John Soldatos

OpenIoT: Open Source Internet-of-Things in the Cloud

Despite the proliferation of Internet-of-Things (IoT) platforms for building and deploying IoT applications in the cloud, there is still no easy way to integrate heterogeneous geographically and administratively dispersed sensors and IoT services in a semantically interoperable fashion. In this paper we provide an overview of the OpenIoT project, which has developed and provided a first-of-kind open source IoT platform enabling the semantic interoperability of IoT services in the cloud. At the heart of OpenIoT lies the W3C Semantic Sensor Networks (SSN) ontology, which provides a common standards-based model for representing physical and virtual sensors. OpenIoT includes also sensor middleware that eases the collection of data from virtually any sensor, while at the same time ensuring their proper semantic annotation. Furthermore, it offers a wide range of visual tools that enable the development and deployment of IoT applications with almost zero programming. Another key feature of OpenIoT is its ability to handle mobile sensors, thereby enabling the emerging wave of mobile crowd sensing applications. OpenIoT is currently supported by an active community of IoT researchers, while being extensively used for the development of IoT applications in areas where semantic interoperability is a major concern.

Agent based middleware infrastructure for autonomous context-aware ubiquitous computing services

Middleware for ubiquitous and context-aware computing entails several challenges, including the need to balance between transparency and context-awareness and the requirement for a certain degree of autonomy. In this paper we outline most of these challenges, and highlight techniques for successfully confronting them. Accordingly, we present the design and implementation of a middleware infrastructure for ubiquitous computing services, which facilitates development of ubiquitous services, allowing the service developer to focus on the service logic rather than the middleware implementation. In particular, this infrastructure provides mechanisms for controlling sensors and actuators, dynamically registering and invoking resources and infrastructure elements, as well as modeling of composite contextual information. A core characteristic of this infrastructure is that it can exploit numerous perceptual components for context acquisition. The introduced middleware architecture has been implemented as a distributed multi-agent system. The various agents have been augmented with fault tolerance capabilities. This middleware infrastructure has been exploited in implementing a non-obtrusive ubiquitous computing service. The latter service resembles an intelligent non-intrusive human assistant for conferences, meetings and presentations and is illustrated as a manifestation of the benefits of the introduced infrastructure.

A breadboard architecture for pervasive context-aware services in smart spaces: middleware components and prototype applications

We present an architectural framework along with a set of middleware elements, facilitating the integration of perceptual components, sensors, actuators, and context-modeling scripts, comprising sophisticated ubiquitous computing applications in smart spaces. The architecture puts special emphasis on the integration of perceptual components contributed by a variety of technology providers, which has not been adequately addressed in legacy architectures. Moreover, the introduced architecture allows for intelligent discovery and management of resources. Along with the description of this breadboard architecture, we present its non-functional features and assess its performance. We also outline a rich set of practical prototype pervasive services that have been built, based on this architecture. These services emphasize on providing non-obtrusive human-centric assistance (e.g., memory aids, meeting recordings, pertinent information) in the scope of meetings, lectures and presentation, Experiences from building these services manifest the benefits of the introduced architecture.

EMPEROR: An OGSA Grid Meta-Scheduler Based on Dynamic Resource Predictions

Scheduling constitutes an integral feature of Grid computing infrastructures, being also a key to realizing several of the Grid promises. In particular, scheduling can maximize the resources available to end users, accelerate the execution of jobs, while also supporting scalable and autonomic management of the resources comprising a Grid. Grid scheduling functionality hinges on middleware components called meta-schedulers, which undertake to automatically distribute jobs across the dispersed heterogeneous resources of a Grid. In this paper we present the design and implementation of a Grid meta-scheduler, which we call EMPEROR. EMPEROR provides a framework for implementing scheduling algorithms based on performance criteria. In implementing a particular instantiation of this framework, we have devised models for predicting host load and memory resources, and accordingly for estimating the running time of a task. These models hinge on time series analysis techniques and take into account results of the cluster computing literature. Apart from incorporating these models, EMPEROR provides fully fledged Grid scheduling functionality, which complies with OGSA standards as the later are reflected in the Globus toolkit. Specifically, EMPEROR interfaces to Globus middleware services (i.e., GSI, MDS, GRAM) towards discovering resources, implementing the scheduling algorithm and ultimately submitting jobs to local scheduling systems. By and large, EMPEROR is one of the few standards based meta-schedulers making use of dynamic scheduling information.

