Service-oriented architectures are often deployed in highly dynamic domains like Fog Computing. In such environments, centralised registries would introduce a bottleneck. We present the design of a self-organised, multi-agent-based distributed knowledge base. It supports non-monotonic reasoning, storage of semantically annotated knowledge, ontology-like queries, and fault-tolerance of partial failures of the system. Experiments with a prototype show its viability.

Multi-agent systems need to communicate to coordinate a shared task. We show that a recurrent neural network (RNN) can learn a communication protocol for coordination, even if the actions to coordinate are performed steps after the communication phase. We show that a separation of tasks with different temporal scale is necessary for successful learning. We contribute a hierarchical deep reinforcement learning model for multi-agent systems that separates the communication and coordination task from the action picking through a hierarchical policy. We further on show, that a separation of concerns in communication is beneficial but not necessary. As a testbed, we propose the Dungeon Lever Game and we extend the Differentiable Inter-Agent Learning (DIAL) framework. We present and compare results from different model variations on the Dungeon Lever Game.

Mobile Cloud Computing (MCC) requires an infrastructure that is combining the capabilities of resource-constrained but mobile and context-aware devices with that of immovable but powerful resources in the cloud. Application execution shall be boosted and battery consumption reduced. Our goal is to relieve mobile devices by enabling applications to cooperate transparently with components provided by third parties remotely, locally, or both. For this purpose, we developed SAM - the Semantic-aware Middleware - and the SAM Store. The latter resembles a registry. It allows component providers to publish semantically enriched interfaces and to offer corresponding local and remote implementations. SAM makes use of the SAM Store to match local interprocess communication (IPC) messages transparently against local and remote components. This architecture facilitates the integration of powerful, but resource-intensive remote components, which may be prioritized over local ones, and fosters various patterns of cooperation that demonstrate useful solutions in the area of MCC. By means of a realistic scenario, our evaluation proves the efficiency with respect to latency and practicality.

Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.

Detecting changes in service interfaces during the application life-cycle is essential for both change analysis and change management. Current approaches focus on structural and semantic changes without considering the actual behavior of a service by inspecting input and output values. This can lead to a selection of unsuitable services during an autonomous service replacement. Although a semantic and structural matching could be successful, the behavior of the selected service could deviate from the replaced service significantly. In this work, we present an architecture that captures and assesses additionally the behavior dimension of services to provide more reliable service replacements.

In contrast to simple autonomous vacuum cleaners, multi-purpose robots that fetch a cup of coffee and clean up rooms require cognitive skills such as learning, planning, and reasoning. Especially reasoning in dynamic and human populated environments demands for novel approaches that can handle comprehensive and fluent knowledge bases. A promising approach is Answer Set Programming (ASP), offering multi-shot solving techniques and non-monotonic stable model semantics. Our objective is to equip multi-agent systems with ASP-based reasoning capabilities, enabling a team of robots to cope with dynamic environments. Therefore, we combined ALICA - A Language for Interactive Cooperative Agents - with the ASP solver Clingo and chose topological path planning as our evaluation scenario. We utilised the Region Connection Calculus as underlying formalism of our evaluation and investigated the scalability of our implementation. The results show that our approach handles dynamic environments and scales up to appropriately large problem sizes.

In this paper, we present MiniWorld, a novel distributed network emulator. It is based on full virtualization using QEMU/KVM, offers three network backends for emulating both wired and wireless communication, and provides several mobility patterns as well as distance-based link quality models. A snapshot boot mode is offered for accelerated booting of identical environments and repeating emulation runs. To decrease runtimes, MiniWorld supports distributed emulation across multiple computers, based on a resource-aware virtual machine (VM) scheduler. Experimental results demonstrate the performance of MiniWorld with respect to VM boot times, network bandwidth, round trip times, and topology switching times.

