Ressourcen Optimierung von SOA-Technologien in eingebetteten Netzwerken

Embedded networks are fundamental infrastructures of many different kinds of domains, such as home or industrial automation, the automotive industry, and future smart grids. Yet they can be very heterogeneous, containing wired and wireless nodes with different kinds of resources and service capabilities, such as sensing, acting, and processing. Driven by new opportunities and business models, embedded networks will play an ever more important role in the future, interconnecting more and more devices, even from other network domains. Realizing applications for such types of networks, however, is a highly challenging task, since various aspects have to be considered, including communication between a diverse assortment of resource-constrained nodes, such as microcontrollers, as well as flexible node infrastructure. Service Oriented Architecture (SOA) with Web services would perfectly meet these unique characteristics of embedded networks and ease the development of applications. Standardized Web services, however, are based on plain-text XML, which is not suitable for microcontroller-based devices with their very limited resources due to XML's verbosity, its memory and bandwidth usage, as well as its associated significant processing overhead. This thesis presents methods and strategies for realizing efficient XML-based Web service communication in embedded networks by means of binary XML using EXI format. We present a code generation approach to create optimized and dedicated service applications in resource-constrained embedded networks. In so doing, we demonstrate how EXI grammar can be optimally constructed and applied to the Web service and service requester context. In addition, so as to realize an optimized service interaction in embedded networks, we design and develop an optimized filter-enabled service data dissemination that takes into account the individual resource capabilities of the nodes and the connection quality within embedded networks. We show different approaches for efficiently evaluating binary XML data and applying it to resource constrained devices, such as microcontrollers. Furthermore, we will present the effectful placement of binary XML filters in embedded networks with the aim of reducing both, the computational load of constrained nodes and the network traffic. Various evaluation results of V2G applications prove the efficiency of our approach as compared to existing solutions and they also prove the seamless and successful applicability of SOA-based technologies in the microcontroller-based environment

VINEA: a policy-based virtual network embedding architecture

Network virtualization has enabled new business models by allowing infrastructure providers to lease or share their physical network. To concurrently run multiple customized virtual network services, such infrastructure providers need to run a virtual network embedding protocol. The virtual network embedding is the (NP-hard) problem of matching constrained virtual networks onto the physical network. We present the design and implementation of a policy-based architecture for the virtual network embedding problem. By policy, we mean a variant aspect of any of the (invariant) embedding mechanisms: resource discovery, virtual network mapping, and allocation on the physical infrastructure. Our architecture adapts to different scenarios by instantiating appropriate policies, and has bounds on embedding efficiency and on convergence embedding time, over a single provider, or across multiple federated providers. The performance of representative novel policy configurations are compared over a prototype implementation. We also present an object model as a foundation for a protocol specification, and we release a testbed to enable users to test their own embedding policies, and to run applications within their virtual networks. The testbed uses a Linux system architecture to reserve virtual node and link capacities.National Science Foundation (CNS-0963974

Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201

Web and Semantic Web Query Languages

A number of techniques have been developed to facilitate powerful data retrieval on the Web and Semantic Web. Three categories of Web query languages can be distinguished, according to the format of the data they can retrieve: XML, RDF and Topic Maps. This article introduces the spectrum of languages falling into these categories and summarises their salient aspects. The languages are introduced using common sample data and query types. Key aspects of the query languages considered are stressed in a conclusion