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When software systems become more complex, it can be advantageous to partition their code into multiple, separate components. In this work, we examine how multiple smart contracts can be coupled to work together. When coupling smart contracts, different design approaches are possible with their own advantages and disadvantages. As an example, we couple two smart contract applications on the Ethereum blockchain: Palinodia and DecentID. Palinodia can be used to ensure the integrity of downloaded executable binaries by checking their hashes against the hashes stored in the blockchain. To make sure that not everyone can modify the data stored on the blockchain, an identity management system is required. This task is fulfilled by DecentID, which provides decentralized identities stored as smart contracts on the blockchain. We evaluate approaches of coupling these two applications and discuss their benefits and drawbacks for this use case.

Many insects use patterns of polarized light in the sky to orient and navigate. Here, we functionally characterize neural circuitry in the fruit fly, Drosophila melanogaster, that conveys polarized light signals from the eye to the central complex, a brain region essential for the fly’s sense of direction. Neurons tuned to the angle of polarization of ultraviolet light are found throughout the anterior visual pathway, connecting the optic lobes with the central complex via the anterior optic tubercle and bulb, in a homologous organization to the ‘sky compass’ pathways described in other insects. We detail how a consistent, map-like organization of neural tunings in the peripheral visual system is transformed into a reduced representation suited to flexible processing in the central brain. This study identifies computational motifs of the transformation, enabling mechanistic comparisons of multisensory integration and central processing for navigation in the brains of insects.

SUMMARYMany insects use patterns of polarized light in the sky to orient and navigate. Here we functionally characterize neural circuitry in the fruit fly,Drosophila melanogaster, that conveys polarized light signals from the eye to the central complex, a brain region essential for the fly’s sense of direction. Neurons tuned to the angle of polarization of ultraviolet light are found throughout the anterior visual pathway, connecting the optic lobes with the central complex via the anterior optic tubercle and bulb, in a homologous organization to the ‘sky compass’ pathways described in other insects. We detail how a consistent, map-like organization of neural tunings in the peripheral visual system is transformed into a reduced representation suited to flexible processing in the central brain. This study identifies computational motifs of the transformation, enabling mechanistic comparisons of multisensory integration and central processing for navigation in the brains of insects.

Protocol detection is the process of determining the application layer protocol in the context of network security monitoring, which requires a timely and precise decision to enable protocol-specific deep packet inspection. This task has proven to be complex, as isolated characteristics like port numbers are not sufficient to reliably determine the application layer protocol. Hence, more dynamic detection approaches have been developed. In this paper, we analyze the Dynamic Protocol Detection mechanisms employed by popular and widespread open-source network monitoring tools. We show on the example of HTTP that all analyzed detection mechanisms are vulnerable to evasion attacks, which pose a serious threat to real-world monitoring operations. We find that the underlying fundamental problem of protocol disambiguation is not adequately addressed in two of three monitoring systems that we analyzed. To enable adequate operational decisions, this paper highlights the inherent trade-offs within Dynamic Protocol Detection.

Payment channel networks are a highly discussed approach for improving scalability of cryptocurrencies such as Bitcoin. As they allow processing transactions off-chain, payment channel networks are referred to as second layer technology, while the blockchain is the first layer. We uncouple payment channel networks from blockchains and look at them as first-class citizens. This brings up the question what model payment channel networks require as first layer. In response, we formalize a model (called RFL model) for a first layer below a payment channel network. While transactions are globally made available by a blockchain, the RFL model only provides the reduced property that a transaction is delivered to the users being affected by a transaction. We show that the reduced model’s properties still suffice to implement payment channels. By showing that the RFL model can not only be instantiated by the Bitcoin blockchain but also by trusted third parties like banks, we show that the reduction widens the design space for the first layer. Further, we show that the stronger property provided by blockchains allows for optimizations that can be used to reduce the time for locking collateral during payments over multiple hops in a payment channel network.

The Matrix message-oriented middleware (see https://matrix.org) is gaining momentum as a basis for a decentralized, secure messaging system as shown, for example, by its deployment within the French government and by the Mozilla foundation. Thus, understanding the corresponding access control approach is important. This paper provides an ab- straction and an analysis of the access control approach followed by Matrix. We show that Matrix can be seen as a form of Distributed Ledger Technology (DLT) based on Transaction-based Directed Acyclic Graphs (TDAGs). TDAGs connect individual transactions to form a DAG, instead of collecting transactions in blocks as in blockchains. These TDAGs only provide causal order, eventual consistency, and no finality. However, unlike conventional DLTs, Matrix does not aim for a strict system-wide consensus. Thus, there is also no guarantee for a strict consensus on access rights. By de- composition of the Matrix approach, we show that a sound decen- tralized access control can be implemented for TDAGs in general, and for Matrix in particular, despite those weak guarantees. In ad- dition, we discovered security issues in popular implementations and emphasize the need for a formal verification of the employed conflict resolution mechanism.

