Sebastian Richly

JouleUnit: a generic framework for software energy profiling and testing

Energy consumption has become an important characteristic of nowadays information and communication technology (ICT) applications, especially for mobile devices, whose uptime is limited by the available battery capacity. Hence, ICT applications are optimized to provide the best possible user satisfaction for the least possible energy budget. An inevitable prerequisite for such optimizations is the ability to analyze softwares energy consumption. In consequence, many energy profiling frameworks have been developed. The problem we address in this paper is that profiling frameworks are device- and application-specific and, hence, cannot be reused. We analyze the key requirements of energy profiling frameworks and propose a generic framework reusable for different devices and applications, designed according to these requirements. We evaluate the presented framework using two case studies showing the reusability in two significantly different scenarios.

Comparing mobile applications' energy consumption

As mobile devices are nowadays used regularly and everywhere, their energy consumption has become a central concern. However, todays mobile applications often do not consider energy requirements and users lack information on their energy consumption before they install and try them. In this paper, we compare mobile applications from two domains and show that they reveal different energy consumption while providing similar services. We define microbenchmarks for emailing and web browsing and evaluate apps from these domains. We show that non-functional features such as web page caching can but not have to have a positive influence on an applications energy consumption.

Using Cloud Technologies to Optimize Data-Intensive Service Applications

The role of data analytics increases in several application domains to cope with the large amount of captured data. Generally, data analytics are data-intensive processes, whose efficient execution is a challenging task. Each process consists of a collection of related structured activities, where huge data sets have to be exchanged between several loosely coupled services. The implementation of such processes in a service-oriented environment offers some advantages, but the efficient realization of data flows is difficult. Therefore, we use this paper to propose a novel SOA-aware approach with a special focus on the data flow. The tight interaction of new cloud technologies with SOA technologies enables us to optimize the execution of data-intensive service applications by reducing the data exchange tasks to a minimum. Fundamentally, our core concept to optimize the data flows is found in data clouds. Moreover, we can exploit our approach to derive efficient process execution strategies regarding different optimization objectives for the data flows.

Open Service Process Platform 2.0

Service-oriented architectures (SOA) have revolutionized software-engineering over the last years. As a result, many domains have begun to switch to this architecture style. However, to efficiently support different domains from an SOA perspective, several extensions have to be included, e.g., concepts for efficient data transfer or runtime adaptation of processes. On the one hand, our Open Service Process Platform 2.0 is a central SOA infrastructure including several extensions. On the other hand, this platform can be used as the basis for the development of further extensions. The unique features of our platform are: (i) orchestration and execution of processes in an easy way (ii) arbitrary extensibility with regard to simple specialization for various domains, (iii) central infrastructure within an organization, and (iv) full accessibility through Web 2.0 technologies.

A BDI-Based Reflective Infrastructure for Dynamic Workflows

Business processes (workflows) standardize frequently recurring courses of events and actions in organizations. If these business processes are optimized, the resulting improvements in efficiency and quality are multiplied throughout the respective organization as the experience of individuals is shared among all employees. It is also true that all employees of a given organization have to follow the respective process instructions unless it appears necessary to deviate from the prescribed actions in order to react to unexpected events, failures, or other exceptions the process has not been designed for. In this paper, we present our approach for reflective and dynamic workflows that are based on the BDI (belief desire intention) agent technology. Our primary goal is to introduce a new way of adaptation using sub-workflows instead of atomic changes. The second challenge we meet is the need for workflows to find and apply modifications on their own; this should also be learned at runtime.

BPELDT — Data-Aware Extension for Data-Intensive Service Applications

Aside from business processes, the service-oriented approach —currently realized with Web services and BPEL—should be utilizable for data-intensive applications as well. Fundamentally, data-intensive applications are characterized by (i) a sequence of functional operations processing large amounts of data and (ii) the delivery and transformation of huge data sets between those functional activities. However, for the efficient handling of massive data sets, a significant amount of data infrastructure is required and the predefined ‘by value’ data semantic within the invocation of Web services and BPEL is not well suited for this context. To tackle this problem on the BPEL level, we developed a seamless extension to BPEL—the ‘BPEL data transitions’.

Data-aware SOA for Gene Expression Analysis Processes

In the context of genome research, the method of gene expression analysis has been used for several years. Related microarray experiments are conducted all over the world, and consequently, a vast amount of microarray data sets are produced. Having access to this variety of repositories, researchers would like to incorporate this data in their analyses processes to increase the statistical significance of their results. Such analyses processes are typical examples of data-intensive processes. In general, data-intensive processes are characterized by (i) a sequence of functional operations processing large amount of data and (ii) the transportation and transformation of huge data sets between the functional operations. To support data-intensive processes, an efficient and scalable environment is required, since the performance is a key factor today. The service-oriented architecture (SOA) is beneficial in this area according to process orchestration and execution. However, the current realization of SOA with Web services and BPEL includes some drawbacks with regard to the performance of the data propagation between Web services. Therefore, we present in this paper our data-aware service-oriented approach to efficiently support such data-intensive processes.

A semantic-BDI-based approach to realize cooperative, reflexive workflows

In the last years, autonomous and adaptive processes have became more and more important. Even business processes are more complex today. The more complex a system becomes, the more difficult it is to handle changed requirements. This increases the need for adaptation abilities of workflows. In these new workflow systems, autonomy would have great impact regarding the possible usability of such workflows. They can decide on their own how to handle a certain situation, for example, in case of a Web service timeout, new business rules, or new knowledge about the domain. Another aspect in current workflow engines is the inefficient way of executing process instances. Today, process instances perform actions separated from each other. This leads to much redundant work if two process instances work on the same workflow model at the same time. Some of the tasks will be executed twice, but the result in every process instance is the same.Without knowing what all the other instances do, the engines waste time and resources. Our primary goal is to provide an approach for autonomous adaptations in workflow engines. We solved that through a combination of the Belief-Desire-Intention technique and semantics. We also provide processes with the ability to know all other engines and processes running and to communicate with other engines as well as with all processes via semantic knowledge.

Supporting Gene Expression Analysis Processes by a Service-Oriented Platform

In the context of genome research, the method of gene expression analysis has been used for several years. Related microarray experiments are conducted all over the world, and consequently, a vast amount of microarray data sets are produced. Having access to this variety of repositories, researchers would like to incorporate this data in their analyses to increase the statistical significance of their results. In this paper, we present our service-oriented approach for the gene expression analysis. Our approach is oriented towards scalability and efficiency.

FRaMED: full-fledge role modeling editor (tool demo)

Since the year 1977, role modeling has been continuously investigated as promising paradigm to model complex, dynamic systems. However, this research had almost no influence on the design of todays increasingly complex and context-sensitive software systems. The reason for that is twofold. First, most modeling languages focused either on the behavioral, relational or context-dependent nature of roles rather than combining them. Second, there is a lack of tool support for the design, validation, and generation of role-based software systems. In particular, there exists no graphical role modeling editor supporting the three natures as well as the various proposed constraints. To overcome this deficiency, we introduce the Full-fledged Role Modeling Editor (FRaMED), a graphical modeling editor embracing all natures of roles and modeling constraints featuring generators for a formal representation and source code of a role-based programming language. To show its applicability for the development of role-based software systems, an example from the banking domain is employed.