During disasters, crisis, and emergencies the public relies on online services provided by official authorities to receive timely alerts, trustworthy information, and access to relief programs. It is therefore crucial for the authorities to reduce risks when accessing their online services. This includes catering to secure identification of service, secure resolution of name to network service, and content security and privacy as a minimum base for trustworthy communication.

As a step towards ubiquitous and mobile computing, a decentralized localization platform allows positioning for objects and persons. The decentralized computation of the position enables to shift the application-level knowledge into a Mobile Station (MS) and avoids the communication with a remote device such as a server. In addition, computing a position on resource-constrained devices is challenging due to the restricted storage, computing capacity, and power supply. Therefore, we propose suitable algorithms to compute unoptimized as well as optimized positions on resource-limited MSs. Algorithms for unoptimized positions will be analyzed with respect to the stability, complexity, and memory requirements. The calculated positions are optimized by using the Gauss-Newton (GNM) or Levenberg-Marquardt methods (LVMs). We analyze and compare the GNM with two variants of the LVM algorithm. Furthermore, we develop an adaptive algorithm for the position optimization, which is based on the Singular Value Decomposition (SVD), LVM algorithm, and the Dilution of Precision. This method allows an adaptive selection mechanism for the LVM algorithm. The influence and choice of the right parameter combination of the LVM algorithm will be analyzed and discussed. Finally, we design and evaluate a method to reduce multipath errors on the MS.

Recently various indoor positioning techniques have been developed based on smartphone. However, most of them need external signals. In this paper a self-contained approach relying on built-in inertial sensors is implemented. Taking advantage of Pedestrian Dead Reckoning, it updates the current position by measuring the length and the heading of each step. Foremost the whole walking process is divided into segments, in which only straight walking is involved. After that the Feature Vectors are extracted for step detection. Specially, to cope with the instabilities caused by gait change, an equivalent Model Wave is created to substitute the original data. Finally, Particle Filter is employed for map matching. According to a group of experiments, our approach is as accurate as traditional positioning technique but shows more robustness.

Nowadays positioning and navigation technologies based on smartphone are sprouting up for numerous application scenarios. In this paper a more self-contained approach is introduced by which merely inertial units within the smartphone are utilized. By the Pedestrian Dead Reckoning technique, all kinds of indoor location information are provided at users' disposal. With the gyroscope, the attitude of smartphone is measured. So the real time accelerations in standard coordinate system without gravity component can be calculated. Here only vertical acceleration signals are made use of to extract the features for steps counting as well as step lengths estimation. A series of algorithms are employed to eliminate the noise and deviation, such as Zero Velocity Compensation, Moving Average Filter, Kalman Filter, and Successive Peaks Merging. Particularly the whole walking process is divided into small segments in each of which only straight walking, no stop, no turn is contained. So, different segments are processed respectively with distinctive parameters. The breakpoints are determined by moving variance analysis for accelerations and rotation angles, after which the heading and length of every step are acquired so that the mileage and position can be updated, closely followed by moving trajectory. In experiments, the average deviation of our approach is 0.48 m.

A major current focus in multi-sensor systems for indoor localisation is how to calibrate the sensors. In this study, we introduce a new method for this task. By using the datafusion of the combined sensor data, we were able to eliminate the errors of an individual sensor. The challenging matter was the connection of the different sensors for a continuous calibration. The necessary data for the calibration were given due to the natural movement of a person. The examination of this values offers an automatic re-calibration without using a given calibration sequence. This finding is promising for improving the calculation of the exact position of a person, who is moving free in a room.

Computer systems are commonly attacked by malicious transport contacts. We present a comparative study that analyzes to what extent those attacks depend on the network access, in particular if an adversary targets specifically on mobile or non-mobile devices. Based on a mobile honeypot that extracts first statistical results, our findings indicate that a few topological domains of the Internet have started to place particular focus on attacking mobile networks.