Ensuring the integrity of executable binaries is of vital importance to systems that run and depend on them. Additionally, supply-chain attacks and security related bugs demonstrate that binaries, once deployed, may need to be revoked and replaced with updated versions. Recently, blockchain ecosystems have garnered broad attention as middlewares for decentralised solutions to existing problems. Stengele et al. presented a concept how the Ethereum blockchain and peer-to-peer network can be used to ensure the integrity of binaries with timely, accurate, and machine-readable revocations. In this work, we show this concept in practice with a user client implementation in Go and demonstrate how revocations and updates can reliably reach a user client within minutes. We show the client's ability to ensure the integrity of multiple binaries and continuously monitor the Ethereum blockchain for updates and revocations via an unmodified Ethereum client. We also examine the trust relations and trade-offs through our use case. Since the user client fully relies on an Ethereum client as a gateway, the latter's resilience against malicious actors is crucial to consider in a practical deployment.

Matrix is a new message-oriented data synchronization middleware, used as a federated platform for near real-time decentralized applications. It features a novel approach for inter-server communication based on synchronizing message history by using a replicated data structure. We measured the structure of public parts in the Matrix federation as a basis to analyze the middleware's scalability. We confirm that users are currently cumulated on a single large server, but find more small servers than expected. We then analyze network load distribution in the measured structure and identify scalability issues of Matrix' group communication mechanism in structurally diverse federations.

Temporary blockchain forks are part of the regular consensus process in permissionless blockchains such as Bitcoin. As forks can be caused by numerous factors such as latency and miner behavior, their analysis provides insights into these factors, which are otherwise unknown. In this paper we provide an empirical analysis of the announcement and propagation of blocks that led to forks of the Bitcoin blockchain. By analyzing the time differences in the publication of competing blocks, we show that the block propagation delay between miners can be of similar order as the block propagation delay of the average Bitcoin peer. Furthermore, we show that the probability of a block to become part of the main chain increases roughly linearly in the time the block has been published before the competing block. Additionally, we show that the observed frequency of short block intervals between two consecutive blocks mined by the same miner after a fork is conspicuously large. While selfish mining can be a cause for this observation, other causes are also possible. Finally, we show that not only the time difference of the publication of competing blocks but also their propagation speeds vary greatly.

We explore challenges of and present a concept for a decentralized payment service which is based on trusted execution environments. The system guarantees that users can always cash out their funds without depending on the cooperation of other network members, hence minimizing the trust required in other network members. We present an overview of the system, motivate key components for a secure architecture and provide a communication protocol. We prove that the payment service users can cash out their funds at any time without any dependence on other network members.

Bitcoin relies on a peer-to-peer network for communication between participants. Knowledge of the network topology is of scientific interest but can also facilitate attacks on the users’ anonymity and the system’s availability. We present two approaches for inferring the network topology and evaluate them in simulations and in real-world experiments in the Bitcoin testnet. The first approach exploits the accumulation of multiple transactions before their announcement to other peers. Despite the general feasibility of the approach, simulation and experimental results indicate a low inference quality. The second approach exploits the fact that double spending transactions are dropped by clients. Experimental results show that inferring the neighbors of a specific peer is possible with a precision of 71 % and a recall of 87 % at low cost.

The Lightning Network is a payment channel network built on top of the cryptocurrency Bitcoin. It allows Bitcoin to scale by performing transactions off-chain to reduce load on the blockchain. Malicious payment channel participants can try to commit fraud by closing channels with outdated balances. The Lightning Network allows resolving this dispute on the blockchain. However, this mechanism forces the channels' participants to watch the blockchain in regular intervals. It has been proposed to offload this monitoring duty to a third party, called a watchtower. However, existing approaches for watchtowers do not scale as they have storage requirements linear in the number of updates in a channel. In this work, we propose TEE Guard, a new architecture for watchtowers that leverages the features of Trusted Execution Environments to build watchtowers that require only constant memory and are thus able to scale. We show that TEE Guard is deployable because it can run with the existing Bitcoin and Lightning Network protocols. We also show that it is economically viable for a third party to provide watchtower services. As a watchtower needs to be trusted to be watching the blockchain, we also introduce a mechanism that allows customers to verify that a watchtower has been running continuously.

