualized services in which users are free from the burden of worrying about the low-level system administration details. Migrating Web applications to Cloud services and integrating Cloud services into existing computing infrastructures is non-trivial. It leads...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Apr 2012

    A Semantically Enabled Architecture for Crowdsourced Linked Data Management

    Increasing amounts of structured data are exposed on the web using graph-based representation models and protocols such as RDF and SPARQL. Nevertheless, while the overall volume of such open, or easily accessible, data sources reaches critical mass, the ability of potential consumers to use them in novel applications and services...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Apr 2012

    A USRP-Based Testbed for OFDM-Based Radar and Communication Systems

    In this paper, the authors present a measurement testbed for OFDM radar which uses USRPs as a front-end. The resulting system, using two USRPs and a laptop, requires little power and can thus be easily installed in vehicles to perform measurements for car-to-car or car-to-infrastructure applications. As an example, they...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Apr 2012

    SLA Based Service Brokering in Intercloud Environments

    The fast emerging Cloud computing market over the last years resulted in a variety of heterogeneous and less interoperable Cloud infrastructures. This leads to a challenging and urgent problem for Cloud users when selecting their best fitting Cloud provider and hence it ties them to a particular provider. A new...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Apr 2012

    The KeY Approach for the Cryptographic Verification of JAVA Programs: A Case Study

    In this paper, the authors report on an ongoing case study in which they use the KeY tool, a theorem prover for checking functional correctness and noninterference properties of JAVA programs, to establish computational indistinguishability for a simple JAVA program that involves clients sending encrypted messages over an untrusted network...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Mar 2012

    Optimizing Practical Adaptive Frequency Hopping and Medium Access Control in Ad Hoc Networks

    Adaptive Frequency Hopping (AFH) as proposed, e.g., in IEEE 802.15.2 aims at increasing system reliability in the presence of quasi-static external interference. Practical approaches require autonomous sensing of the interference environment, with the measurements containing both external interference and network self-interference. In prior work, a simplistic model for AFH-based ad...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Jan 2012

    KSM++: Using I/O-Based Hints to Make Memory-Deduplication Scanners More Efficient

    Memory scanning deduplication techniques, as implemented in Linux' Kernel Samepage Merging (KSM), work very well for deduplicating fairly static, anonymous pages with equal content across different virtual machines. However, scanners need very aggressive scan rates when it comes to identifying sharing opportunities with a short life span of up to...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Jul 2013

    Vectorizing Database Column Scans with Complex Predicates

    The performance of the full table scan is critical for the overall performance of column-store database systems such as the SAP HANA database. Compressing the underlying column data format is both an advantage and a challenge, because it reduces the data volume involved in a scan on one hand and...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Jul 2011

    A Hypervisor-Based Bus System for Usage Control

    Usage control, generalizes access control to what happens to data after access has been granted. This is particularly difficult in distributed settings. Data usage control is concerned with requirements on data after access has been granted. In order to enforce usage control requirements, it is necessary to track the different...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Feb 2012

    A Virtualized Usage Control Bus System

    Usage control is an extension of access control that additionally defines what must and must not happen to data after access has been granted. The process of enforcing usage control requirements on data must take into account all the different representations that the data may assume at different levels of...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Sep 2012

    Stochastic Nonlinear Model Predictive Control Based on Progressive Density Simplification

    Increasing demand for nonlinear model predictive control with the ability to handle highly noise-corrupted systems has recently given rise to stochastic control approaches. Besides providing high-quality results within a noisy environment, these approaches have one problem in common, namely a high computational demand and, as a consequence, generally a short...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Sep 2012

    Optimal Point Estimates for Multi-Target States Based on Kernel Distances

    Almost all multi-target tracking systems have to generate point estimates for the targets, e.g., for displaying the tracks. The novel idea in this paper is to consider point estimates for multi-target states that are optimal according to a kernel distance measure. Because the kernel distance is a metric on point...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Sep 2012

    Sequence-Based Control for Networked Control Systems Based on Virtual Control Inputs

