Role-based Data Management

Database systems build an integral component of today’s software systems and as such they are the central point for storing and sharing a software system’s data while ensuring global data consistency at the same time. Introducing the primitives of roles and their accompanied metatype distinction in modeling and programming languages, results in a novel paradigm of designing, extending, and programming modern software systems. In detail, roles as modeling concept enable a separation of concerns within an entity. Along with its rigid core, an entity may acquire various roles in different contexts during its lifetime and thus, adapts its behavior and structure dynamically during runtime. Unfortunately, database systems, as important component and global consistency provider of such systems, do not keep pace with this trend. The absence of a metatype distinction, in terms of an entity’s separation of concerns, in the database system results in various problems for the software system in general, for the application developers, and finally for the database system itself. In case of relational database systems, these problems are concentrated under the term role-relational impedance mismatch. In particular, the whole software system is designed by using different semantics on various layers. In case of role-based software systems in combination with relational database systems this gap in semantics between applications and the database system increases dramatically. Consequently, the database system cannot directly represent the richer semantics of roles as well as the accompanied consistency constraints. These constraints have to be ensured by the applications and the database system loses its single point of truth characteristic in the software system. As the applications are in charge of guaranteeing global consistency, their development requires more effort in data management. Moreover, the software system’s data management is distributed over several layers, which results in an unstructured software system architecture. To overcome the role-relational impedance mismatch and bring the database system back in its rightful position as single point of truth in a software system, this thesis introduces the novel and tripartite RSQL approach. It combines a novel database model that represents the metatype distinction as first class citizen in a database system, an adapted query language on the database model’s basis, and finally a proper result representation. Precisely, RSQL’s logical database model introduces Dynamic Data Types, to directly represent the separation of concerns within an entity type on the schema level. On the instance level, the database model defines the notion of a Dynamic Tuple that combines an entity with the notion of roles and thus, allows for dynamic structure adaptations during runtime without changing an entity’s overall type. These definitions build the main data structures on which the database system operates. Moreover, formal operators connecting the query language statements with the database model data structures, complete the database model. The query language, as external database system interface, features an individual data definition, data manipulation, and data query language. Their statements directly represent the metatype distinction to address Dynamic Data Types and Dynamic Tuples, respectively. As a consequence of the novel data structures, the query processing of Dynamic Tuples is completely redesigned. As last piece for a complete database integration of a role-based notion and its accompanied metatype distinction, we specify the RSQL Result Net as result representation. It provides a novel result structure and features functionalities to navigate through query results. Finally, we evaluate all three RSQL components in comparison to a relational database system. This assessment clearly demonstrates the benefits of the roles concept’s full database integration

Towards a Role-Based Contextual Database

Traditional modeling approaches and information systems assume static entities that represent all information and attributes at once. However, due to the evolution of information systems to increasingly context-aware and self-adaptive systems, this assumption no longer holds. To cope with the required flexibility, the role concept was introduced. Although researchers have proposed several role modeling approaches, they usually neglect the contextual characteristics of roles and their representation in database management systems. Unfortunately, these systems do not rely on a conceptual model of an information system, rather they model this information by their own means leading to transformation and maintenance overhead. So far, the challenges posed by dynamic complex entities, their first class implementation, and their contextual characteristics lack detailed investigations in the area of database management systems. Hence, this paper, presents an approach that ties a conceptual role-based data model and its database implementation together, to directly represent the information modeled conceptually inside a database management system. In particular, we propose a formal database model to describe roles and their contextual information in compartments. Moreover, to provide a context-dependent role-based database interface, we extend RSQL by compartments. Finally, we introduce RSQL Result Net to preserve the contextual role semantics as well as enable users and applications to both iterate and navigate over results produced by RSQL. In sum, these means allow for a coherent design of more dynamic, complex software systems

