Application Layer Traffic Optimization (ALTO) [5] [8] allows operators to guide the peer selection of P2P applications. Using ALTO, operators can reduce inter-domain transmission costs while at the same time P2P applications can improve their performance. Essentially, an ALTO server is a dedicated service (operated by a network operator or ISP) which can guide applications by providing network layer information about resource providers which applications cannot measure themselves. In this work, we study the effect of ALTO-guidance for P2P live streaming applications. In earlier work [6], we studied to what extent the amount of costly inter-ISP traffic can be reduced with ALTO while still fulfilling the stringent requirements of P2P live streaming. In this work we focus on how ALTO can be beneficial from an application/user perspective. We investigate in which scenarios and to what extent ALTO can reduce application-layer delay and chunk loss, thereby improving the perceived Quality-of-Experience (QoE) for users. Based on datasets that model the Internet's AS-level routing topology with high accuracy, we investigate different peer selection strategies to assess the effectiveness of ALTO-guidance in decreasing delay and chunk loss in P2P live streaming applications.

Many automation systems are used in safety-critical environments, in which any nondeterministic timing behavior of the software may damage equipment or even threaten the health of people. Making software behave deterministically usually relies on hardware-bound optimizations, leaving little room for abstraction layers. This, however, has a negative impact on several important software qualities such as portability, maintainability, or scalability. As a consequence, it becomes difficult to use the same software across different platforms, scale it up or down to changing requirements, or reuse code across different families of products. In this article, we show how both flexibility and robustness can be achieved for real-time automation software. To this end, we present the mechanisms behind the component-based execution framework FASA. This framework offers a platform abstraction mechanism, which allows developers to port it to various platforms in a well-defined manner while maintaining its deterministic qualities. Furthermore, FASA supports runtime reconfigurations and software updates while executing real-time applications without any disruptions. For each of these concepts, we detail our reference implementation.

Automation and monitoring systems for industrial and commercial sites (short: Site Management Systems) often grow organically, hence they need to be able to integrate large numbers of heterogeneous devices, based on both legacy and novel tools and systems. Currently, many standards are used in the site management field for both control (e.g., KNX, BACNet, LON) and communication (e.g., WiFi, Ethernet). Different systems are responsible for different tasks and parts of the site. Since they are usually not designed to interoperate, the site manager is forced to choose one that suits most of her needs, forgoing features offered by alternative solutions. I.e, the flexibility of the site manager is limited. Moreover, site management systems often require technical personnel for installation, calibration and configuration, and are not designed to be modified frequently to adapt to changes. Because of this, the site manager is discouraged from changing the settings of the system or from adding or updating devices, by lack of technical knowledge and by high costs. In other words, a site management system that makes adding new devices, e.g., solar panels, as easy as plugging in and using a webcam is needed.

Software integration tests for embedded systems must cater for the physical process with which the systems interact and can include user input. This can make testing very time-consuming because test engineers often manually execute test specifications with many thousand lines of instructions. Furthermore, such manual tests are often imprecise because human operators cannot execute interactions at a granularity of a few milliseconds. This article presents the CAST (Computer-Aided Specification and Testing) approach to automating the testing of embedded systems, which consists of three parts: a domain-specific language, which allows test engineers to specify test cases formally with a familiar syntax, an execution engine, which allows them to run tests either automatically or interactively, and an interface, which connects the execution engine to the embedded system. We validate the proposed approach by deploying it to a product testing environment and show that our solution provides several advantages such as significantly reduced testing times and more concise test specifications.