The success of software applications that collect and process personal data does not only depend on technical aspects, but is also linked to social compatibility and user acceptance. It requires experts from different disciplines to ensure legal compliance, to foster the users' trust, to enhance the usability of the application and to finally realize the application. Multidisciplinary requirements have to be formulated, interwoven and implemented. We advocate the use of interdisciplinary design patterns that capture the design know-how of typical, recurring features in socially aware applications with particular concern for socio-technical requirements. The proposed patterns address interdisciplinary concerns in a tightly interwoven manner and are intended to facilitate the development of accepted and acceptable applications that in particular deal with sensitive user context information.

For enterprises, it is important to know how the IT infrastructure contributes to the business goals set. The COBIT IT governance framework provides a high-level view how this can be achieved. However, COBIT provides no machine-readable model that allows to refer to entities (processes, goals, actions, metrics etc.). In this paper, we present an approach to create a formal model for COBIT using an ontology. The COBIT ontology is enhanced with a formalization of metrics and a way to use selection rules and mappings to calculate metric values at runtime using data from existing systems. The calculated metric values are then inserted into the COBIT ontology and can be used for dynamic management decisions. The paper describes the modeling of the COBIT ontology and the corresponding runtime system.

Many robotic task specifications can be naturally expressed by boolean combinations of arbitrary constraints. This allows a separation of problem description and solution strategy. In this paper, we present a novel approach to solve non-linear constraint systems based on Satisfiability Modulo Theories. While most SMT-based techniques emphasize completeness, we intentionally use an incomplete local search strategy. Despite this incompleteness, the presented solution is able to deal with many real world problems like task allocation or robot positioning. We show that our approach is able to exploit the logical structure to solve highly complex tasks almost in real-time.

SUMMARY Although the idea of context‐awareness was introduced almost two decades ago, few mobile software applications are available today that can sense and adapt to their run‐time environment. The development of context‐aware and self‐adaptive applications is complex and few developers have experience in this area. On the basis of several demonstrators built by the joint European research project MUSIC, this paper describes typical context and adaptation features relevant for the development of context‐aware and self‐adaptive mobile applications. We explain how the demonstrators were realised using the open‐source platform MUSIC and present the feedback of the developers of these demonstrators. The main contribution of this paper is to show how the development complexity of context‐aware and self‐adaptive mobile applications can be mastered by using an adaptation framework such as MUSIC. Copyright © 2012 John Wiley & Sons, Ltd.

Incomplete or imprecise models of control systems make it difficult to find an appropriate structure and parameter set for a corresponding control policy. These problems are addressed by reinforcement learning algorithms like policy gradient methods. We describe how to stabilise the policy gradient descent by introducing a regularisation term to enhance the episodic natural actor-critic approach. This allows a more policy independent usage. We used the resulting algorithm to optimise a z-transformed rational function representing the control policy. This representation facilitates simultaneous optimisation of the control structure and its parameters in time space and can be analysed in terms of control theory to predict the control behaviour for arbitrary scenarios. Furthermore we present a solution to the general problem of finding a initial parameter set with the help of a single demonstrated trajectory. The approach is evaluated on a cartpole simulation for demonstrating the expressiveness of the policy. Furthermore, a real soccer robot scenario demonstrates the ability of the proposed approach to deal with real world scenarios.

We describe the motivation, focus, and organization of SESENA11, the 2nd International Workshop on Software Engineering for Sensor Network Applications. The workshop took place under the umbrella of ICSE 2011, the 33rd ACM/IEEE International Conference on Software Engineering, in Honolulu, Hawaii, on May 22, 2011. The aim was to attract researchers belonging to the Software Engineering (SE) and Wireless Sensor Network (WSN) communities, not only to exchange their recent research results on the topic, but also to stimulate discussion on the core open problems and define a shared research agenda. More information can be found at the workshop website: http://www.sesena.info.

