Dennis Pfisterer

A survey on facilities for experimental internet of things research

The initial vision of the Internet of Things was of a world in which all physical objects are tagged and uniquely identified by RFID transponders. However, the concept has grown into multiple dimensions, encompassing sensor networks able to provide real-world intelligence and goal-oriented collaboration of distributed smart objects via local networks or global interconnections such as the Internet. Despite significant technological advances, difficulties associated with the evaluation of IoT solutions under realistic conditions in real-world experimental deployments still hamper their maturation and significant rollout. In this article we identify requirements for the next generation of IoT experimental facilities. While providing a taxonomy, we also survey currently available research testbeds, identify existing gaps, and suggest new directions based on experience from recent efforts in this field.

SPITFIRE: toward a semantic web of things

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.

Deterministic boundary recognition and topology extraction for large sensor networks

We present a new framework for the crucial challenge of self-organization of a large sensor network. The basic scenario can be described as follows: Given a large swarm of immobile sensor nodes that have been scattered in a polygonal region, such as a street network. Nodes have no knowledge of size or shape of the environment or the position of other nodes. Moreover, they have no way of measuring coordinates, geometric distances to other nodes, or their direction. Their only way of interacting with other nodes is to send or to receive messages from any node that is within communication range. The objective is to develop algorithms and protocols that allow self-organization of the swarm into large-scale structures that reflect the structure of the street network, setting the stage for global routing, tracking and guiding algorithms.Our algorithms work in two stages: boundary recognition and topology extraction. All steps are strictly deterministic, yield fast distributed algorithms, and make no assumption on the distribution of nodes in the environment, other than sufficient density.

Neighborhood-Based Topology Recognition in Sensor Networks

We consider a crucial aspect of self-organization of a sensor network consisting of a large set of simple sensor nodes with no location hardware and only very limited communication range. After having been distributed randomly in a given two-dimensional region, the nodes are required to develop a sense for the environment, based on a limited amount of local communication. We describe algorithmic approaches for determining the structure of boundary nodes of the region, and the topology of the region. We also develop methods for determining the outside boundary, the distance to the closest boundary for each point, the Voronoi diagram of the different boundaries, and the geometric thickness of the network. Our methods rely on a number of natural assumptions that are present in densely distributed sets of nodes, and make use of a combination of stochastics, topology, and geometry. Evaluation requires only a limited number of simple local computations.

WISEBED: An Open Large-Scale Wireless Sensor Network Testbed

In this paper we present an overview of WISEBED, a large-scale wireless sensor network testbed, which is currently being built for research purposes. This project is led by a number of European Universities and Research Institutes, hoping to provide scientists, researchers and companies with an environment to conduct experiments with, in order to evaluate and validate their sensor network-related work. The initial planning of the project includes a large, heterogeneous testbed, consisting of at least 9 geographically disparate networks that include both sensor and actuator nodes, and scaling in the order of thousands (currently being in total 550 nodes). We present here the overall architecture of WISEBED, focusing on certain aspects of the software ecosystem surrounding the project, such as the Open Federation Alliance, which will enable a view of the whole testbed, or parts of it, as single entities, and the testbed’s tight integration with the Shawn network simulator. We also present examples of the actual hardware used currently in the testbed and outline the architecture of two of the testbed’s sites.

SpyGlass: a wireless sensor network visualizer

In this paper we present a modular and extensible visualization framework for wireless sensor networks. These networks have typically no means of visualizing their internal state, sensor readings or computational results. Visualization is therefore a key issue to develop and operate these networks. Data emitted by individual sensor nodes is collected by gateway software running on a machine in the sensor network. It is then passed on via TCP/IP to the visualization software on a potentially remote machine. Visualization plug-ins can register to different data types, and visualize the information using a flexible multi-layer mechanism that renders the information on a canvas. Developers can easily adapt existing or develop new custom tailored plug-ins for their specific visualization needs and applications.

Flexible experimentation in wireless sensor networks

Virtual testbeds model them by seamlessly integrating physical, simulated, and emulated sensor nodes and radios in real time.

Shawn: The fast, highly customizable sensor network simulator

Shawn is a discrete event simulator for sensor networks. Due to its high customizability, it is extremely fast but can be tuned to any accuracy that is required by the simulation or application.

Integrating wireless sensor networks into web service-based business processes

Wireless Sensor Networks (WSNs) are envisioned to become an integral part of the Future Internet where they extend the Internet to the physical world. Yet, while Service-Oriented Architectures (SOA) are prospering in Enterprise-IT, wireless sensor networks have -- despite contrary prognoses -- not found their way into enterprises. A major obstacle is certainly the different and resource-constraint nature of this class of devices. We argue that approaches for the seamless integration with existing, widely deployed SOA technologies such as XML, Web Services, and the Business Process Execution Language (BPEL) are key to the success of WSNs in enterprises. In this paper, we present our approach to integrate WSNs into SOA environments using these technologies in a resource-efficient but fully standard-compliant way. We evaluate our implementation and present a case study.

A wireless sensor network for border surveillance

We will demonstrate a wireless sensor network system for the surveillance of critical areas and properties -- e.g. borders. The system consists of up to 10 sensor nodes that monitor a small border area. The protocols we show focus on detecting trespassers across a predefined area and reporting the detection to a gateway node securely. There, the trespassers path will be graphically diplayed on a border map. The demonstration features secure protocols for the detection of trespassers, node failure and network partitioning, along with a duty cycle protocol to ensure network longevity. All information pertaining to relevant events in the network or border area will be graphically displayed on a gateway computer.