    In this paper, the authors address the problem of controlling a system over an unreliable UDP-like network that is affected by time-varying delays and randomly occurring packet losses. A major challenge of this setup is that the controller just has uncertain information about the control inputs actually applied by the...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Sep 2012

    Optimal Kalman Gains for Combined Stochastic and Set-Membership State Estimation

    In state estimation theory, two directions are mainly followed in order to model disturbances and errors. Either uncertainties are modeled as stochastic quantities or they are characterized by their membership to a set. Both approaches have distinct advantages and disadvantages making each one inherently better suited to model different sources...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Dec 2012

    Decentralized Control Based on Globally Optimal Estimation

    A new method for globally optimal estimation in decentralized sensor-networks is applied to the decentralized control problem. The resulting approach is proven to be optimal when the nodes have access to all information in the network. More precisely, the authors utilize an algorithm for optimal distributed estimation in order to...

    Provided By Karlsruhe Institute of Technology

  • White Papers // May 2012

    Modeling the Target Extent With Multiplicative Noise

    Extended target tracking deals with simultaneously tracking the shape and the kinematic parameters of a target. In this paper, the authors formulate the extended target tracking problem as a state estimation problem with both multiplicative and additive measurement noise. In case of extended targets with known orientation, they show that...

    Provided By Karlsruhe Institute of Technology

  • White Papers // May 2012

    State Estimation in Networked Control Systems

    The authors consider the problem of state estimation in a Networked Control System, where measurements and control inputs are transmitted via a communication network. The network is subject to time-varying delays and stochastic data losses and does not provide acknowledgments of successfully transmitted data packets. A challenge that arises in...

    Provided By Karlsruhe Institute of Technology

  • White Papers // May 2012

    A Robust Computational Test for Overlap of Two Arbitrary-Dimensional Ellipsoids in Fault-Detection of Kalman Filters

    On-line fault-detection in uncertain measurement and estimation systems is of particular interest in many applications. In certain systems based on the Kalman filter, this test can be performed by checking whether hyper-ellipsoids overlap. This test can be applied to detecting failure in the system itself or in the sensors used...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Jul 2012

    Control Over Unreliable Networks Based on Control Input Densities

    Time delays and data losses arising from an unreliable communication between the components of a control loop decrease the quality of control and thus, have to be incorporated explicitly in the control decision. In this paper, a novel concept, the so-called virtual control inputs, is presented, which extends the well-established...

    Provided By Karlsruhe Institute of Technology

  • White Papers // May 2012

    Tracking 3D Shapes in Noisy Point Clouds With Random Hypersurface Models

    State of the art depth-sensors such as range cameras (time-of-flight, structured light, stereo) or laser rangefinder obtain three-dimensional point cloud data of a given real-world scene. Recently, multi-sensor setups have received increasing attention. Point clouds have become highly relevant for many real world applications, such as surveillance, target tracking, 3D...

    Provided By Karlsruhe Institute of Technology

  • White Papers // May 2012

    Recursive Bayesian Calibration of Depth Sensors With Non-Overlapping Views

    Setting up a network of multiple depth sensors introduces several issues that need to be addressed. For example, the popular Microsoft Kinect TM device acquires depth information using an active measurement system which projects an infrared pattern. This has important consequences in setups with overlapping fields of view, where the...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Jul 2012

    Combined Stochastic and Set-Membership Information Filtering in Multisensor Systems

    In state estimation theory, stochastic and set membership approaches are generally considered separately from each other. Both concepts have distinct advantages and disadvantages making each one inherently better suited to model different sources of estimation uncertainty. In order to better utilize the potentials of both concepts, the core element of...

