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Climate change has put significant pressure on energy markets. Political decisions such as the plan of the German government to shut down coal power plants by 2038 are shifting electricity production towards renewable and distributed energy resources. The share of these resources will continue to grow significantly in the coming years. This trend changes the ways how energy markets work which mandates fundamental changes in the underlying IT infrastructure. In this paper, we propose a blockchain-based solution which enables an economically viable and grid-serving integration of distributed energy resources into the existing energy system. Our blockchain-based approach targets intraday and day-ahead operating reserve markets, on which energy grid operators and operators of distributed energy resources can trade flexibilities within the schedulable energy production and consumption of their resources. By utilizing these flexibilities as an operating reserve, renewable and climate-friendly technologies can contribute to maintaining the grid stability and security of supply while simultaneously creating economically interesting business models for their operators. We propose to define blockchain-based short-term energy markets by utilizing the concept of general-purpose smart contracts and cryptocurrencies. This enables direct and decentralized trading of energy flexibilities without any intermediary or central instance. We demonstrate the feasibility of our approach through an implementation of a prototype of the proposed markets based on the Ethereum blockchain and provide a detailed evaluation of its efficiency and scalability. [ABSTRACT FROM AUTHOR]

Identification is an essential building block for many services in distributed information systems. The quality and purpose of identification may differ, but the basic underlying problem is always to bind a set of attributes to an identifier in a unique and deterministic way. Name/directory services, such as DNS, X.500, or UDDI, are a well-established concept to address this problem in distributed information systems. However, none of these services addresses the specific requirements of peer-to-peer systems with respect to dynamism, decentralization, and maintenance. We propose the implementation of directories using a structured peer-to-peer overlay network and apply this approach to support self-contained maintenance of routing tables with dynamic IP addresses in structured P2P systems. Thus, we can keep routing tables intact without affecting the organization of the overlay networks, making it logically independent of the underlying network infrastructure. Even though the directory is self-referential, since it uses its own service to maintain itself, we show that it is robust due to a self-healing capability. For security, we apply a combination of PGP-like public key distribution and a quorum-based query scheme. We describe the algorithm as implemented in the P-Grid P2P lookup system (http://www.p-grid.org/) and give a detailed analysis and simulation results demonstrating the efficiency and robustness of our approach. Index Terms--Peer-to-peer systems, identity handling, self-maintaining, decentralized directory service, distributed hash tables, dynamic resilience.

Byline: Le-Hung Vu, Manfred Hauswirth, Fabio Porto, Karl Aberer Directory services are a genuine constituent of any distributed architecture which facilitate binding attributes to names and then querying this information, that is, announcing and discovering resources. In such contexts, especially in a business environment, Quality of Service (QoS) and non-functional properties are usually the most important criteria to decide whether a specific resource will be used. To address this problem, we present an approach to the semantic description and discovery of web services which specifically takes into account their QoS properties. Our solution uses a robust trust and reputation model to provide an accurate picture of the actual QoS to user. The search engine is based on an algebraic discovery model and uses adaptive query-processing techniques to parallelise expensive operators. Architecturally, the engine can be run as a centralised service for small-scale environments or can be distributed among any number of cooperating registry providers.

Byline: Karl Aberer, Anwitaman Datta, Manfred Hauswirth The success story of eBay has shown the demand for customer-to-customer (C2C) electronic commerce. eBay is a centralised infrastructure with all its scalability problems (network bandwidth, server load, availability, etc.). In this paper, we argue that C2C e-commerce is an application domain that maps naturally onto the emerging field of peer-to-peer (P2P) systems simply by its underlying interaction model of customers, i.e., peers. This offers the opportunity to take P2P systems beyond mere file sharing systems into interesting new application domains. The long-term goal would be to design a fully functional decentralised system which resembles eBay without eBay's dedicated, centralised infrastructure. Since security (authenticity, non-repudiation, trust, etc.) is key to any e-commerce infrastructure, our envisioned P2P e-commerce platform has to address these security issues adequately. As the first step in this direction, we present an approach for a completely decentralised P2P public key infrastructure (PKI) which can serve as the basis for higher-level security service. We base it on a statistical approach and present an analytical model to quantify its behaviour and properties and to provide probabilistic guarantees. To justify our claims, we provide a first-order analysis and discuss the PKI's resilience against various known threats and attack scenarios.