Smartphones are popular attack targets, but usually too weak in applying common protection concepts. SKIMS designs and implements a cooperative, cross-layer security system for mobile devices. Detection mechanisms as well as a proactive and reactive defense of attacks are core components of this project. In this demo, we show a comprehensive proof-of-concept of our approaches, which include entropy-based malware detection, a mobile honeypot, and spontaneous, socio-inspired trust establishment.

Event detection is a major issue for applications of wireless sensor networks. In order to detect an event, a sensor network has to identify which application-specific incident has occurred based on the raw data gathered by individual sensor nodes. In this context, an event may be anything from a malfunction of monitored machinery to an intrusion into a restricted area. The goal is to provide high-accuracy event detection at minimal energy cost in order to maximize network lifetime. In this paper, we present a system for collaborative event detection directly on the sensor nodes. The system does not require a base station for centralized coordination or processing, and is fully trainable to recognize different classes of application-specific events. Communication overhead is reduced to a minimum by processing raw data directly on the sensor nodes and only reporting which events have been detected. The detection accuracy is evaluated using a 100node sensor network deployed as a wireless alarm system on the fence of a real-world construction site.

In the natural sciences, research often relies on extensive manual investigation. Such methods can be error-prone and obviously don't scale well. The development of autonomous data acquisition systems such as Wireless Sensor Networks (WSN) has provided a method to significantly reduce manual work and, as such, has the potential to enable researchers to address previously infeasible scientific questions. However, making the transition from WSN deployments in a laboratory to real-world deployments is still very challenging. Creating robust, error-free systems that are able to run autonomously in real-world environments without manual supervision has proven to be complex and, therefore, the number of successful collaborations between computer scientists and natural scientists is still limited. Here, we describe our successful attempt to design and deploy a WSN to monitor seabirds on Skomer Island, a UK National Nature Reserve. We summarize the evolution of the system over a period of three years, share insights on selected design decisions, and discuss both, our experience and the problems we have encountered.

In rescue scenarios, real-time requirements are one key issue when using wireless sensor networks (WSNs) for tracking and monitoring of rescue forces. If a node detects an alarm condition, the alarm message must be delivered to the base station in time. To guarantee the timely delivery the whole system architecture has to fulfill real-time requirements. There are only a few real-time architectures which can be used for sensor networks. These architectures are too generic to comply with the other requirements of a WSN architecture, like RAM usage and energy awareness. In this paper, we present FireKernel, a real-time micro kernel designed for WSN operating systems with a special focus on hard real-time requirements and strict energy management. It offers a preemptive real-time scheduler, mutexes and synchronous message passing for interprocess communication (IPC). The scheduler is prioritybased and uses no periodical timers. As part of the kernel we introduce a tickless timer system. We have implemented and tested the kernel on MSP430 and ARM7TDMI based sensor nodes. We discuss the kernel's architecture, implementation and resource usage. Further, we present benchmark results for interrupt latency and energy consumption of the timer architecture.

The main purpose of wireless sensor networks (WSNs) is to obtain information about their environment. However, WSNs often produce imprecise and incorrect sensor data, e.g. because of sensor failure or unreliable radio communication. We propose a system for WSN applications that allows to assess the quality of sensor data and further allows to fuse data based on their estimated quality. Our system comprises local and distributed heuristics to estimate the quality of sensor data, with a focus on data accuracy and data consistency. In the fusion step, the most plausible value of the measured quantity is inferred from multiple sensor readings by use of the Dempster-Shafer theory of evidence. Both quality assessment and data fusion are carried out within the network and thus do not rely on a powerful sink node. We demonstrate the effectiveness of our system by means of a wireless game controller for the game Pong, built from multiple sensor nodes. The controller can detect and reject incorrect sensor readings and thus improve the player's control over the in-game paddle.

Wireless sensor networks (WSNs) are often advertised with high sensing accuracy, long lifetime, and easy deployment. However, they are still not widely used in environmental research due to of poor tool support and high complexity. A wider use of WSNs in field science would enable researchers to address scientific questions that are infeasible today.