An essential, but nevertheless often neglected, objective for the design of safety-critical IEEE 802.11p-based application is: fail-safety. A fail-safe application is an application that incorporates features that automatically counteract the effect of anticipated sources of failure. In the context of a rear-end collision avoidance application two main possible sources of failure exist: an unpredictable human behavior and unreliable communication. This paper presents mechanisms that, when integrated into the design of rear-end collision avoidance application, counteract these failure cases and thus ensure fail-safety. However, fail-safety comes at a cost: either large inter-vehicle distances have to be kept to ensure that all drivers have enough time to react or the application has to take over vehicle control to allow smaller inter-vehicle distances and thus higher traffic efficiency. In this paper we analyze this tradeoff and quantify what part of drivers’ population has to be deprived of vehicle control in order to achieve acceptable traffic efficiency when deploying IEEE 802.11p-based rear-end collision avoidance application.

Public Blockchains on their own are, by definition, incapable of keeping data private and disclosing it at a later time. Control over the eventual disclosure of private data must be maintained outside a Blockchain by withholding and later publishing encryption keys, for example. We propose the Atomic Information Disclosure (AID) pattern based on threshold encryption that allows a set of key holders to govern the release of data without having access to it. We motivate this pattern with problems that require independently reproduced solutions. By keeping submissions private until a deadline expires, participants are unable to plagiarise and must therefore generate their own solutions which can then be aggregated and analysed to determine a final answer. We outline the importance of a game-theoretically sound incentive scheme, possible attacks, and other future work.

Intelligent transportation systems (ITS) all around the world are collecting and processing huge amounts of data from numerous sensors to generate a ground truth of urban traffic. Such data has set the foundation of traffic theory, planning and simulation to create rule-based systems but it can also be very useful for time-series analysis to predict future traffic flow. Still, the acceptance for data-driven forecasting is quiet low in productive systems of the public sector. Without enough probe data from floating cars (FCD) ITS owners feel unable to reach an accuracy like private telecommunication or car manufacturing companies. On the other hand, investigating into FCD requires a thoughtful treatment of user privacy and a close look on data quality which can also be very time consuming. With this paper we prove that a modern deep learning framework is capable to operate on city-wide sensor data and produces very good results with even simple artificial neural networks (ANN). In order to forecast space-time traffic dynamics we are testing a Feed Forward Neural Network (FFNN) with different geotemporal constraints and can show where and when they have a positive but also a negative effect on the prediction accuracy.

In September 2013, leading experts in intervehicle communication from all over the world met at the renowned Dagstuhl Castle for a seminar discussing the question "Inter-Vehicular Communication - Quo Vadis?" The objective was to identify the current state of the art and, more important, the open challenges in R&D from both a scientific and an industrial point of view. After more than a decade of research on vehicular networks, the experts very seriously asked whether additional research in this field is necessary and, if so, which will be the most intriguing and innovative research directions. It turned out that the overall perspective has changed in the last few years, mainly as a result of the ongoing field operational tests in the United States and Europe. In this article, we report the key outcomes and results from the discussions, pointing to new research directions and new challenges that need to be met for a second generation of vehicular networking applications and protocols. In particular, we present the reports and findings from the four working groups on scientific foundations of vehicular networking, field operational tests, IVC applications, and heterogeneous vehicular networks.

This special section includes nine technical papers that mainly deal with vehicular wireless networks, covering a rich variety of research topics ranging from vehicular channel modeling to safety application design.

Address clustering tries to break the privacy of bitcoin users by linking all addresses created by an individual user, based on information available from the blockchain. As an alternative information source, observations of the underlying peer-to-peer network have also been used to attack the privacy of users. In this paper, we assess whether combining blockchain and network information may facilitate the clustering process. For this purpose, we apply all applicable clustering heuristics that are known to us to current blockchain information and associate the resulting clusters with IP address information extracted from observing the message flooding process of the bitcoin network. The results indicate that only a small share of clusters (less than 8%) were conspicuously associated with a single IP address. Also, only a small number of IP addresses showed a conspicuous association with a single cluster.

This book constitutes the refereed conference proceedings of the 14th International Workshop on Data Privacy Management, DPM 2019, and the Third International Workshop on Cryptocurrencies and Blockchain Technology, CBT 2019, held in conjunction with the 24th European Symposium on Research in Computer Security, ESORICS 2019, held in Luxembourg in September 2019. For the CBT Workshop 10 full and 8 short papers were accepted out of 39 submissions. The selected papers are organized in the following topical headings: lightning networks and level 2; smart contracts and applications; and payment systems, privacy and mining. The DPM Workshop received 26 submissions from which 8 full and 2 short papers were selected for presentation. The papers focus on privacy preserving data analysis; field/lab studies; and privacy by design and data anonymization. Chapter 2, “Integral Privacy Compliant Statistics Computation,” and Chapter 8, “Graph Perturbation as Noise Graph Addition: a New Perspective for Graph Anonymization,” of this book are available open access under a CC BY 4.0 license at link.springer.com.