The Resource Description Framework (RDF) represents a main ingredient and data representation format for Linked Data and the Semantic Web. It supports a generic graph-based data model and data representation format for describing things, including their relationships with other things. As the size of RDF datasets is growing fast, RDF data management systems must be able to cope with growing amounts of data. Even though physically handling RDF data using a relational table is possible, querying a giant triple table becomes very expensive because of the multiple nested joins required for answering graph queries. In addition, the heterogeneity of RDF Data poses entirely new challenges to database systems. This article provides a comprehensive study of the state of the art in handling and querying RDF data. In particular, we focus on data storage techniques, indexing strategies, and query execution mechanisms. Moreover, we provide a classification of existing systems and approaches. We also provide an overview of the various benchmarking efforts in this context and discuss some of the open problems in this domain. [ABSTRACT FROM AUTHOR]

The proliferation of heterogeneous Linked Data on the Web poses new challenges to database systems. In particular, the capacity to store, track, and query provenance data is becoming a pivotal feature of modern triplestores. We present methods extending a native RDF store to efficiently handle the storage, tracking, and querying of provenance in RDF data. We describe a reliable and understandable specification of the way results were derived from the data and how particular pieces of data were combined to answer a query. Subsequently, we present techniques to tailor queries with provenance data. We empirically evaluate the presented methods and show that the overhead of storing and tracking provenance is acceptable. Finally, we show that tailoring a query with provenance information can also significantly improve the performance of query execution. [ABSTRACT FROM PUBLISHER]

The Internet of Things (IoT) with billions of connected devices has been generating an enormous amount of data every hour. Connecting every data item generated by IoT to the rest of the digital world to turn this data into meaningful actions will create new capabilities, richer experiences, and unprecedented economic opportunities for businesses, individuals, and countries. However, providing an integrated view for exploring and querying such data at real-time is extremely challenging due to its Big Data natures: big volume, fast real-time update and messy data sources. To address this challenge, we provide a unified integrated and live view for heterogeneous IoT data sources using Linked Data, called the Graph of Things (GoT). GoT is backed by a scalable and elastic software stack to deal with billions of records of historical and static datasets in conjunction with millions of triples being fetched and enriched to connect to GoT per hour in real time. GoT makes approximately a half of million stream data sources queryable via a SPARQL endpoint and a continuous query channel that enable us to create a live explorer of GoT ( http://graphofthings.org/ ) with just HTML and Javascript. [ABSTRACT FROM AUTHOR]

Physical-cyber-social (PCS) computing involves a holistic treatment of data, information, and knowledge from the physical, cyber, and social worlds to integrate, understand, correlate, and provide contextually relevant abstractions to humans and the applications that serve them. PCS computing extends current progress in cyber-physical, socio-technical, and cyber-social systems. Here, the guest editors consider powerful ways to exploit data available through various Internet of Things (IoT), citizen and social sensing, Web, and open data sources that are seeing explosive growth. This special issue highlights a variety of PCS applications, such as smart firefighting, intelligent infrastructure, and user guidance in an airport. [ABSTRACT FROM AUTHOR]

This paper introduces the stack for service delivery models and interoperability in the Internet of Things. The main characteristics and functional layers of the IoT stack are described. The applicability of the IoT stack is described based on particular use cases and deployed pilots. The validation of the IoT stack in terms of functionality and adaptation at different IoT particular areas is based on the Virtual Development Kit (VDK) developed and implemented within the framework of the OpenIoT project—OpenIoT project is the awarded Internet of Things open-source rookie of the year by BlackDuck Software Co. (www.github.com/OpenIotOrg ). The methods and standards that boosted OpenIoT-VDK implementation are described in this paper. An instance of the OpenIoT-VDK process is described as the practical use case demonstrating being an IoT platform with autonomic behavior. OpenIoT-VDK creates IoT instances, analyzes the IoT stack dependence, and resolves them following interoperability principles. The OpenIoT-VDK instance deploys IoT service delivery models facilitating the validation of use cases by using the OpenIoT platform. As proof of concept, a delivered IoT service using open data from OpenIoT local instantiation is described. [ABSTRACT FROM PUBLISHER]

Abstract: The W3C Semantic Sensor Network Incubator group (the SSN-XG) produced an OWL 2 ontology to describe sensors and observations — the SSN ontology, available at http://purl.oclc.org/NET/ssnx/ssn. The SSN ontology can describe sensors in terms of capabilities, measurement processes, observations and deployments. This article describes the SSN ontology. It further gives an example and describes the use of the ontology in recent research projects. [Copyright &y& Elsevier]

