Daniel Behnke

PASER: Secure and Efficient Routing Approach for Airborne Mesh Networks

Low-altitude unmanned aerial vehicles (UAVs) combined with WLAN mesh networks (WMNs) have facilitated the emergence of airborne network-assisted applications. In disaster relief, they are key solutions for (1) on-demand ubiquitous network access and (2) efficient exploration of sized areas. Nevertheless, these solutions still face major security challenges as WMNs are prone to routing attacks. Consequently, the network can be sabotaged, and the attacker might manipulate payload data or even hijack the UAVs. Contemporary security standards, such as the IEEE 802.11i and the security mechanisms of the IEEE 802.11s mesh standard, are vulnerable to routing attacks as we experimentally showed in previous works. Therefore, a secure routing protocol is indispensable for making feasible the deployment of UAV-WMN. As far as we know, none of the existing research approaches have gained acceptance in practice due to their high overhead or strong assumptions. Here, we present the position-aware, secure, and efficient mesh routing approach (PASER). Our proposal prevents more attacks than the IEEE 802.11sΓi security mechanisms and the well-known, secure routing protocol ARAN, without making restrictive assumptions. In realistic UAV-WMN scenarios, PASER achieves similar performance results as the well-established, nonsecure routing protocol HWMP combined with the IEEE 802.11s security mechanisms.

UAV-Based Connectivity Maintenance for Borderline Detection

The communication aspects of Swarm-based Unmanned Aerial Systems (UAS) for surveillance and monitoring tasks have received increased attention in recent research. In this paper, we address the specific challenges of unpredictable incidents as forest fires, accidents in chemical or nuclear plants which cause potentially dangerous plumes. Therefore, we focus on the detection of chemical plume borderlines while maintaining the connectivity within the UAV team. Leveraging previously developed spatial exploration algorithms like Cooperative Repelling Walk we introduce two novel strategies to optimize the trade-off between detection-efficiency and communication constraints: the Aerosol-detecting Cooperative Repelling Walk (ADCRW) and the Distributed Dispersion Detection (DDD) Algorithm. Both algorithms are evaluated with the help of a multi-scale simulation model which includes a newly incorporated Briggs plume model. Considering the mentioned scenario the results of the performance evaluation demonstrate that the detection-efficiency of our novel algorithms is significantly improved, while at the same time connectivity goals are still met: with the new algorithms the time to detect the borderline of a plume can be reduced by 35%, while the connectivity within the swarm is about 100%.

Comparison of Distributed Ad-Hoc Network Planning Algorithms for Autonomous Flying Robots

The constraints of current monitoring systems, such as stationary data loggers, wired sensor arrays, manned reconnaissance aircraft or remote sensing by means of satellites, have prompted extensive research in wireless sensor networks. Consequently, the use of Unmanned Aerial Vehicles (UAV) for aerial exploration enables the introduction of aerial sensor networks. In this paper we focus on the development of communication aware steering strategies for UAV swarms to achieve quick and comprehensive Spatial Exploration Ratio while maintaining connectivity within the swarm. We develop, enhance and compare two new random based steering strategies, namely Smart Cube and Cooperative RepellingWalk. Our results show that the proposed algorithms simultaneously attain an efficient equilibrium for the mesh connectivity, sensor perception and distribution in the aerial network. Considering autonomous communication awareness enhances the exploration efficiency in terms of swarm coherence and subsequently reliability.

B.A.T.Mobile: Leveraging Mobility Control Knowledge for Efficient Routing in Mobile Robotic Networks

Efficient routing is one of the key challenges of wireless networking for unmanned autonomous vehicles (UAVs) due to dynamically changing channel and network topology characteristics. Various well known mobile-ad-hoc routing protocols, such as AODV, OLSR and B.A.T.M.A.N. have been proposed to allow for proactive and reactive routing decisions. In this paper, we present a novel approach which leverages application layer knowledge derived from mobility control algorithms guiding the behavior of UAVs to fulfill a dedicated task. Thereby a prediction of future trajectories of the UAVs can be integrated with the routing protocol to avoid unexpected route breaks and packet loss. The proposed extension of the B.A.T.M.A.N. routing protocol by a mobility prediction component - called B.A.T.Mobile - has shown to be very effective to realize this concept. The results of in-depth simulation studies show that the proposed protocol reaches a distinct higher availability compared to the established approaches and shows robust behavior even in challenging channel conditions.

Cloud-based semantic services for pan-European emergency preparation and planning

Todays emergency management especially in cross-border incidents is still underlying communication and interoperability barriers. By the introduction of a Common Information Space (CIS) as a socio-technical system, concepts for bridging between involved first responder and Police Authorities becomes evident. Within this paper technical elements of the concepts are described to also demonstrate the practical realization of a CIS.