ScatterClipse is a generative plugin-oriented tool-chain for the model-driven development of the applications running on the sensor boards of our WSN-platform ScatterWeb. The goal is the furthermost automated and standardized generation of software system families for the ScatterWeb sensor boards. The ScatterClipse's novel approach lies in the accomplishment of the integration of visual automated application debugging and WSN-management features in the model-driven software development process of the deployed sensor boards. Furthermore the just-in-time model validation makes a large contribution towards robustness by discovering certain bugs early on, which, if manually implemented, would only be discovered very late in the process. The plugin-oriented open architecture eases the appropriate enhancement of our opensource tool-chain in response to newly arisen questions regarding WSN.

Service placement deals with the problem of selecting which node in a network is most suitable for hosting a service that responds to queries from other nodes. Optimally placing services reduces network traffic and improves connectivity between clients and servers. Service placement algorithms may thus be regarded as an interesting building block for research into service-oriented middleware. Recently, new approaches to address the service placement problem in the field of ad-hoc networking have been proposed. This paper surveys, classifies and evaluates ten representative approaches, thereby providing a summary of the state of the art in service placement.

In order to avoid transmitting raw data to a base station, sensor nodes are trained to cooperatively recognize deployment-specific events based on the data sampled by their sensors. As both training and event detection are performed without the need for central coordination or processing, only information about the detected event needs to be reported.

Efficient multi-hop data dissemination is a crucial building block to enable mature wireless sensor network (WSN) applications. Exploiting machine learning for these routing problems has received increasing attention in recent years due to its flexibility and localized mechanisms. However, with such an approach the resulting protocols often have additional memory and processing time requirements. Nevertheless, these requirements \emph {are} within the reach of today's WSN hardware, however few substantial tests have been performed to clearly demonstrate this. This paper evaluates and discusses the results and experiences gained from implementing our reinforcement learning based multicast routing protocol (FROMS) in a testbed of ScatterWeb nodes. A comparison of our results is made to a well-known WSN routing scheme, namely a multicast variation of Directed Diffusion. Our evaluation includes several minor, but practical modifications to both protocols such as transmission backoffs and the use of acknowledgments.This paper offers three main contributions. First, we demonstrate that machine learning algorithms \emph{can be} efficiently implemented on resource restricted devices and that they perform very well in multiple network scenarios. Second, we confirm the validity of simulation results obtained in a previous evaluation of FROMS, and at the same time gather delivery rates under realistic settings. Finally, we offer some general observations on properties and pitfalls of WSN implementations along with potential solutions.

In this paper we present the design and implemen tation of a small-scale marine sensor network. The network monitors the temperature in the Baltic Sea on different heights from the water surface down to the bottom. Unlike many other wireless sensor networks, this network contains both a wired and a wireless part. One of the major challenges is that the network is hard to access after its deployment and hence both hard- and software must be robust and reliable. We also present the design of an advanced buoy system featuring a diving unit that achieves a better vertical resolution and discuss remaining challenges of sensor networking in aquatic environments.

Name services for mobile ad hoc networks are essential to discover and bind resources given by their name or URI to a specific network address. As there is no fixed infrastructure available in MANETs, nodes cannot rely on any DNS-like system as is taken for granted in the Internet. To keep up with the dynamicity of MANETs, a name service needs to be flexible and scalable. For this purpose, we propose MAPNaS (mobile ad-hoc peer-to-peer name service), a lightweight and locality-aware peer-to-peer based name service. MAPNaS runs on top of MADPastry (T. Zhan and J. Schiller, June 2005), a general-purpose DHT substrate especially designed for MANETs. Through simulation we compare the performance of MAPNaS - both in terms of the success rate and overall network traffic - against an unstructured, broadcast-based reference approach. We thereby demonstrate how to efficiently build a peer-to-peer based name service in mobile ad hoc networks

Energy conservation plays a crucial in wireless sensor networks since such networks are designed to be placed in hostile and nonaccessible areas. While battery-driven sensors will run out of battery sooner or later, the use of renewable energy sources such as solar power or gravitation may extend the lifetime of a sensor network. We propose to utilize solar power in wireless sensor networks and extend LEACH a well-known cluster-based protocol for sensor networks to become solar-aware. The presented simulation results show that making LEACH solar-aware significantly extends the lifetime of sensor networks.