Since the development of tree-based Oblivious RAMs by Shi et al. it has become apparent that privacy preserving outsourced storage can be practical. Although most current constructions follow a client-server model, in many applications, such as Genome Wide Association Studies (GWAS), it is desirable that multiple entities can share data, while being able to hide access patterns not only from the server, but also from any other entities that can access parts of the data. Inspired by the efficiency and simplicity of Path-ORAM, in this work, we study an extension of Path-ORAM that allows oblivious sharing of data in a multi-client setting, so that accesses can be hidden from the server and from other clients. We address various challenges that emerge when using Path-ORAM in a multi-client setting, and prove that with adequate changes, Path-ORAM is still secure in a setting, where the clients are semi-honest, do not trust each other, but try to learn the access patterns of each other. We demonstrate our ORAM construction in a GWAS setting. Our experiments show that in databases storing \(2^{23}\) data blocks (corresponding to a database holding \(2^{17}\) blocks per client, capable of storing human genome in the form of SNPs, for 100 clients), the average query time is less than 7 s, yielding a secure and practical solution.

Flooding Peer-to-Peer (P2P) networks form the basis of services such as the electronic currency system Bitcoin. The decentralized architecture enables robustness against failure. However, knowledge of the network's topology can allow adversaries to attack specific peers in order to, e.g., isolate certain peers or even partition the network. Knowledge of the topology might be gained by observing the flooding process, which is inherently possible in such networks,, performing a timing analysis on the observations. In this paper we present a timing analysis method that targets flooding P2P networks, show its theoretical, practical feasibility. A validation in the real-world Bitcoin network proves the possibility of inferring network links of actively participating peers with substantial precision, recall (both ~ 40%), potentially enabling attacks on the network. Additionally, we analyze the countermeasure of trickling, quantify the tradeoff between the effectiveness of the countermeasure, the expected performance penalty. The analysis shows that inappropriate parametrization can actually facilitate inference attacks.

Secure Data Sharing (SDS) enables users to share data in the cloud in a confidential and integrity-preserving manner. Many recent SDS approaches are based on Attribute-Based Encryption (ABE), leveraging the advantage that ABE allows to address a multitude of users with only one ciphertext. However, ABE approaches often come with the downside that they require a central fully-trusted entity that is able to decrypt any ciphertext in the system. In this paper, we investigate on whether ABE could be used to efficiently implement Decentralized Secure Data Sharing (D-SDS), which explicitly demands that the authorization and access control enforcement is carried out solely by the owner of the data, without the help of a fully-trusted third party. For this purpose, we did a comprehensive analysis of recent ABE approaches with regard to D-SDS requirements. We found one ABE approach to be suitable, and we show different alternatives to employ this ABE approach in a group-based D-SDS scenario. For a realistic estimation of the resource consumption, we give concrete resource consumption values for workloads taken from real-world system traces and exemplary up-to-date mobile devices. Our results indicate that for the most D-SDS operations, the resulting computation times and outgoing network traffic will be acceptable in many use cases. However, the computation times and outgoing traffic for the management of large groups might prevent using mobile devices.

The wide scale deployment of cooperative vehicular ad-hoc networks will require the design of efficient congestion control policies that guarantee stable and reliable communications between vehicles and with infrastructure nodes. These policies should reduce the load on the communications channel, while satisfying the strict application's reliability requirements. To this aim, this letter proposes and evaluates a contextual cooperative congestion control policy that exploits the traffic context information of each vehicle to reduce the channel load, while satisfying the vehicular applications requirements.

There has been significant interest and progress in the field of vehicular ad hoc networks over the last several years. VANETs comprise vehicle-to-vehicle and vehicle-to-infrastructure communications based on wireless local area network technologies. The distinctive set of candidate applications (e.g., collision warning and local traffic information for drivers), resources (licensed spectrum, rechargeable power source), and the environment (e.g., vehicular traffic flow patterns, privacy concerns) make the VANET a unique area of wireless communication. This article gives an overview of the field, providing motivations, challenges, and a snapshot of proposed solutions.

In addition to design-time considerations, user trust and the trustworthiness of software-intensive socio-technical systems (STS) need to be maintained during runtime. Especially trust can only be monitored based on the actual usage of the system in operation. Service providers should be able to make informed decisions about runtime adaptation based on trust and trustworthiness, as well as respective essential relations. In this paper we present a unified approach to support the coordination of trust and trustworthiness maintenance. Trustworthiness maintenance is based on measuring objective system qualities, while trust maintenance considers two complementary measures of trust, i.e., the user behavior, and an estimation of the perceived system trustworthiness. A prototype tool demonstrates the feasibility of our approach. Furthermore, we illustrate specific functionalities of the tool by means of an application example.