Abstract: The Web has long exceeded its original purpose of a distributed hypertext system and has become a global, data sharing and processing platform. This development is confirmed by remarkable milestones such as the Semantic Web, Web services, social networks and mashups. In parallel with these developments on the Web, the Internet of Things (IoT), i.e., sensors and actuators, has matured and has become a major scientific and economic driver. Its potential impact cannot be overestimated–for example, in logistics, cities, electricity grids and in our daily life, in the form of sensor-laden mobile phones–and rivals that of the Web itself. While the Web provides ease of use of distributed resources and a sophisticated development and deployment infrastructure, the IoT excels in bringing real-time information from the physical world into the picture. Thus a combination of these players seems to be the natural next step in the development of even more sophisticated systems of systems. While only starting, there is already a significant amount of sensor-generated, or more generally dynamic information, available on the Web. However, this information is not easy to access and process, depends on specialised gateways and requires significant knowledge on the concrete deployments, for example, resource constraints and access protocols. To remedy these problems and draw on the advantages of both sides, we try to make dynamic, online sensor data of any form as easily accessible as resources and data on the Web, by applying well-established Web principles, access and processing methods, thus shielding users and developers from the underlying complexities. In this paper we describe our Linked Stream Middleware (LSM, http://lsm.deri.ie/), which makes it easy to integrate time-dependent data with other Linked Data sources, by enriching both sensor sources and sensor data streams with semantic descriptions, and enabling complex SPARQL-like queries across both dataset types through a novel query processing engine, along with means to mashup the data and process results. Most prominently, LSM provides (1) extensible means for real-time data collection and publishing using a cloud-based infrastructure, (2) a Web interface for data annotation and visualisation, and (3) a SPARQL endpoint for querying unified Linked Stream Data and Linked Data. We describe the system architecture behind LSM, provide details of how Linked Stream Data is generated, and demonstrate the benefits and efficiency of the platform by showcasing some experimental evaluations and the system’s interface. [Copyright &y& Elsevier]

Abstract: Linked Data is becoming the core part of modern Web applications and thus efficient access to structured information expressed in RDF gains paramount importance. A number of efficient local RDF stores exist already, while distributed indexing and distributed query processing over Linked Data with similar efficiency and data management features as known from traditional database and data integration systems are only starting to develop. Distributed approaches will necessarily co-exist with centralized schemes, as data will be owned by different stakeholders who may not want to provide their complete data sets to a central place. Additionally, central/integrated storage may be prohibited for organizational or legal reasons in certain areas. To support decentralized schemes, only a few attempts in this direction exist so far, but they are limited in terms of capabilities and the degree of distribution vs. efficiency, query expressivity, and scalability. To remedy this situation, the approach and proof-of-concept prototype presented in this paper provides a solution for these open challenges. As we argue for widely distributed systems as a possible answer to scalability issues, we first identify and discuss the main challenges and based on this analysis, we propose an approach for efficient and scalable query processing over distributed Linked Data sources, taking into account the latest advances in database technology. Our system is based on a layered architecture that makes use of the advantages of decentralized indexing and query processing approaches, which have been researched and matured over the last decade. Our approach is based on a logical algebra for queries over RDF data and a related physical query algebra to enable optimization, both on the logical and physical layers in query processing. The introduced operators and strategies for processing complex query plans make excessive use of parallelism and other optimization paradigms of distributed query processing. Our query processing framework includes a sophisticated cost model to enable cost-efficient query planning and query execution. We extensively evaluate our approach through an experimental evaluation of a real proof-of-concept deployment, which demonstrates the efficiency, applicability, and correctness of the proposed concepts. [Copyright &y& Elsevier]

Abstract: Network simulators are necessary for testing algorithms of large scale wireless sensor networks (WSNs), but lack the accuracy of real-world deployments. Deploying real WSN testbed provides a more realistic test environment, and allows users to get more accurate test results. However, deploying real testbed is highly constrained by the available budget when the test needs a large scale WSN environment. By leveraging the advantages of both network simulator and real testbed, an approach that integrates simulation environment and testbed can effectively solve both scalability and accuracy issues. Hence, the simulation of virtual WSN, the visualization of real testbed, and the interaction between simulated WSN and testbed emerge as three key challenges. In this paper, we present an integrated framework called NetTopo for providing both simulation and visualization functions to assist the investigation of algorithms in WSNs. NetTopo provides a common virtual WSN for the purpose of interaction between sensor devices and simulated virtual nodes. Two case studies are described to prove the effectiveness of NetTopo. [Copyright &y& Elsevier]