The primary purpose of a wireless sensor network (WSN) is to collect and disseminate sensory data and possibly perform some calculations. However, there are no convenient frameworks in place to allow instant access to this sensed information in a programming environment. Using a model-driven approach, we present a development tool to support applications development for data-centric sensor network. In this study, a domain-specific language (DSL) and corresponding meta-models are designed and implemented to specify all aspects of a sensor node application, especially for data processing tasks such as sampling, aggregation and forwarding. The language comes with tools supporting automatic model transformations to generate application code.

This editorial preface describes the aims and motivation as well as some details of the reviewing process of SESENA 2010, the First International Workshop on Software Engineering for Sensor Network Applications, which took place under the umbrella of ICSE 2010, the 32rd ACM/IEEE International Conference on Software Engineering, in Cape Town, South Africa, May 2010. See also our workshop's website at http://www.sesena.info/

Genetic programming (GP) is known to provide good solutions for many problems like the evolution of network protocols and distributed algorithms. In most cases it is a hardwired module of a design framework assisting the engineer in optimizing specific aspects in system development. In this article, we show how the utility of GP can be increased remarkably by isolating it as a component and integrating it into the model-driven software development process. Our GP framework produces XMI-encoded UML models that can easily be loaded into widely available modeling tools, which in turn offer code generation as well as additional analysis and test capabilities. We use the evolution of a distributed election algorithm as an example to illustrate how GP can be combined with model-driven development (MDD).

Abstract Driven by the emergence of mobile and pervasive computing there is a growing demand for context‐aware software systems that can dynamically adapt to their run‐time environment. We present the results of project MADAM that has delivered a comprehensive solution for the development and operation of context‐aware, self‐adaptive applications. The main contributions of MADAM are (a) a sophisticated middleware that supports the dynamic adaptation of component‐based applications, and (b) an innovative model‐driven development methodology that is based on abstract adaptation models and corresponding model‐to‐code transformations. MADAM has demonstrated the viability of a general, integrated approach to application‐level adaptation. We discuss our experiences with two real‐world case studies that were built using the MADAM approach. Copyright © 2008 John Wiley & Sons, Ltd.

The fitness landscape of a problem is the relation between the solution candidates and their reproduction probability. In order to understand optimization problems, it is essential to also understand the features of fitness landscapes and their interaction. In this paper we introduce a model problem that allows us to investigate many characteristics of fitness landscapes. Specifically noise, affinity for overfitting, neutrality, epistasis, multi-objectivity, and ruggedness can be independently added, removed, and fine-tuned. With this model, we contribute a useful tool for assessing optimization algorithms and parameter settings.

Semantic web service composition is about finding services from a repository that are able to accomplish a specified task if executed. The task is defined in a form of a composition request which contains a set of available input parameters and a set of wanted output parameters. Instead of the parameter values, concepts from an ontology describing their semantics are passed to the composition engine. The parameters of the services in the repository the composer works on are semantically annotated in the same way as the parameters in the request. The composer then finds a sequence of services, called a composition. If the input parameters given in the request are provided, the services of this sequence can subsequently be executed and will finally produce the wanted output parameters. In this paper, three different approaches to semantic web service composition are formally defined and compared with each other: an uninformed search in form of an IDDFS algorithm, a greedy informed search based on heuristic functions, and a multi- objective genetic algorithm.

This paper identifies requirements for querying and accessing context information in mobile and pervasive computing environments. Furthermore it studies existing query languages showing that they satisfy only a subset of these requirements or cover some of them only to a limited extent. A new context query language is presented to overcome these shortcomings, improving the state of the art in several respects: heterogeneous representations of context information, definition of complex filtering mechanisms, elaborate aggregation functions and ontology integration, all in one language.

Model transformations are a key element of model-driven software development. This paper presents two main innovations: A general methodology to automate the model transformation in heterogeneous environments, and an ontological framework that captures system dependencies and supports reasoning about platform properties and capabilities. Our approach eases the development of software for heterogeneous environments. It has been tested for a realistic application scenario.

