Web Service Composition Systems for the Web Service Challenge - A Detailed Review

This report gives a detailed discussion on the system, algorithms, and techniques that we have applied in order to solve the Web Service Challenges (WSC) of the years 2006 and 2007. These international contests are focused on semantic web service composition. In each challenge of the contests, a repository of web services is given. The input and output parameters of the services in the repository are annotated with semantic concepts. A query to a semantic composition engine contains a set of available input concepts and a set of wanted output concepts. In order to employ an offered service for a requested role, the concepts of the input parameters of the offered operations must be more general than requested (contravariance). In contrast, the concepts of the output parameters of the offered service must be more specific than requested (covariance). The engine should respond to a query by providing a valid composition as fast as possible. We discuss three different methods for web service composition: an uninformed search in form of an IDDFS algorithm, a greedy informed search based on heuristic functions, and a multi-objective genetic algorithm.

Context as a Service

In the vision of Mark Weiser on ubiquitous computing, computers are disappearing from the focus of the users and are seamlessly interacting with other computers and users in order to provide information and services. This shift of computers away from direct computer interaction requires another way of applications to interact without bothering the user. Context is the information which can be used to characterize the situation of persons, locations, or other objects relevant for the applications. Context-aware applications are capable of monitoring and exploiting knowledge about external operating conditions. These applications can adapt their behaviour based on the retrieved information and thus to replace (at least a certain amount) the missing user interactions. Context awareness can be assumed to be an important ingredient for applications in ubiquitous computing environments. However, context management in ubiquitous computing environments must reflect the specific characteristics of these environments, for example distribution, mobility, resource-constrained devices, and heterogeneity of context sources. Modern mobile devices are equipped with fast processors, sufficient memory, and with several sensors, like Global Positioning System (GPS) sensor, light sensor, or accelerometer. Since many applications in ubiquitous computing environments can exploit context information for enhancing their service to the user, these devices are highly useful for context-aware applications in ubiquitous computing environments. Additionally, context reasoners and external context providers can be incorporated. It is possible that several context sensors, reasoners and context providers offer the same type of information. However, the information providers can differ in quality levels (e.g. accuracy), representations (e.g. position represented in coordinates and as an address) of the offered information, and costs (like battery consumption) for providing the information. In order to simplify the development of context-aware applications, the developers should be able to transparently access context information without bothering with underlying context accessing techniques and distribution aspects. They should rather be able to express which kind of information they require, which quality criteria this information should fulfil, and how much the provision of this information should cost (not only monetary cost but also energy or performance usage). For this purpose, application developers as well as developers of context providers need a common language and vocabulary to specify which information they require respectively they provide. These descriptions respectively criteria have to be matched. For a matching of these descriptions, it is likely that a transformation of the provided information is needed to fulfil the criteria of the context-aware application. As it is possible that more than one provider fulfils the criteria, a selection process is required. In this process the system has to trade off the provided quality of context and required costs of the context provider against the quality of context requested by the context consumer. This selection allows to turn on context sources only if required. Explicitly selecting context services and thereby dynamically activating and deactivating the local context provider has the advantage that also the resource consumption is reduced as especially unused context sensors are deactivated. One promising solution is a middleware providing appropriate support in consideration of the principles of service-oriented computing like loose coupling, abstraction, reusability, or discoverability of context providers. This allows us to abstract context sensors, context reasoners and also external context providers as context services. In this thesis we present our solution consisting of a context model and ontology, a context offer and query language, a comprehensive matching and mediation process and a selection service. Especially the matching and mediation process and the selection service differ from the existing works. The matching and mediation process allows an autonomous establishment of mediation processes in order to transfer information from an offered representation into a requested representation. In difference to other approaches, the selection service selects not only a service for a service request, it rather selects a set of services in order to fulfil all requests which also facilitates the sharing of services. The approach is extensively reviewed regarding the different requirements and a set of demonstrators shows its usability in real-world scenarios.