    Provided By Karlsruhe Institute of Technology

  • White Papers // May 2012

    On Optimal Distributed Kalman Filtering in Non-Ideal Situations

    The distributed processing of measurements and the subsequent data fusion is called Track-to-Track fusion. Although a solution for the Track-to-Track fusion that is equivalent to a central processing scheme has been proposed, this algorithm suffers from strict requirements regarding the local availability of knowledge about utilized models of the remote...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Jul 2011

    Fitting Conics to Noisy Data Using Stochastic Linearization

    Fitting conic sections, e.g., ellipses or circles, to noisy data points is a fundamental sensor data processing problem, which frequently arises in robotics. In this paper, the authors introduce a new procedure for deriving a recursive Gaussian state estimator for fitting conics to data corrupted by additive Gaussian noise. For...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Nov 2012

    A Social Content Delivery Network for Scientific Cooperation: Vision, Design, and Architecture

    Data volumes have increased so significantly that the authors need to carefully consider how they interact with, share, and analyze data to avoid bottlenecks. In contexts such as e-Science and scientific computing, a large emphasis is placed on collaboration, resulting in many well-known challenges in ensuring that data is in...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Oct 2012

    Network Virtualization for QoS-Aware Resource Management in Cloud Data Centers: A Survey

    The increasing popularity of Cloud Computing is leading to the emergence of large virtualized data centers hosting increasingly complex and dynamic IT systems and services. Over the past decade, the efficient sharing of computational resources through virtualization has been subject to intensive research, while network management in cloud data centers...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Dec 2012

    Towards Truthful Resource Reservation in Cloud Computing

    Prudent capacity planning to meet their clients future computational needs is one of the major issues cloud computing providers face today. By offering resource reservations in advance, providers gain insight into the projected demand of their customers and can act accordingly. However, customers need to be given an incentive, e.g....

    Provided By Karlsruhe Institute of Technology

  • White Papers // May 2013

    Elasticity in Cloud Computing: What It Is, and What It Is Not

    Originating from the field of physics and economics, the term elasticity is nowadays heavily used in the context of cloud computing. In this context, elasticity is commonly understood as the ability of a system to automatically provision and deprovision computing resources on demand as workloads change. However, elasticity still lacks...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Aug 2012

    A Conceptual Framework for Simulating Autonomic Cloud Markets

    One of the major challenges facing the Cloud paradigm is the emergence of suitable economic platforms for the trading of Cloud services. Today, many researchers investigate how specific Cloud market platforms can be conceived and in some cases implemented. However, such endeavours consider only specific types of actors, business models,...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Feb 2012

    Towards Large-Scale Network Virtualization

    Most existing Virtual Network (VN) provisioning approaches assume a single administrative domain and therefore, VN deployments are limited to the geographic footprint of the substrate provider. To enable wide-area VN provisioning, network virtualization architectures need to address the intricacies of inter-domain aspects, i.e., how to provision VNs with limited control...

    Provided By Karlsruhe Institute of Technology

  • White Papers // May 2013

    A Method for Simulating Cloud Business Models: A Case Study on Platform as a Service

    Cloud computing has changed how software is produced, distributed, consumed, and priced. The cloud paradigm has had a disruptive effect on existing business models and elicited a need for more thoroughly defined business models as well as the tools to represent and compare business models. In this paper, the authors...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Feb 2011

    Implementing Trust in Cloud Infrastructures

    Today's cloud computing infrastructures usually require customers who transfer data into the cloud to trust the providers of the cloud infrastructure. Not every customer is willing to grant this trust without justification. It should be possible to detect that at least the configuration of the cloud infrastructure - as provided...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Apr 2011

    Semantic Support for Security-Annotated Business Process Models

    Service-Oriented Architectures (SOA) benefit from Business Processes (BP), which orchestrate Web Services (WS) and human actors in cross organizational environments. In this setting, handling the security and privacy issues while exchanging and processing personal data is essential. This lacks for secure business processes management. To achieve this, the authors represent...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Sep 2013

    Model-Based Throughput Prediction in Data Center Networks

    In this paper, the authors address the problem of performance analysis in computer networks. They present a new meta-model designed for the performance modeling of network infrastructures in modern data centers. Instances of their meta-model can be automatically transformed into stochastic simulation models for performance prediction. They evaluate the approach...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Nov 2011

    Providing Dependability and Performance in the Cloud: Case Studies

    In this paper, the authors present three case studies as examples on how the previously mentioned challenges can be addressed and how the opportunities can be used to add value to systems running in cloud computing environments. The first two case studies are approaches on managing performance and dependability in...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Jan 2011