Sharing data within a closed user group is the basis for lots of applications today in both personal and professional life. The risk that the storage provider or an attacker illegitimately inspects or tampers with the shared data can be mitigated by employing client-side cryptography. In this work, we estimate the resource consumption that secure data sharing based on client-side cryptography requires in terms of computation time and network traffic volume. We therefore go beyond asymptotical analyses and state the absolute resource consumption for different secure data sharing protocols and client devices under realistic sharing models. These sharing models are extracted from traces of real-world collaboration platforms running in production. To the best of our knowledge, this is the first time that such a characterization of sharing models is published. Furthermore, we provide a clearly defined resource consumption estimation model. Our results show that for users who just up-and download data, the execution time of required cryptographic operations is typically up to a few seconds. The results also show that group owners have to deal with significantly higher computation times and network traffic when a user is removed from a sharing group with a few hundred or more members, given that basic secure data sharing protocols are used as they are in place today. A further finding is that computation time and network traffic volume are considerably lowered by extending the secure data sharing protocol with group key management approaches, at the price of slightly raised computation times for smaller groups.

The emergence of decentralized crypto currencies such as Bitcoin and the success of the anonymizing network TOR lead to an increased interest in peer-to-peer based technologies lately -- not only due to the prevalent deployment of mass network surveillance technologies by authorities around the globe. While today's application services typically employ centralized client/server architectures that require the user to trust the service provider, new decentralized platforms that eliminate this need of trust are on their rise. In this paper we critically analyze a fully decentralized alternative to today's digital ecosystem -- MaidSafe -- that drops most of the commonly applied principles. The MaidSafe network implements a fully decentralized personal data storage platform on which user applications can be built. The network is made up by individual users who contribute storage, computing power and bandwidth. All communication between network nodes is encrypted, yet users only have to remember a username and password. To guarantee these objectives, MaidSafe combines mechanisms such as Self-Authentication, Self-Encryption, and a P2P-based public key infrastructure. This paper provides a condensed description of MaidSafe's key protocol mechanisms, derives the underlying identity and access management architecture, and evaluates it with respect to security and privacy aspects.

To achieve highest performance, parallel simulation of networks on modern hardware architectures depends on large numbers of independent computational tasks. However, the properties determining a network model's concurrency are still not well understood. In this paper, we propose an analytical model that enables concurrency estimations based on model knowledge and on statistics gathered from sequential simulation runs. In contrast to an automated concurrency analysis of event traces, the analytical approach enables insights into the relationship between the topology and communication patterns of the simulated network, and the resulting concurrency. We consider three fundamentally different network models as implemented in the network simulators PeerSim and ns-3: a large-scale application-layer peer-to-peer network, IP-based routing in a fixed topology, and a wireless ad-hoc network. For each model, we conduct an in-depth analysis, exposing the relationships between model characteristics and concurrency. Our analysis is validated by comparing estimated concurrency values to reference results of a trace-based analysis. The identification of key factors for concurrency forms a step towards a classification of network models according to their potential for parallelization.

We present a simulation model of the Bitcoin peer-to-peer network, a widely deployed distributed electronic currency system. The model enables evaluations of the feasibility and cost of attacks on the Bitcoin network at full scale of 6,000 nodes. The simulation model is based on unmodified code from core segments of the Bitcoin reference implementation used by 99% of nodes. Parametrization of the model is performed based on large-scale measurements of the real-world network. We present preliminary validation results showing a reasonable correspondence of the propagation of messages in the Bitcoin network compared with simulation results. We apply the model to study the feasibility of a partitioning attack on the network and show that the attack is sensitive to the churn of the attacking nodes.

Many algebraic operations can be efficiently implemented as pipe networks in arrays of functional units such as systolic arrays that provide a large amount of parallelism. However, the applicability of classical systolic arrays is restricted to problems with strictly regular data dependencies yielding only arrays with uniform linear pipes. This limitation can be circumvented by using reconfigurable systolic arrays or reconfigurable data path arrays, where the node interconnections and operations can be redefined even at run time. In this context, several alternative reconfigurable systolic architectures can be explored and powerful tools are needed to model and evaluate them. Well-known rewriting-logic environments such as ELAN and Maude can be used to specify and simulate complex application-specific integrated systems. In this article we propose a methodology based on rewriting-logic which is adequate to quickly model and evaluate reconfigurable architectures (RA) in general and, in particular, reconfigurable systolic architectures. As an interesting case study we apply this rewriting-logic modeling methodology to the space-efficient treatment of the Fast-Fourier Transform (FFT). The FFT prototype conceived in this way, has been specified and validated in VHDL using the Quartus II system.