Managing Quality Properties of Web Service Compositions

Web services from different partners can be combined to applications that realize a more complex business goal. Such applications built as Web service compositions define how interactions between Web services take place in order to implement the business logic. Web service compositions not only have to provide the desired functionality but also have to comply with certain Quality of Service (QoS) levels. Maximizing the users' satisfaction, also reflected as Quality of Experience (QoE), is a primary goal to be achieved in a Service-Oriented Architecture (SOA). Unfortunately, in a dynamic environment like SOA unforeseen situations might appear like services not being available or not responding in the desired time frame. In such situations, appropriate actions need to be triggered in order to avoid the violation of QoS and QoE constraints. In this thesis, proper solutions are developed to manage Web services and Web service compositions with regard to QoS and QoE requirements. The Business Process Rules Language (BPRules) was developed to manage Web service compositions when undesired QoS or QoE values are detected. BPRules provides a rich set of management actions that may be triggered for controlling the service composition and for improving its quality behavior. Regarding the quality properties, BPRules allows to distinguish between the QoS values as they are promised by the service providers, QoE values that were assigned by end-users, the monitored QoS as measured by our BPR framework, and the predicted QoS and QoE values. BPRules facilitates the specification of certain user groups characterized by different context properties and allows triggering a personalized, context-aware service selection tailored for the specified user groups. In a service market where a multitude of services with the same functionality and different quality values are available, the right services need to be selected for realizing the service composition. We developed new and efficient heuristic algorithms that are applied to choose high quality services for the composition. BPRules offers the possibility to integrate multiple service selection algorithms. The selection algorithms are applicable also for non-linear objective functions and constraints. The BPR framework includes new approaches for context-aware service selection and quality property predictions. We consider the location information of users and services as context dimension for the prediction of response time and throughput. The BPR framework combines all new features and contributions to a comprehensive management solution. Furthermore, it facilitates flexible monitoring of QoS properties without having to modify the description of the service composition. We show how the different modules of the BPR framework work together in order to execute the management rules. We evaluate how our selection algorithms outperform a genetic algorithm from related research. The evaluation reveals how context data can be used for a personalized prediction of response time and throughput.

Integrated soil fertility management in eastern and western Africa: The role of knowledge and innovation systems, its adoption and impact

The rise in population growth, as well as nutrient mining, has contributed to low agricultural productivity in Sub-Saharan Africa (SSA). A plethora of technologies to boost agricultural production have been developed but the dissemination of these agricultural innovations and subsequent uptake by smallholder farmers has remained a challenge. Scientists and philanthropists have adopted the Integrated Soil Fertility Management (ISFM) paradigm as a means to promote sustainable intensification of African farming systems. This comparative study aimed: 1) To assess the efficacy of Agricultural Knowledge and Innovation Systems (AKIS) in East (Kenya) and West (Ghana) Africa in the communication and dissemination of ISFM (Study I); 2) To investigate how specifically soil quality, and more broadly socio-economic status and institutional factors, influence farmer adoption of ISFM (Study II); and 3) To assess the effect of ISFM on maize yield and total household income of smallholder farmers (Study III). To address these aims, a mixed methodology approach was employed for study I. AKIS actors were subjected to social network analysis methods and in-depth interviews. Structured questionnaires were administered to 285 farming households in Tamale and 300 households in Kakamega selected using a stratified random sampling approach. There was a positive relationship between complete ISFM awareness among farmers and weak knowledge ties to both formal and informal actors at both research locations. The Kakamega AKIS revealed a relationship between complete ISFM awareness among farmers and them having strong knowledge ties to formal actors implying that further integration of formal actors with farmers’ local knowledge is crucial for the agricultural development progress. The structured questionnaire was also utilized to answer the query pertaining to study II. Soil samples (0-20 cm depth) were drawn from 322 (Tamale, Ghana) and 459 (Kakamega, Kenya) maize plots and analysed non-destructively for various soil fertility indicators. Ordinal regression modeling was applied to assess the cumulative adoption of ISFM. According to model estimates, soil carbon seemed to preclude farmers from intensifying input use in Tamale, whereas in Kakamega it spurred complete adoption. This varied response by farmers to soil quality conditions is multifaceted. From the Tamale perspective, it is consistent with farmers’ tendency to judiciously allocate scarce resources. Viewed from the Kakamega perspective, it points to a need for farmers here to intensify agricultural production in order to foster food security. In Kakamega, farmers with more acidic soils were more likely to adopt ISFM. Other household and farm-level factors necessary for ISFM adoption included off-farm income, livestock ownership, farmer associations, and market inter-linkages. Finally, in study III a counterfactual model was used to calculate the difference in outcomes (yield and household income) of the treatment (ISFM adoption) in order to estimate causal effects of ISFM adoption. Adoption of ISFM contributed to a yield increase of 16% in both Tamale and Kakamega. The innovation affected total household income only in Tamale, where ISFM adopters had an income gain of 20%. This may be attributable to the different policy contexts under which the two sets of farmers operate. The main recommendations underscored the need to: (1) improve the functioning of AKIS, (2) enhance farmer access to hybrid maize seed and credit, (3) and conduct additional multi-locational studies as farmers operate under varying contexts.