When an emergency occurs within a building, it is safer to send autonomous mobile agents instead of human responders, to explore the area and identify hazards and victims. Existing exploration algorithms (Svennebring, J. and Koenig, S. (2004) Building terrain-covering Ant robots: a feasibility study. Auton. Robots, 16, 313–332, Ferranti, E., Trigoni, N. and Levene, M. (2007) Brick&Mortar: An On-Line Multi-Agent Exploration Algorithm. ICRA07: Proc. 2007 IEEE Int. Conf. Robotics and Automation, April, pp. 761–767. IEEE Press) allow mobile agents to make distributed navigation decisions by communicating with nearby fixed sensors embedded in the environment. These algorithms are very efficient in terms of exploration time, but they have only been evaluated in simulation environments, where idealized assumptions were made regarding the ability of agents to localize sensors and move accurately towards them. The objective of this work is to investigate practical issues of building a real testbed of mobile agents and fixed sensors, and implementing exploration algorithms in such a testbed. In particular, we describe our experiences from building a real system consisting of a Surveyor SRV-1 robot and Tmote Sky sensors running the Contiki OS (Dunkels, A., Gron̈vall, B. and Voigt, T. (2004) Contiki — A Lightweight and Flexible Operating System for Tiny Networked Sensors. Proc. 1st Annual IEEE Int. Workshop on Embedded Networked Sensors, November, pp. 455–462). We select two existing exploration algorithms, Ants (Svennebring, J. and Koenig, S. (2004) Building terrain-covering Ant robots: a feasibility study. Auton. Robots, 16, 313–332) and Brick&Mortar (Ferranti, E., Trigoni, N. and Levene, M. (2007) Brick&Mortar: An On-Line Multi-Agent Exploration Algorithm. ICRA07: Proc. 2007 IEEE Int. Conf. Robotics and Automation, April, pp. 761–767. IEEE Press), and discuss challenges in trying to implement them in our testbed. To address these challenges, we propose practical solutions that allow a mobile agent to: (i) identify and localize fixed sensors deployed in its vicinity and (ii) accurately move towards a carefully selected fixed sensor. Using our real network deployment, we derive realistic models of localization and odometry errors. We then insert these error models into a realistic simulation environment, in order to extensively compare Ants and Brick&Mortar, and measure their performance degradation as a result of introducing realistic errors.

When an emergency occurs within a building, it is crucial to guide victims towards emergency exits or human responders towards the locations of victims and hazards. The objective of this work is thus to devise distributed algorithms that allow agents to dynamically discover and maintain short evacuation routes connecting emergency exits to critical cells in the area. We propose two Evacuation Route Discovery mechanisms, Agent2Tag-ERD and Tag2Tag-ERD, and show how they can be seamlessly integrated with existing exploration algorithms, like Ants, MDFS and Brick&Mortar. We then examine the interplay between the tasks of area exploration and evacuation route discovery; our goal is to assess whether the exploration algorithm influences the length of evacuation paths and the time that they are first discovered. Finally, we perform an extensive simulation to assess the impact of the area topology on the quality of discovered evacuation paths.

When an emergency occurs within a building, it may be initially safer to send autonomous mobile nodes, instead of human responders, to explore the area and identify hazards and victims. Exploring all the area in the minimum amount of time and reporting back interesting findings to the human personnel outside the building is an essential part of rescue operations. Our assumptions are that the area map is unknown, there is no existing network infrastructure, long-range wireless communication is unreliable and nodes are not location-aware. We take into account these limitations, and propose a novel algorithm, HybridExploration, that makes use of both mobile nodes (robots, called agents) and stationary nodes (inexpensive smart devices, called tags). As agents enter the emergency area, they sprinkle tags within the space to label the environment with states. By reading and updating the state of the local tags, agents are able to coordinate indirectly with each other, without relying on direct agent-to-agent communication. In addition, tags wirelessly exchange local information with nearby tags to further assist agents in their exploration task. Our simulation results show that the proposed algorithm, which exploits both tag-to-tag and agent-to-tag communication, outperforms previous algorithms that rely only on agent-to-tag communication.

When an emergency occurs within a building, it is critical to explore the area as fast as possible in order to find victims and identify hazards. We propose Brick&Mortar, an algorithm for the autonomous exploration of unknown terrains by a team of mobile nodes, referred to as agents. Because of the unreliability and short range of wireless communications in an indoor environment we suggest that agents communicate indirectly with each other by tagging the environment. Agents have no prior knowledge of the terrain map, but are able to coordinate in order to explore a variety of terrains with different topological features. In our experimental evaluation, we show that Brick&Mortar significantly outperforms the competing algorithms, namely ants and multiple depth first search, in terms of exploration time. The observed performance benefits suggest that our algorithm is suitable for safety-critical applications that require rapid area coverage for real-time event detection and response.