Given the inherent autonomy, heterogeneity, and continuous evolution of Web services, mismatches usually exist between service protocols. Adapters are typically used to reconcile these mismatches. Before synthesizing an adapter, a service requestor is often willing to assess whether her expected interactions can be conducted or not. The effort of synthesizing an adapter is beneficial only if the result of this assessment is positive. Previous effort analyzing service interactions focused on either (i) compatibility analysis for checking whether interactions can be conducted in a direct manner or (ii) adapter synthesization for reconciling mismatches. In this paper we propose a new kind of adaptability assessment that (i) determines whether two service protocols of a requestor and a provider are adaptable, (ii) computes an adaptation degree, and (iii) identifies conditions that determine when these two service protocols can be adapted. This adaptability assessment provides complementary criteria to the service requestor for selecting a suitable service protocol from a set of functionally equivalent candidates according to her requirements. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this paper, we propose an efficient Two-Phase geographic Greedy Forwarding (TPGF) routing algorithm for WMSNs. TPGF takes into account both the requirements of real time multimedia transmission and the realistic characteristics of WMSNs. It finds one shortest (near-shortest) path per execution and can be executed repeatedly to find more on-demand shortest (near-shortest) node-disjoint routing paths. TPGF supports three features: (1) hole-bypassing, (2) the shortest path transmission, and (3) multipath transmission, at the same time. TPGF is a pure geographic greedy forwarding routing algorithm, which does not include the face routing, e.g., right/left hand rules, and does not use planarization algorithms, e.g., GG or RNG. This point allows more links to be available for TPGF to explore more routing paths, and enables TPGF to be different from many existing geographic routing algorithms. Both theoretical analysis and simulation comparison in this paper indicate that TPGF is highly suitable for multimedia transmission in WMSNs. [ABSTRACT FROM AUTHOR]

The existence of an increasing number of different ontologies used in semantic web service fields raises numerous interoperation and communication problems with respect to service discovery, composition, and execution. Current approaches for ontology mediation often fail due to their lack of sufficient semantic expressiveness and reasoning capability. In this paper, we present a novel approach allowing ontologies to provide self-contained semantics for service applications. We show how desired application ontologies can be generated using a new merging algorithm for service ontologies based on the names of the terms. We present experimental results and compare them to the output of the PROMPT ontology merging tool. [ABSTRACT FROM AUTHOR]

Packet filtering used in query process is an important approach to reduce energy consumption in sensor networks. Interest is used as a constraint to filter uninterested data when users query information. Within interested data some are more important because they have more valuable information than that of others. We hope to process these more important data first. In this paper, we firstly define reward to denote the importance level of data, and then we present a two tiers buffer model as the platform for our ETRI packet filtering algorithm. We especially present two packet filtering algorithms for real time and non-real time transmissions. Based on simulation result, we find out that both packet filtering algorithms can substantially improve the quality of information and reduce energy consumption. Copyright © 2007 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Semantic interoperability for the Internet of Things (IoT) is enabled by standards and technologies from the Semantic Web. As recent research suggests a move towards decentralised IoT architectures, we have investigated the scalability and robustness of RDF (Resource Description Framework)engines that can be embedded throughout the architecture, in particular at edge nodes. RDF processing at the edge facilitates the deployment of semantic integration gateways closer to low-level devices. Our focus is on how to enable scalable and robust RDF engines that can operate on lightweight devices. In this paper, we have first carried out an empirical study of the scalability and behaviour of solutions for RDF data management on standard computing hardware that have been ported to run on lightweight devices at the network edge. The findings of our study shows that these RDF store solutions have several shortcomings on commodity ARM (Advanced RISC Machine) boards that are representative of IoT edge node hardware. Consequently, this has inspired us to introduce a lightweight RDF engine, which comprises an RDF storage and a SPARQL processor for lightweight edge devices, called RDF4Led. RDF4Led follows the RISC-style (Reduce Instruction Set Computer) design philosophy. The design constitutes a flash-aware storage structure, an indexing scheme, an alternative buffer management technique and a low-memory-footprint join algorithm that demonstrates improved scalability and robustness over competing solutions. With a significantly smaller memory footprint, we show that RDF4Led can handle 2 to 5 times more data than popular RDF engines such as Jena TDB (Tuple Database) and RDF4J, while consuming the same amount of memory. In particular, RDF4Led requires 10%–30% memory of its competitors to operate on datasets of up to 50 million triples. On memory-constrained ARM boards, it can perform faster updates and can scale better than Jena TDB and Virtuoso. Furthermore, we demonstrate considerably faster query operations than Jena TDB and RDF4J. [ABSTRACT FROM AUTHOR]

The developed world is awash with sensors. However, they are typically locked into unimodal closed systems. To unleash their full potential, access to sensors should be opened such that their data and services can be integrated with data and services available in other information systems, facilitating novel applications and services that are based on the state of the real world. We describe our vision and architecture of a Semantic Web of Things: a service infrastructure that makes the deployment and use of semantic applications involving Internet-connected sensors almost as easy as building, searching, and reading a web page today. [ABSTRACT FROM PUBLISHER]

In the telehealth domain, caregiver networks provide support to the patient in the community, often through a personal health record (PHR). Current PHR systems typically are used where data and services are delivered through a single integrated data store that limits choice, is a fixed solution, and forces providers to conform to a specific data interface. Sqwelch is a mashup maker that enables trusted collaboration between a caregiver network's members through a virtual, distributed PHR. Sqwelch provides an intuitive means for the caregiver network to create personalized mashups, while the patient retains privacy control through trust specifications. [ABSTRACT FROM AUTHOR]