Position-based routing, as it is used by protocols like Greedy Perimeter Stateless Routing (GPSR) [5], is very well suited for highly dynamic environments such as inter-vehicle communication on highways. However, it has been discussed that radio obstacles [4], as they are found in urban areas, have a significant negative impact on the performance of position-based routing. In prior work [6] we presented a position-based approach which alleviates this problem and is able to find robust routes within city environments. It is related to the idea of position-based source routing as proposed in [1] for terminode routing. The algorithm needs global knowledge of the city topology as it is provided by a static street map. Given this information the sender determines the junctions that have to be traversed by the packet using the Dijkstra shortest path algorithm. Forwarding between junctions is then done in a position-based fashion. In this short paper we show how position-based routing can be aplied to a city scenario without assuming that nodes have access to a static street map and without using source routing.

The random waypoint model is a commonly used mobility model for simulations of wireless communication networks. By giving a formal description of this model in terms of a discrete-time stochastic process, we investigate some of its fundamental stochastic properties with respect to: (a) the transition length and time of a mobile node between two waypoints, (b) the spatial distribution of nodes, (c) the direction angle at the beginning of a movement transition, and (d) the cell change rate if the model is used in a cellular-structured system area. The results of this paper are of practical value for performance analysis of mobile networks and give a deeper understanding of the behavior of this mobility model. Such understanding is necessary to avoid misinterpretation of simulation results. The movement duration and the cell change rate enable us to make a statement about the "degree of mobility" of a certain simulation scenario. Knowledge of the spatial node distribution is essential for all investigations in which the relative location of the mobile nodes is important. Finally, the direction distribution explains in an analytical manner the effect that nodes tend to move back to the middle of the system area.

Existing position-based unicast routing algorithms which forward packets in the geographic direction of the destination require that the forwarding node knows the positions of all neighbors in its transmission range. This information on direct neighbors is gained by observing beacon messages each node sends out periodically. Due to mobility, the information that a node receives about its neighbors becomes outdated, leading either to a significant decrease in the packet delivery rate or to a steep increase in load on the wireless channel as node mobility increases. In this paper, we propose a mechanism to perform position-based unicast forwarding without the help of beacons. In our contention-based forwarding scheme (CBF) the next hop is selected through a distributed contention process based on the actual positions of all current neighbors. For the contention process, CBF makes use of biased timers. To avoid packet duplication, the first node that is selected suppresses the selection of further nodes. We propose three suppression strategies which vary with respect to forwarding efficiency and suppression characteristics. We analyze the behavior of CBF with all three suppression strategies and compare it to an existing greedy position-based routing approach by means of simulation with ns-2. Our results show that CBF significantly reduces the load on the wireless channel required to achieve a specific delivery rate compared to the load a beacon-based greedy forwarding strategy generates.

Mobile IP, the current IETF proposal for IP mobility support, represents a key element for future All-IP wireless networks to provide service continuity while on the move within a multi-access environment. We conducted a performance evaluation of Mobile IPv6 and its proposed enhancements, i.e., Fast Handovers for Mobile IPv6, Hierarchical Mobile IPv6 and our proposed combination of them, using the network simulator ns-2 for the case of a 'hot spot' deployment scenario. The simulation scenario comprises four access routers and up to 50 mobile nodes that communicate in accordance with the IEEE 802.11 wireless LAN standard. The study provides quantitative results of the performance improvements obtained by the proposed enhancements as observed by a single mobile user with respect to handoff latency, packet loss rate and achieved bandwidth per station. As a complementary part of the study, the signaling load costs associated with the performance improvements provided by the enhancements has been analyzed. The simulation environment allowed us also to investigate the behavior of the protocol in extreme cases, e.g., under channel saturation conditions and considering different traffic sources: CBR, VoIP, Video and TCP transfers. While some simulation results corroborate the intention of the protocols specifications, other results give insights not easily gained without performing simulations. This study provides a deep understanding of the overall performance of the various protocols and supports the design process of a Mobile IPv6-based network when a decision of whether it is appropriate to implement any of the proposed Mobile IPv6 enhancements has to be made.

The paper addresses a broad readership in information technology, computer science and related areas, and gives an introduction to fine grain and coarse grain morphware, reconfigurable computing, and its impact on classical computer science and business models. It points out trends driven by microelectronics technology, EDA, and the mind set of data-stream-based computing.

In recent years Arvind’s Group at MIT has shown the usefulness of term rewriting theory for the specification of processor architectures. In their approach processors specified by term rewriting systems are translated into a standard hardware description language for simulation purposes. In this work we present our current investigation on the use of Rewriting-Logic, which is a more powerful theoretical framework than pure rewriting, for specification, exploration and verification of processor architectures at a higher abstraction level. We adopt the rewriting-logic environment ELAN to specify, explore and verify architectures without the need to resort to the details of hardware description languages for simulation purposes. Our investigation shows that simulation at rewriting-logic level may provide useful insights to guide the architectural design.