An ontology-based framework for dynamic resource management in ubiquitous computing environments

Ubiquitous computing applications are supported by sophisticated middleware components enabling dynamic discovery, invocation and management of resources, as well as reasoning in cases of uncertainty. This paper advocates semantic Web technologies as primary vehicles to achieve dynamic management of resources in ubiquitous computing infrastructures and services. We introduce a framework for implementing ubiquitous computing services comprising a large number of sensors and perceptive interfaces, emphasizing the role of knowledge bases for dynamic registration and invocation of resources. We present the use of ontology-based mechanisms for controlling sensors and actuators. Moreover, we describe the implementation of a knowledge base server that can leverage different ontology management systems, while also exposing a host to different client access interfaces. The introduced framework has been exploited in implementing real prototype ubiquitous computing services, which we also outline in the paper.

Defining the Stack for Service Delivery Models and Interoperability in the Internet of Things: A Practical Case With OpenIoT-VDK

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.

Supply chain management and NFC picking demonstrations using the AspireRfid middleware platform

RFID middleware is a cornerstone of non-trivial RFID deployments in complex heterogeneous environments. In this demonstration, we introduce and present the AspireRfid middleware platform using demonstrators in the area of Supply Chain management and Near Field Communications. The AspireRfid platform provides support for non-trivial RFID applications in several fields including supply-chain management, logistics, access control, asset management and pharmaceuticals. In this demonstration we present a traceability application for logistics and supply chain management, as well as a pick and pack application. AspireRfid implements several building blocks of the EPCglobal architecture. However, it also extends the EPCglobal architecture with several middleware modules, which can greatly facilitate RFID application development and deployment. Hence, prior to presenting the demonstrations, we provide a brief discussion of the EPCglobal architecture and the extensions implemented by AspireRFid. We end-up with an illustration of the demonstrators.

Robust Multimodal Audio-Visual Processing for Advanced Context Awareness in Smart Spaces

Identifying people and tracking their locations is a key prerequisite to achieving context-awareness in smart spaces. Moreover, in realistic context-aware applications, these tasks have to be carried out in a non-obtrusive fashion. In this paper we present a set of robust person identification and tracking algorithms, based on audio and visual processing. A main characteristic of these algorithms is that they operate on far-field and unconstraint audio-visual streams, which ensures that they are non-intrusive. We also illustrate that the combination of their outputs can lead to composite multimodal tracking components, which are suitable for supporting a broad range of context-aware services. In combining audio-visual processing results, we exploit a context-modeling approach based on a graph of situations. Accordingly, we discuss the implementation of realistic prototype applications that make use of the full range of audio, visual and multimodal algorithms.

Middleware Building Blocks for Architecting RFID Systems

RFID middleware is a cornerstone of non-trivial RFID deployments in complex heterogeneous environments. In this paper we present the principal middleware building blocks specified in the scope of the EPCglobal architecture. Alternative protocols and implementation frameworks for realizing these middleware blocks are also presented. At the same time we outline several middleware extensions to the EPCglobal architecture, towards meeting common requirements of automatic identification applications. Furthermore, we classify RFID applications into various categories based on their complexity, as well as based on their closed or open loop nature. Accordingly, we highlight the middleware blocks that are most important to each application category.

Design principles for utility-driven services and cloud-based computing modelling for the Internet of Things

By following an analysis of the state of the art in the convergence of cloud computing and the Internet of Things IoT, this paper presents design principles for the IoT in cloud environments. A framework for on-demand establishment of IoT services based on the automated formulation of societies of internet-connected objects is described and the interactions between architecture modules are explained in detail to validate this approach. The main building blocks of the functional framework and its operational components follow the utility-driven cloud-based computing model. The framework leverages well-known technologies i.e. linked sensor data and standards notably the W3C semantic sensor networks ontology. Finally, an example for service formulation and delivery of services for a smart campus scenario is provided and discussed. This paper also introduces some experiment results using the utility-driven service formulation model for mobile applications.