Common information space for collaborative emergency management

Interoperability and lacks in communication and information sharing are amongst the most common flaws in nowadays emergency management. The socio-technical concept of a Common Information Space (CIS) enhances interoperability and communication even within an organization. In addition, cloud-based implementations of a CIS offer flexibility and adaptability to existing systems and processes. Even more, this allows the efficient integration of a CIS to existing systems and infrastructures. This paper presents a framework concept for cloud-based Common Information Space for emergency management with special regard to cross country use cases. We will present the SecInCoRe concept of a CIS, that somehow can be called a European version and extension of the Unified Incident Command and Decision Support (UICDS, now XChangeCore).

Distributed Flow Permission Inspection for Mission-Critical Communication of Untrusted Autonomous Vehicles

Swarms of Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs) are used for cooperative sensing, clarification and communication relaying in disaster situations and, thereby, allow to reduce jeopardizing the health of rescue personnel. Having meshed interconnection, a swarm maintains a communication network dedicated for applications with context-dependent performance requirements that require reliable traffic classification and conditioning. Nevertheless, these systems are vulnerable because UAVs/UGVs may act incorrectly resulting in an erroneous network behavior which may affect the performance of mission-critical flows. This is a major problem if a couple of untrusted UAVs and UGVs from different rescue organizations are connected. In this paper, the reliability of traffic conditioning within untrusted swarms is enhanced by the Distributed Flow Permission Inspection (DiFPIN) scheme. DiFPIN is used to verify the flow classification to circumvent the usage of erroneous entities on the transmission path. Thereby, the negative impairment of mission-critical flows can be reduced.

ScalaNC — Scalable heterogeneous link aggregation enabled by Network Coding

The aggregation of multiple carriers and even heterogeneous links is a well established method to boost data rates in wireless networks. At the same time, Network Coding has been proven as an efficient and robust mechanism to distribute content in mesh networks or cloud storages. In this paper, we introduce with ScalaNC a new method of heterogeneous link aggregation, which requires no changes in the network infrastructure and incorporates Network Coding to allow for a scalable trade-off between speed, latency and security in terms of confidentiality (information distribution) of the aggregated end-to-end connection. The proposed method is particularly useful in emergency response scenarios, in which first responders need to access cloud storages to retrieve data in harsh communication environments. Using the scalable parameterization the users can increase real-time capability, speed or security depending on the actual needs. ScalaNC is validated with an experimental setup, in which the increase in real-time capability, goodput and security with high packet error rates was demonstrated: while the goodput of an aggregated link operated with Multipath TCP is reduced to around 50 % with occurring packet errors, the ScalaNC-enabled aggregated link maintains stable goodput.

Design and experimental validation of UAV-assisted radiological and nuclear sensing

For the detection of radiological and nuclear material a wide - area deployment of unmanned ground and aerial vehicles acting as an autonomous sensor swarm has been developed and validated by the ANCHORS project. In this paper the software architecture and platform for the control of the heterogeneous robot system as well as the communication system are presented. For a highly-reliable communication the ANCHORS system integrates a flexible ad-hoc wireless communication infrastructure using a combination of a stand-alone LTE system and IEEE 802.11s wireless mesh networking technology. The system was validated in 2015 during a large-scale fire brigade exercise in strong cooperation with potential end-users. Ongoing research addresses the integration of the results gained with systems such as the ANCHORS system in a cloud-based data storage accessible for rescue organizations. The paper introduces therefore the combination of the autonomous distributed sensor swarm with a cloud emergency information system concept currently developed within the EU-Project SecInCoRe (Secure Dynamic Cloud for Information, Communication and Resource Interoperability based on Pan-European Disaster Inventory).

Comparison of multiobjective optimization algorithms for mobility behaviors in autonomous robot systems

Innovative mobility algorithms for autonomous robots have been developed to address civil applications such as disaster relief in the past. Using sophisticated development methodologies such as combinations of model-based as well as Software- and Hardware-in-the-Loop simulations help to reduce the gap between simulations and real world scenarios. An open issue regarding the mobility is to find the optimal parametrization considering multiple optimization goals. In this research work, we introduce and analyze the Mobility Evaluation and Parameter Optimizer (MobEPO). Multiobjective optimization algorithms are used to find optimal parameter sets. We present the approach and a proof-of-concept evaluation in a common exploration scenario. We compare three suitable optimization algorithms and describe their use for prospective steering algorithm design.