RSQL - a query language for dynamic data types

Database Management Systems (DBMS) are used by software applications, to store, manipulate, and retrieve large sets of data. However, the requirements of current software systems pose various challenges to established DBMS. First, most software systems organize their data by means of objects rather than relations leading to increased maintenance, redundancy, and transformation overhead when persisting objects to relational databases. Second, complex objects are separated into several objects resulting in Object Schizophrenia and hard to persist Distributed State. Last but not least, current software systems have to cope with increased complexity and changes. These challenges have lead to a general paradigm shift in the development of software systems. Unfortunately, classical DBMS will become intractable, if they are not adapted to the new requirements imposed by these software systems. As a result, we propose an extension of DBMS with roles to represent complex objects within a relational database and support the exibility required by current software systems. To achieve this goal, we introduces RSQL, an extension to SQL with the concept of objects playing roles when interacting with other objects. Additionally, we present a formal model for the logical representation of roles in the extended DBMS

Position paper: Runtime Model for Role-based Software Systems

In the increasingly dynamic realities of today's software systems, it is no longer feasible to always expect human developers to react to changing environments and changing conditions immediately. Instead, software systems need to be self-aware and autonomously adapt their behavior according to their experiences gathered from their environment. Current research provides role-based modeling as a promising approach to handle the adaptivity and self-awareness within a software system. There are established role-based systems e.g., for application development, persistence, and so on. However, these are isolated approaches using the role-based model on their specific layer and mapping to existing non-role-based layers. We present a global runtime model covering the whole stack of a software system to maintain a global view of the current system state and model the interdependencies between the layers. This facilitates building holistic role-based software systems using the role concept on every single layer to exploit its full potential, particularly adaptivity and self-awareness

Comparing the Outage Capacity of Transmit Diversity and Incremental Relaying

We present the e-outage capacity of incremental relaying at low signal-to-noise ratios (SNR) in a wireless cooperative network with slow Rayleigh fading channels. The relay performs decode-and-forward and repetition coding is employed in the network, which is optimal in the low SNR regime. We derive an expression on the optimal relay location that maximizes the e-outage capacity. It is shown that this location is independent of the outage probability and SNR but only depends on the channel conditions represented by a path-loss factor. We compare our results to the e-outage capacity of the cut-set bound and demonstrate that the ratio between the e-outage capacity of incremental relaying and the cut-set bound lies within 1/wurzel2 and 1. Furthermore, we derive lower bounds on the e-outage capacity for the case of K relays

Derivation of aerosol optical properties using ground-based radiation measurements

The knowledge of the optical and microphysical properties of aerosol particles in the atmosphere is relevant in various scientific fields from public health issues to climate modeling. A retrieval method is presented that estimates the single scattering albedo and asymmetry parameter of aerosol particles in regions of high pollution using spectral ground-based radiance and irradiance measurements, radiative transfer simulations, and a priori knowledge of the aerosol optical depth (AOD) derived from sun photometer observations. The used measurement data originated from the Pearl River Delta in China. The results are compared with sun photometer data and show a high agreement for AODs larger than 0.5. For low AODs and for cloudy conditions the method did not work due to the strong sensitivity of the initial parameters.Kenntnisse über optische und mikrophysikalische Eigenschaften von Aerosolpartikeln in der Atmosphäre werden in vielen verschiedenen wissenschaftlichen Gebieten benötigt. Diese reichen vom Gesundheitswesen bis hin zur Klimamodellierung. Deswegen wird im Folgenden eine Ableitungsmethode vorgestellt, die die Einfachstreualbedo und Asymmtrieparameter von Aerosolpartikeln bestimmt. Diese Methode wurde dabei für Messungen im Pearl River Delta, China, in denen oft hohe Luftverschmutzungen auftreten, angewandt. Es werden dazu bodengebundene Messungen der spektralen abwärtsgerichteten Strahlungsflussdichte und Strahldichte, gekoppelt mit Strahlungsübertragungsrechnungen durchgeführt. Um die aerosoloptischen Parameter ableiten zu können, wird als zusätzliche Randbedingung die aerosol-optische Dicke (AOD) benötigt. Sonnenphotometermessungen liefern dabei zum einen die AOD und zum anderen die aerosoloptische Eigenschaften, die mit den Ergebnissen der Ableitungsmethode verglichen werden. Dabei wurden für große AOD-Werte (über 0.5) gute Übereinstimmungen zwischen beiden Methoden festgestellt werden. Für AOD-Werte kleiner als 0.5 und bei bewölkten Bedingungen zeigt die Methode große Unsicherheiten, weil die Parameter zu empfindlich auf diese Begebenheiten reagieren

