Raphael Kunis

A component based software architecture for e-government applications

The raising need for e-government applications leads to many new approaches in this sector. To fulfill the requirement for a flexible government-to-government (G2G) software system being adaptable for the usage in many sectors of e-government applications we introduce the reference architecture for e-government (RAfEG) in this paper. The key features of the system are flexibility, security, adaptability and interoperability between authorities. The efficient usage of heterogeneous systems and heterogeneous hardware platforms, respectively, allows the execution of large interactive applications in e-government. Because security is a critical issue in e-government applications our solution uses different types of authentication and authorization methods and also supports secure communication between the interoperating heterogeneous systems. Due to the fact that the electronically supported execution of government procedures is the main aspect of the RAfEG system, an approach where these procedures are modeled as workflows and executed by an underlying workflow management system (WfMS) is the solution we present in this paper. Although many e-government applications exist at present, the RAfEG system is a new approach because it is able to cope with a wide range of internal official procedures and also highly adaptable to new procedures within e-government.

A scheduling toolkit for multiprocessor-task programming with dependencies

The performance of many scientific applications for distributed memory platforms can be increased by utilizing multiprocessortask programming. To obtain the minimum parallel runtime an appropriate schedule that takes the computation and communication performance of the target platform into account is required. However, many tools and environments for multiprocessor-task programming lack the support for an integrated scheduler. This paper presents a scheduling toolkit, which provides this support and integrates popular scheduling algorithms. The implemented scheduling algorithms provide an infrastructure to automatically determine a schedule for multiprocessor-tasks with dependencies represented by a task graph.

SEParAT: scheduling support environment for parallel application task graphs

Programs using parallel tasks can be represented by task graphs so that scheduling algorithms can be used to find an efficient execution order of the parallel tasks. This article proposes a flexible, component-based and extensible scheduling framework called SEParAT that supports the scheduling of a parallel program in multiple ways. The article describes the functionality and the software architecture of SEParAT. The flexible interfaces enable the cooperation with other programming tools, e.g., tools exploiting a specification of the parallel task structure of an application. The core component of SEParAT is an extensible scheduling algorithm library that provides an infrastructure to determine efficient schedules for task graphs. Homogeneous as well as heterogeneous platforms can be handled. The article also includes detailed experimental results comprising the evaluation of SEParAT as well as the evaluation of a variety of scheduling algorithms.

Optimization of Layer-based Scheduling Algorithms for Mixed Parallel Applications with Precedence Constraints Using Move-blocks

The efficient scheduling of large mixed parallel applications is challenging. Most existing algorithms utilize scheduling heuristics and approximation algorithms to determine a good schedule as basis for an efficient execution in large scale scientific computing. This paper concentrates on the scheduling of mixed parallel applications represented by task graphs with parallel tasks and precedence constraints between them. Layer-based scheduling algorithms for homogeneous target platforms are improved by adding a move-blocks phase that further reduces the resulting parallel runtime.The layer-based scheduling approach is described and the move-blocks algorithm is introduced in detail.The move-blocks extension provides better scheduling results for small as well as for large problems but has only a small increase in runtime.This is shown by a comparison of the modified and the original algorithms over a wide range of test cases.

Modeling of energy-sensitive manufacturing processes

Energy-saving manufacturing of products is an important feature for the success of todays producing enterprises. Beside the marketing point of view, energy-efficiency plays a key role due to the fact that the costs for purchasing materials and energy increases. The basis of economic manufacturing are manufacturing processes taking energy- and resource-efficiency into account. Influence factors are not restricted to process planning and the results of planning processes, but also consider the whole product life cycle and its impact on the manufacturing of products. In this article, a specification model for energy-sensitive manufacturing processes is introduced and a data model focusing on the manufacturing of powertrain components is presented. Furthermore, a component-based software reference architecture for the integrated consideration of the energy and resource consumption is proposed.

Optimizing layer-based scheduling algorithms for parallel tasks with dependencies

Programming with parallel tasks leads to task graphs with dependencies representing a parallel program. Scheduling algorithms are employed to find an efficient execution order of the parallel tasks. A large variety of scheduling algorithms exist, including layer‐based scheduling algorithms for homogeneous target platforms that build consecutive layers of independent parallel tasks and schedule each layer separately. Although these scheduling algorithms provide good results in terms of scheduling algorithm runtime and schedule execution time, the resulting schedules leave room for optimization. This article proposes an optimization for arbitrary layer‐based scheduling algorithms, which is called Move‐blocks algorithm. Given a layer‐based schedule of the parallel tasks, this algorithm moves blocks of parallel tasks into preceding layers in order to reduce the overall execution time of a task‐based application. Suitable blocks of parallel tasks are identified by the algorithm Find‐blocks, which is employed together with the Move‐blocks algorithm. The algorithm Move‐blocks is applied to four well‐known scheduling algorithms. A detailed evaluation for a wide range of test cases is given. Copyright

Task-block identification and movement for layer-based scheduling algorithms

The programming with parallel tasks leads to task graphs with dependencies representing a parallel program. Scheduling algorithms are employed to find an efficient execution order of the parallel tasks. A large variety of scheduling algorithms exists, including layer-based scheduling algorithms for homogeneous target platforms that build consecutive layers of independent parallel tasks and schedule each layer separately. The resulting schedules leave room for optimization. This article presents an optimization for arbitrary layer-based scheduling algorithms by adding a movement phase which shifts blocks of tasks to previous layer-schedules. Especially, a block identification algorithm is proposed, which identifies suitable blocks of tasks in arbitrary layer-schedules and, thus, allows the application of the movement of blocks to a wide range of layer-based scheduling algorithms. The block identification and the movement algorithm are applied to two scheduling algorithms and show good performance improvements.