Genetic programming is known to provide good solutions for many problems like the evolution of network protocols and distributed algorithms. Then, it is most likely a hardwired module of a design framework where it assists the engineer in optimizing specific aspects in system development. In this paper we show how the utility of genetic programming can be increased remarkably by isolating it as a component and integrating it into the model-driven software development process. Our genetic programming framework produces XMI-encoded UML models that can easily be loaded into widely available modeling tools, which in turn offer code generation as well as additional analysis and test capabilities. We use the evolution of a distributed election algorithm as an example to illustrate how genetic programming can be combined with model-driven development.

Enterprises apply SOAs to implement business processes as services which are adaptive to software changes and updates. Service management has to ensure high availability, performance and fault tolerance and is therefore crucial for the undisturbed functionality of a SOA. However, manual service management is cumbersome with a large amount of services and applications. Services that fail or do not achieve a certain quality of service (QoS) need to be manually replaced. Up to now, a fully automatic approach is missing. We introduce a semantic model and architecture for automatic service brokering in service-oriented architectures (SOA). A Service Broker is used for semantic service discovery with respect to functional criteria and QoS. Hence, we use a semantic matching algorithm on an extension of the OWL-S ontology. Services are requested by service containers which monitor and replace services in interaction with the service broker. The architecture is presented with an implementation using Web Services.

Service level management (SLM) has gained more and more importance in the past few years. One of the biggest challenges is the integration of emerging new technologies such as Web services. A large number of different SLM approaches has been proposed which complicates an efficient SLM. This paper describes an SLM approach that is based on the model driven architecture (MDA). The first step is to specify abstract reusable SLA patterns which are bound later to a concrete management platform and are finally physically deployed into the managed environment. This approach benefits from the advantages of the MDA and provides a mechanism for transforming SLA patterns for different SLA management platforms. Our approach has been prototypically implemented for the Web services level agreement (WSLA) environment.

Web services are the key technology for implementing distributed enterprise level applications such as B2B and grid computing. An important goal is to provide dependable quality guarantees for client-server interactions. Therefore, service level management (SLM) is gaining more and more significance for clients and providers of Web services. The first step to control service level agreements is a proper instrumentation of the application code in order to monitor the service performance. However, manual instrumentation of Web services is very costly and error-prone and thus not very efficient. Our goal was to develop a systematic and automated, tool-supported approach for Web services instrumentation. We present a dual approach for efficiently instrumenting Web services. It consists of instrumenting the frontend Web services platform as well as the backend services. Although the instrumentation of the Web services platform necessarily is platform-specific, we have found a general, reusable approach. On the backend-side aspect-oriented programming techniques are successfully applied to instrument backend services. We present experimental studies of performance instrumentation using the application response measurement (ARM) API and evaluate the efficiency of the monitoring enhancements. Our results point the way to systematically gain better insights into the behaviour of Web services and thus how to build more dependable Web-based applications.

The concern for non-functional properties of software components and distributed applications has increased significantly in recent years. Non-functional properties are often subsumed under the term Quality of Service (QoS). It refers to quality aspects of a software component or service such as real-time response guarantees, availability and fault-tolerance, the degree of data consistency, the precision of some computation, or the level of security. Consequently, the specification and implementation of QoS mechanisms has become an important concern in the engineering of distributed applications. In this tutorial the attendees will learn how non-functional requirements can be engineered in a systematic way into applications on top of distribution platforms such as CORBA and .NET The tutorial focuses on two major subjects areas: (1) Specification of QoS properties and (2) implementation of QoS mechanisms in middleware. We present a comprehensive, model-driven approach. It starts with a platform-independent model (PIM) in UML that captures the application QoS requirements. This model is mapped by a tool to a platform-specific model (PSM) tailored for a specific middleware, which is extended with the corresponding QoS mechanisms. Finally, the PSM is translated to code. Participants in this tutorial will get a thorough understanding of general QoS requirements, QoS modeling alternatives and QoS mechanism integration in respect to popular distributed object middleware. Furthermore, we will discuss the pros and cons of CORBA and .NET for QoS engineering. A tool will be demonstrated that eases substantially the modeling stages and the code generation.