Combining atmospheric and snow radiative transfer models to assess the solar radiative effects of black carbon in the Arctic

The magnitude of solar radiative effects (cooling or warming) of black carbon (BC) particles embedded in the Arctic atmosphere and surface snow layer was explored on the basis of case studies. For this purpose, combined at- mospheric and snow radiative transfer simulations were per- formed for cloudless and cloudy conditions on the basis of BC mass concentrations measured in pristine early summer and more polluted early spring conditions. The area of inter- est is the remote sea-ice-covered Arctic Ocean in the vicin- ity of Spitsbergen, northern Greenland, and northern Alaska typically not affected by local pollution. To account for the radiative interactions between the black-carbon-containing snow surface layer and the atmosphere, an atmospheric and snow radiative transfer model were coupled iteratively. For pristine summer conditions (no atmospheric BC, minimum solar zenith angles of 55◦) and a representative BC particle mass concentration of 5 ng g−1 in the surface snow layer, a positive daily mean solar radiative forcing of +0.2Wm−2 was calculated for the surface radiative budget. A higher load of atmospheric BC representing early springtime conditions results in a slightly negative mean radiative forcing at the surface of about −0.05 W m−2, even when the low BC mass concentration measured in the pristine early summer condi- tions was embedded in the surface snow layer. The total net surface radiative forcing combining the effects of BC em- bedded in the atmosphere and in the snow layer strongly de- pends on the snow optical properties (snow specific surface area and snow density). For the conditions over the Arctic Ocean analyzed in the simulations, it was found that the at- mospheric heating rate by water vapor or clouds is 1 to 2 or-ders of magnitude larger than that by atmospheric BC. Sim- ilarly, the daily mean total heating rate (6 K d−1) within a snowpack due to absorption by the ice was more than 1 order of magnitude larger than that of atmospheric BC (0.2 K d−1). Also, it was shown that the cooling by atmospheric BC of the near-surface air and the warming effect by BC embedded in snow are reduced in the presence of clouds

A Novel Combining Receiver for a Dual-Diversity Wireless Relay Network

We present a simple combining receiver for a dual-diversity wireless relay network. The main concern of the paper is to face the trade-off between performance and complexity. The receiver focuses on signal-to-noise ratio (SNR) monitoring and selects dynamically between selection combining (SC) and equal gain combining (EGC) depending on the SNR ratio of the two received branches. It is shown that SC suffers no SNR degradation compared to a single branch communications system if the two receive branches are unbalanced, wheres EGC suffers a loss of 3 dB. Error performance with respect to branch unbalance is considered as well and limiting values for a high degree of branch unbalance are derived