We performed a simulative evaluation of Mobile IPv6 (MIPv6) via ns-2 for a scenario comprising up to three access routers and 30 mobile nodes that communicate in accordance with the IEEE 802.11 wireless LAN standard. We compare standard MIPv6 to a fast handoff procedure and analyze route optimization issues. We present results with respect to handoff latency, packet loss, end-to-end delay, signaling load, channel utilization, and bandwidth per station, and show how various traffic types like UDP CBR, VoIP, and TCP are affected by the handoffs. While some simulation results corroborate the intention of the protocol specification, other results give insights not easily gained without performing simulations. For example, we learned that (i) the fast handoff mechanism almost fully eliminates packet losses but only improves handoff latency in specific cases, (ii) the signaling load introduced by MIPv6 does not severely affect the performance, and (iii) in a shared environment like IEEE 802.11, traffic type can affect the handoff rate since in high-load situations router advertisements might get lost more frequently thereby 'irritating' the handoff decision mechanism. As a challenge for future simulations we have identified the design of a random mobility model that allows good control of the handoff rate.

Die Möglichkeit mit Hilfe von drahtloser Kommunikation Nachrichten zwischen Fahrzeugen auszutauschen, wird in naher Zukunft das Autofahren sicherer und komfortabler gestalten. Insbesondere das Weiterleiten dieser Nachrichten von einem Sender zu einem oder mehreren Empfängern stellt hierbei eine interessante Herausforderung dar. In diesem Artikel wird ein positionsbasiertes Ad-Hoc Routing Verfahren vorgestellt, welches dieses Problem löst. Dabei arbeiten die Fahrzeuge selbst bei der Weiterleitung von Nachrichten zusammen, so dass keine flächendeckende Infrastruktur notwendig ist. Der vorgeschlagene Ansatz ist daher sowohl kostengünstig als auch robust gegenüber dem Ausfall einzelner Komponenten. Um die Funktionsfähigkeit des positionsbasierten Ad-Hoc Routing Verfahrens nachzuweisen, wurden realitätsnahe Fahrzeugbewegungen erzeugt und als Grundlage für eine Simulationsstudie mit dem Netzwerksimulator ns-2 verwendet. Die Studie belegt, dass auch für die Kommunikation über größere Distanzen und über mehrere Fahrzeuge hinweg sehr gute Zustellraten erreicht werden.

Urban vehicle-to-vehicle radio propagation is commonly modeled using simplified path loss models which are either based on empirical measurements or analytical considerations. These models have in common that their parameterability is rather limited and it is thus only possible to consider, e.g., the distance between transmitter and receiver, antenna heights or street widths. Aspects, such as the shape of an intersection or to which degree vehicles or vegetation are present cannot explicitly be considered using these models. In contrast, recent work suggests that even effects, such as obstructed line-of-sight by vehicles on the road or destructive multipath propagation can drastically influence simulation results. Accordingly, adjusted models are suggested which, however, incorporate only one additional aspect at a time. In this paper, we pursue a different approach and take a first step in evaluating which aspects influence radio conditions in urban areas to which degree and how these individual aspects affect each other. We consequently consolidate existing works and evaluate in which situations a more detailed radio propagation modeling might yield substantially different results with respect to the requirements of IEEE 802.11p networks. In order to achieve comparable results and being able to model several aspects, we employed ray tracing with an accurate geographic scenario and individually modeled obstacles, such as post boxes or trees at the roadside. Our results show and explain that the presence of radio obstacles can indeed make a difference within certain ranges if considered individually, the overall path loss in a heterogeneous and crowded urban scenario, however, is still approximated well with currently employed path loss models.

Distributed Hash Tables (DHTs) provide information lookup within a Peer-to-Peer (P2P) network. A multitude of distributed applications leverages DHTs for offering more advanced services such as distributed file systems, web caches or distributed DNS. For such DHT-based applications, lookup performance is highly important. However, lookup performance is severely affected by network characteristics, i.e., churn and connectivity issues due to NAT routers. As those characteristics are heavily influenced by user behavior, changes are not only likely but also hard to predict. Although DHTs are known for their self-organization, current implementations often do not adapt optimally to variation in network characteristics. In this paper, we propose to dynamically optimize the client through tuning its parameters at run-time. For doing so, different configurations are tested and compared automatically. To reduce overhead, requests sent to other peers are recorded and replayed by a simulation engine, if the same peer is queried again using the same parameter. We evaluated our approach at two exemplary scenarios of the future state of the BitTorrent Mainline DHT (MDHT), one of the most widely used public DHTs. In these scenarios, the lookups of a client using static parameters were more than three times slower and had a 25% higher network overhead than those of an adaptive client. With only 4 additional UDP packets sent per second and a one-digit CPU load, the proposed approach also induces minimal overhead.