A vast amount of applications and mechanisms recently developed for mobile ad-hoc networks could greatly benefit from the utilization of network status information. That includes, but is not limited to the detection of network partitioning. Network partitioning is a form of network failure. A single connected network topology breaks apart into two or more network topologies separated from each other. Nodes within each partition are still able to communicate with each other but nodes in other partitions are unreachable. This paper proposes two different partition detection mechanisms, one using a centralized approach, the other one utilizing the advantages of a distributed mechanism. The simulations show that both approaches detect partitioning reliably, with both having unique advantages.

While the concept of UDDI supports the automatic discovery of services implementing a common public tModel interface, there have been only few attempts to find a standardized form to describe the quality of service (QoS) properties of Web services. We introduce our approach "Web service QoS (WS-QoS)" that enables an efficient, dynamic, and QoS-aware selection and monitoring of Web services. The prototype of our approach is implemented with the .NET technology, including the following components: a WS-QoS Editor for the specification of QoS properties, a WS-QoS Requirement Manager for retrieving QoS requirements specified by client applications, a Web service broker for an efficient and QoS-aware selection of Web service offers, and a WS-QoS Monitor for checking the compliance of the service offers.

Studies of mobile ad-hoc networks are often based on simulation and their underlying, necessarily simplified assumptions of physical reality. In order to analyse the practical problems we built our own hardware and software. The hardware consists of a core Motorola controller and different wired and wireless interfaces like a Bluetooth and a 433/868 MHz RF module. It allows therefore analysing different scenarios: First, the deployment of a pure ad-hoc network using Bluetooth or 433/868 MHz RF modules. Scenarios going beyond this cover the connection of Bluetooth piconets using the complementary RF technology. This overcomes the proximity requirements of Bluetooth scatternets. Finally, hybrid scenarios with some nodes connected to the Internet and providing Web access over a multihop adhoc network can be studied.

Sensor networks are designed especially for deployment in adverse and non-accessible areas without a fixed infrastructure. Therefore, energy conservation plays a crucial role for these networks. We propose to utilize solar power in wireless sensor networks, establishing a topology where, changing over time, some nodes can receive and transmit packets without consuming the limited battery resources. We propose and evaluate two protocols that perform solar-aware routing. The presented simulation results show that both protocols provide significant energy savings when utilizing solar power. The paper shows that incorporating the solar status of nodes in the routing decision is feasible and results in reduced overall battery consumption.

Quality of service (QoS) supporting network architectures, like the differentiated services architecture, require a certain agreement regarding service levels. Traffic characteristics like data rates will be part of such agreements and, thus, senders must take care to stay within the agreed limits. Traffic shaping is one important mechanism to avoid penalties in networks (dropped or delayed packets) due to violations of the agreement. This paper presents a new class-based QoS traffic shaper for Linux that aims at shaping aggregate traffic as well as individual flows within an aggregate. In comparison to other approaches (e.g., class-based queuing), our flow based queuing mechanism causes significantly less jitter. Implemented in end-systems, this approach even benefits from direct interaction with applications to create traffic in accordance to application requirements.

Ubiquitous communication will be one of the paradigms for the next decades. The use of the Internet in such applications demands for a highly reliable and secure system, especially when used in non-academical environments like remote offices, e-commerce, or traffic telematics. Today's Internet, even with the mobility extension Mobile IP, has not been designed with private addresses, firewalls, network address translation quality of service etc. in mind. Several optimisations already exist-however security is often neglected. This paper proposes the firewall-aware transparent Internet mobility architecture FATIMA, which integrates security functionality but is transparent to existing Mobile IP implementations. All security critical functions are concentrated in a firewall, all control messages are authenticated, and micro-mobility is supported. Corporate networks with private addresses are supported seamlessly, and further extensions allow for the use of dynamic home addresses and quality of service support.