Role-based Data Management

Database systems build an integral component of today’s software systems and as such they are the central point for storing and sharing a software system’s data while ensuring global data consistency at the same time. Introducing the primitives of roles and their accompanied metatype distinction in modeling and programming languages, results in a novel paradigm of designing, extending, and programming modern software systems. In detail, roles as modeling concept enable a separation of concerns within an entity. Along with its rigid core, an entity may acquire various roles in different contexts during its lifetime and thus, adapts its behavior and structure dynamically during runtime. Unfortunately, database systems, as important component and global consistency provider of such systems, do not keep pace with this trend. The absence of a metatype distinction, in terms of an entity’s separation of concerns, in the database system results in various problems for the software system in general, for the application developers, and finally for the database system itself. In case of relational database systems, these problems are concentrated under the term role-relational impedance mismatch. In particular, the whole software system is designed by using different semantics on various layers. In case of role-based software systems in combination with relational database systems this gap in semantics between applications and the database system increases dramatically. Consequently, the database system cannot directly represent the richer semantics of roles as well as the accompanied consistency constraints. These constraints have to be ensured by the applications and the database system loses its single point of truth characteristic in the software system. As the applications are in charge of guaranteeing global consistency, their development requires more effort in data management. Moreover, the software system’s data management is distributed over several layers, which results in an unstructured software system architecture. To overcome the role-relational impedance mismatch and bring the database system back in its rightful position as single point of truth in a software system, this thesis introduces the novel and tripartite RSQL approach. It combines a novel database model that represents the metatype distinction as first class citizen in a database system, an adapted query language on the database model’s basis, and finally a proper result representation. Precisely, RSQL’s logical database model introduces Dynamic Data Types, to directly represent the separation of concerns within an entity type on the schema level. On the instance level, the database model defines the notion of a Dynamic Tuple that combines an entity with the notion of roles and thus, allows for dynamic structure adaptations during runtime without changing an entity’s overall type. These definitions build the main data structures on which the database system operates. Moreover, formal operators connecting the query language statements with the database model data structures, complete the database model. The query language, as external database system interface, features an individual data definition, data manipulation, and data query language. Their statements directly represent the metatype distinction to address Dynamic Data Types and Dynamic Tuples, respectively. As a consequence of the novel data structures, the query processing of Dynamic Tuples is completely redesigned. As last piece for a complete database integration of a role-based notion and its accompanied metatype distinction, we specify the RSQL Result Net as result representation. It provides a novel result structure and features functionalities to navigate through query results. Finally, we evaluate all three RSQL components in comparison to a relational database system. This assessment clearly demonstrates the benefits of the roles concept’s full database integration

Role-based Data Management

Database systems build an integral component of today’s software systems and as such they are the central point for storing and sharing a software system’s data while ensuring global data consistency at the same time. Introducing the primitives of roles and their accompanied metatype distinction in modeling and programming languages, results in a novel paradigm of designing, extending, and programming modern software systems. In detail, roles as modeling concept enable a separation of concerns within an entity. Along with its rigid core, an entity may acquire various roles in different contexts during its lifetime and thus, adapts its behavior and structure dynamically during runtime. Unfortunately, database systems, as important component and global consistency provider of such systems, do not keep pace with this trend. The absence of a metatype distinction, in terms of an entity’s separation of concerns, in the database system results in various problems for the software system in general, for the application developers, and finally for the database system itself. In case of relational database systems, these problems are concentrated under the term role-relational impedance mismatch. In particular, the whole software system is designed by using different semantics on various layers. In case of role-based software systems in combination with relational database systems this gap in semantics between applications and the database system increases dramatically. Consequently, the database system cannot directly represent the richer semantics of roles as well as the accompanied consistency constraints. These constraints have to be ensured by the applications and the database system loses its single point of truth characteristic in the software system. As the applications are in charge of guaranteeing global consistency, their development requires more effort in data management. Moreover, the software system’s data management is distributed over several layers, which results in an unstructured software system architecture. To overcome the role-relational impedance mismatch and bring the database system back in its rightful position as single point of truth in a software system, this thesis introduces the novel and tripartite RSQL approach. It combines a novel database model that represents the metatype distinction as first class citizen in a database system, an adapted query language on the database model’s basis, and finally a proper result representation. Precisely, RSQL’s logical database model introduces Dynamic Data Types, to directly represent the separation of concerns within an entity type on the schema level. On the instance level, the database model defines the notion of a Dynamic Tuple that combines an entity with the notion of roles and thus, allows for dynamic structure adaptations during runtime without changing an entity’s overall type. These definitions build the main data structures on which the database system operates. Moreover, formal operators connecting the query language statements with the database model data structures, complete the database model. The query language, as external database system interface, features an individual data definition, data manipulation, and data query language. Their statements directly represent the metatype distinction to address Dynamic Data Types and Dynamic Tuples, respectively. As a consequence of the novel data structures, the query processing of Dynamic Tuples is completely redesigned. As last piece for a complete database integration of a role-based notion and its accompanied metatype distinction, we specify the RSQL Result Net as result representation. It provides a novel result structure and features functionalities to navigate through query results. Finally, we evaluate all three RSQL components in comparison to a relational database system. This assessment clearly demonstrates the benefits of the roles concept’s full database integration