In mobile computing environments the availability of resources may vary significantly and unpredictably at application runtime, and thus may not satisfy a negotiated QoS level. We assume that in the presence of QoS fluctuations applications adapt their behavior to the prevailing operating conditions. We present five new adaptation strategies for application adaptation and study their performance by simulation experiments. The experiments show that one strategy performs best in most configurations in terms of result quality and computational efficiency. This strategy takes into account the ratio of utility value over resource demand as well as the system state.

The management of modern computer networks and distributed systems comprises big challenges due to the complexity of nowadays network environments. It requires a decentralized approach in order to be efficient, effective, scalable, and flexible. Moreover, it has to be proactive since identifying and preventing problems before they affect users becomes increasingly important. Several research projects have identified mobile agents as a possible solution for decentralized management, while others have used neural networks to make predictions and achieve proactiveness. We propose a management system which integrates both technologies to achieve proactiveness in a decentralized fashion. The result is a distributed management system that employs intelligent mobile components. This paper discusses our approach and presents the design and implementation of a prototype application that puts the proposed ideas to practice.

Quality of service (QoS) management is a popular demand on distribution infrastructures. We present MAQS, a generic framework for QoS management based on standard CORBA middleware. The framework facilitates the specification and generation of QoS-enabled client/server applications. Architectural support for re-use and maintenance of implementations of QoS mechanisms is one of our main objectives. Our approach is based on the aspect-oriented programming paradigm. We discuss the design of the framework and how AOP facilitates the re-use and maintenance of QoS components.

Quality of service (QoS) management is an increasing demand on distribution infrastructures. While most of the existing QoS management architectures support a fixed set of QoS only, larger distributed systems encounter a variety of QoS requirements. This leads to a mix of different platforms and increased interoperability and management efforts. Generic QoS management could help to reduce this effort and provide flexibility towards new application requirements. We have developed a generic QoS management architecture based on CORBA. We present the motivations and requirements for the architecture, and we discuss the necessary extensions to the CORBA.

The mobile agent paradigm can be employed effectively for the decentralized management of complex networks. Nevertheless, legacy management protocols such as SNMP need to be supported for reasons of migration and efficiency. We show how the integration of the two paradigms leads to a flexibly adjustable decentralized management architecture. NetDoctor is a network management application framework that allows the monitoring of hosts in a heterogeneous network. Mobile agents may query local or remote SNMP agents, process the status data, and perform certain corrective actions. The system supports run-time adjustment and reconfiguration. A quantitative analysis underlines the benefits in respect to the network load reduction.

In object-oriented distributed processing systems, all interactions between objects occur solely through their defined external interfaces. The authors argue that object reference parameters should be supported in such systems for reasons of programming style and productivity. It is not sufficient to pass the name of an object as a string. The system must be aware of reference parameters and provide means to control and protect the delegation of access. The authors' emphasis is on motivating the need for protected object references and on showing that their efficient implementation is feasible in diverse environments. The design is guided by the principle of minimal trust. Two prototype implementations of object reference support systems are presented. One is an example in which, right from the start, object references are integrated into the design of a kernel for a network operating system for heterogeneous distributed environments. The other prototype shows how object references can be added to a popular remote procedure call package in an upwardly compatible way.>

The integration of accounting functions and an account server into the distributed academic computing network operating system (DACNOS), which is an NOS built on top of a heterogeneous collection of networked computers, is described. The accounting is supported by NOS-kernel mechanisms that can be tailored to the needs of the heterogeneous servers. Accounting data is collected and stored by an account server in the NOS that manages the balances and the resource consumption data of clients. Depending on privileges, accounting data is accessible to clients, servers, and an account server administrator who may use this information for various resource and request management purposes.>