The suitability and performance of medium access protocols in vehicular environments is already being investigated over a long period of time. Carrier Sense Multiple Access (CSMA) has been shown to perform sufficiently well in most situations and being able to support safety and efficiency vehicular applications. Recently, Self-organizing Time-Division Multiple Access (STDMA) is being considered as an alternative and has been shown to coordinate the channel slightly better under certain situations. However, when comparing both protocols the precise details of radio and network conditions and parametrization of the protocols are decisive on which protocol takes a slight lead. Consequently, scenarios can be constructed quite easily in which one protocol is superior over the other one. The focus of this work is thus not to absolutely compare both protocols, but rather to understand the strengths and weaknesses of both protocols in certain situations. In particular, we consider i) to which degree hidden nodes influence the coordination ability, ii) how an extended carrier sensing range is beneficial and iii) how temporary fading influences the performance of both MAC protocols. Our results show that while an extended carrier sensing range is only beneficial for CSMA, the existence and severity of fading is far less detrimental for STDMA than for CSMA.

We present an overview of ad hoc routing protocols that make forwarding decisions based on the geographical position of a packet's destination. Other than the destination's position, each node need know only its own position and the position of its one-hop neighbors in order to forward packets. Since it is not necessary to maintain explicit routes, position-based routing does scale well even if the network is highly dynamic. This is a major advantage in a mobile ad hoc network where the topology may change frequently. The main prerequisite for position-based routing is that a sender can obtain the current position of the destination. Therefore, previously proposed location services are discussed in addition to position-based packet forwarding strategies. We provide a qualitative comparison of the approaches in both areas and investigate opportunities for future research.

This letter proposes a novel proactive congestion control policy for vehicular ad-hoc networks, in which each vehicle's communication parameters are adapted based on their individual application requirements. Contrary to other approaches, where transmission resources tend to be assigned based on system-level performance metrics, the technique proposed in this paper aims to individually satisfy the target application performance of each vehicle, while globally minimising the channel load to prevent channel congestion.

Sharing data with client-side encryption requires key management. Selecting an appropriate key management protocol for a given scenario is hard, since the interdependency between scenario parameters and the resource consumption of a protocol is often only known for artificial, simplified scenarios. In this paper, we explore the resource consumption of systems that offer sharing of encrypted data within real-world scenarios, which are typically complex and determined by many parameters. For this purpose, we first collect empirical data that represents real-world scenarios by monitoring large-scale services within our organization. We then use this data to parameterize a resource consumption model that is based on the key graph generated by each key management protocol. The preliminary simulation runs we did so far indicate that this key-graph based model can be used to estimate the resource consumption of real-world systems for sharing encrypted data.

In this paper we propose MentaLink, a tool for preserving and sharing mental links in science. MentaLink is intended as a public knowledge base of links between scientific publications. Contributors can collaboratively define and edit links between entire articles or specific text passages. MentaLink builds on the idea of typed links, allowing authors to explicitly specify how the publications relate to each other, e.g., whether they share the problem statement, whether one publication is built on another or whether they contain contradictory results.

The benefits of distributing a network simulation depend on characteristics of the simulated network. Performance improvements reported in the literature are comparatively low for peer-to-peer overlay networks in particular, as the logical topology of these networks can necessitate frequent synchronization between the processors executing the simulation. In this paper, we show that a speedup of up to a factor of 6.0 using 16 nodes connected using InfiniBand and close to linear reductions in memory usage are possible for simulations of Kademlia-based networks. Our distributed simulator implementation enables simulations of one of the largest peer-to-peer networks at full scale of about 10 million peers. Based on the two fundamental goals of minimizing communication between processors and minimizing synchronization overheads, we propose two strategies for assigning simulated nodes to processors. We analyze the effects of the two strategies and show that each strategy supports one of the goals, while being detrimental to the other. We propose efficiency metrics that expose how much of the potential for parallel execution is exploited by a simulator. Through detailed performance measurements and by applying the new metrics to our simulator implementation, we quantify remaining efficiency potentials.

"Inter-Vehicular Communication -- Quo Vadis?". With this question in mind, leading experts in the field of vehicular networking met in Dagstuhl to discuss the current state of the art and, most importantly, the open challenges in R&D from both an scientific and an industry point of view. After more than a decade of research on vehicular networks, the experts very seriously asked the question whether all of the initial research issues had been solved so far. It turned out that the perspective changed in the last few years, mainly thanks to the ongoing field operational tests in Europe and the U.S. The results point to new research directions and new challenges that need to be solved for a second generation of vehicular networking applications and protocols. In four working groups, the experts studied these new challenges and derived recommendations that are also very helpful for the respective funding organizations.