    Completeness Theorems with Constructive Proofs for Finite Deterministic 2-Party Functions

    In this paper the authors present simple but comprehensive combinatorial criteria for completeness of finite deterministic 2-party functions with respect to information-theoretic security. They give a general protocol construction for efficient and statistically secure reduction of oblivious transfer to any finite deterministic 2-party function that fulfills their criteria. For the...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Jan 2011

    Unconditional and Composable Security Using a Single Stateful Tamper-Proof Hardware Token

    Cryptographic assumptions regarding tamper proof hardware tokens have gained increasing attention. Even if the tamper-proof hardware is issued by one of the parties, and hence not necessarily trusted by the other, many tasks become possible: tamper proof hardware is sufficient for universally composable protocols, for information-theoretically secure protocols, and even...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Feb 2010

    Encryption Schemes Secure Against Chosen-Ciphertext Selective Opening Attacks

    Imagine many small devices send data to a single receiver, encrypted using the receiver's public key. Assume an adversary that has the power to adaptively corrupt a subset of these devices. Given the information obtained from these corruptions, do the ciphertexts from uncorrupted devices remain secure? Recent results suggest that...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Nov 2013

    Scalable and Live Trace Processing with Kieker Utilizing Cloud Computing

    Knowledge of the internal behavior of applications often gets lost over the years. This paper can arise, for example, from missing documentation. Application-level monitoring, e.g., provided by the researcher, can help with the comprehension of such internal behavior. However, it can have large impact on the performance of the monitored...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Apr 2012

    A Semantically Enabled Architecture for Crowdsourced Linked Data Management

    Increasing amounts of structured data are exposed on the web using graph-based representation models and protocols such as RDF and SPARQL. Nevertheless, while the overall volume of such open, or easily accessible, data sources reaches critical mass, the ability of potential consumers to use them in novel applications and services...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Apr 2010

    Orel: Database-Driven Reasoning for OWL 2 Profiles

    With the standardisation of the web ontology Language OWL 2 in 2009, the development of theoretically well-studied and practically deployable expressive ontology languages for the semantic web has reached a new level of maturity. The authors describe Orel, a reasoning system for an ontology language which subsumes both the EL...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Jan 2014

    Interacting with Statistical Linked Data via OLAP Operations

    On-Line Analytical Processing (OLAP) promises an interface to analyze Linked Data containing statistics going beyond other interaction paradigms such as follow-your-nose browsers, faceted-search interfaces and query builders. As a new way to interact with statistical Linked Data the authors define common OLAP operations on data cubes modelled in RDF and...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Sep 2013

    Towards Online Performance Model Extraction in Virtualized Environments

    Virtualization increases the complexity and dynamics of modern software architectures making it a major challenge to manage the end-to-end performance of applications. Architecture-level performance models can help here as they provide the modeling power and analysis flexibility to predict the performance behavior of applications under varying workloads and configurations. However,...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Oct 2013

    Future Challenges for Linked APIs

    A number of approaches combine the principles and technologies of linked data and RESTful services. Services and APIs are thus enriched by, and contribute to, the web of data. These resource-centric approaches, referred to as linked APIs, focus on flexibility and the integration capabilities of linked data. The authors use...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Oct 2013

    Knowledge Discovery meets Linked APIs

    Knowledge Discovery and Data Mining (KDD) is a very well-established research field with useful techniques that explore patterns and regularities in large relational, structured and unstructured datasets. Theoretical and practical development in this field have led to useful and scalable solutions for the tasks of pattern mining, clustering, graph mining,...

    Provided By Karlsruhe Institute of Technology

  • White Papers // Apr 2012

    The KeY Approach for the Cryptographic Verification of JAVA Programs: A Case Study

    In this paper, the authors report on an ongoing case study in which they use the KeY tool, a theorem prover for checking functional correctness and noninterference properties of JAVA programs, to establish computational indistinguishability for a simple JAVA program that involves clients sending encrypted messages over an untrusted network...

    Provided By Karlsruhe Institute of Technology