Emerging applications such as autonomous driving, virtual reality, and smart factories place greater demands on the Quality of Service of existing network infrastructure, particularly radio networks. The current 5th and new 6th generation of cellular networks aim to meet these requirements and provide ubiquitous connectivity to devices with diverse demands. These networks comprise a control plane and a user plane. While the control plane is responsible for managing the network and its devices, the user plane forwards data and directly influences the experienced Quality of Service. A key network function in the user plane is the User Plane Function (UPF), which forwards packets between cellular network devices and the data network, such as the Internet or an edge data center. However, the extent to which existing UPF implementations can provide sufficient Quality of Service for emerging applications remains largely unexplored. In this work, we analyze and compare various UPF implementations from both theoretical and practical perspectives. We consider both software-based and hardware-accelerated implementations and compare them in terms of performance and latency under load. The setup enables up to 10,000 subscriber sessions while enforcing QoS mechanisms such as rate limiting. The evaluation demonstrates that three of the four investigated UPFs provide QoS enforcement, while their latency behavior differs by orders of magnitude depending on the employed technology.

The centralized control plane in Software-Defined Networking (SDN) offers significant advancements in network management capabilities. However, SDN is also susceptible to cybersecurity risks and vulnerabilities. Deploying the Machine Learning (ML) approach in an Intrusion Detection System (IDS) can facilitate early detection of potential vulnerabilities. However, deploying an ML-based IDS solely in either the SDN control plane or the data plane has its benefits and drawbacks. For instance, a high-capacity ML model deployed in the control plane can enhance the detection performance but may increase network latency and the risk of overwhelming the control plane. In contrast, lightweight ML models deployed in the data plane could accelerate intrusion detection with lower detection performance. However, a functional IDS should provide a good detection performance at a line rate. To accomplish these objectives, we introduce a novel method called Collaborative ML-based IDS (CML-IDS), which involves deploying ML models in both the control and data planes to detect network attacks collaboratively. To facilitate this collaboration, we assess the confidence of the classification model, which is flexibly deployed within the programmable data plane. Our evaluation results demonstrate that the CML-IDS enhances the average intrusion detection performance to 93.46% and reduces the misclassification rate by 54.66% when compared to an IDS that solely relies on the ML model deployed in the data plane. Furthermore, CML-IDS effectively reduces network latency caused by forwarding flows to the control plane.

Let us define transition as the "exchange" between two mechanisms with comparable functionality, but with different algorithms and implementation concepts, which are optimal depending on the respective conditions of the respective context. It is much more that adaptability; it does not cover just the smooth automatic control of e.g., a MAPE loop or a control loop which is in charge to maximize the quality of service of streamed media data while errors occur.

We investigate the application of a recently published metric for flexibility in the context of combined port queue schedules of network paths in Time-Sensitive Networks (TSN). TSN comprises a set of specifications for deterministic networking, including support for scheduled traffic with guaranteed deterministic end-to-end delays. Typically, scheduler resource allocation in TSN disregards flexibility of scheduler configurations. Essentially, the notion of flexibility of paths comprising multiple concatenated ports having each a TSN configuration is based on the number of possible embeddings, i.e., resource allocations, for a new flow of a given specification (size and delay deadline) along that path. This demonstration allows the user to define TSN schedules along network paths and, hence, illustrates the behavior and benefit of performing flexibility-aware TSN configuration.

Large-scale packet queueing and scheduling is the basis for today’s Quality of Service (QoS) in computer access networks, especially to achieve guaranteed high throughput and low latency. While highly performant fixed-function ASICs offer sufficient functionality for most data center use-cases, as of today, they cannot support all functionality required for access networks, e.g., QoS-aware packet queueing.In this poster, we present an FPGA-based architecture for network packet queueing optimized for residential and mobile Internet access networks.

DDoS attack detection is crucial in computer networks to meet the reliability and accessibility requirements of online services. The ability of machine learning to discriminate between DDoS attacks and benign flows makes it a promising candidate for DDoS detection. Correctly classifying the flows with high performance in near real-time is a critical issue for an ML-based DDoS detector to reduce the damages of DDoS attacks. In order to improve the performance of classification and reduce the prediction time, we propose a multi-aspect Ensemble Feature Selection (EFS) for DDoS attack detection in this work. The presented EFS selects the most relevant features of each attack separately, leveraging a combination of statistical filtering approaches and machine learning methods. We evaluate our method on two different datasets to demonstrate the EFS robustness toward model-specific biases. Last, we demonstrate that the prediction time is reduced leveraging the proposed EFS.

Fixed buffer sizing in computer networks, especially the Internet, is a compromise between latency and bandwidth. A decision in favor of high bandwidth, implying larger buffers, subordinates the latency as a consequence of constantly filled buffers. This phenomenon is called Bufferbloat. Active Queue Management (AQM) algorithms such as CoDel or PIE, designed for the use on software based hosts, offer a flow agnostic remedy to Bufferbloat by controlling the queue filling and hence the latency through subtle packet drops.In previous work, we have shown that the data plane programming language P4 is powerful enough to implement the CoDel algorithm. While legacy software algorithms can be easily compiled onto almost any processing architecture, this is not generally true for AQM on programmable data plane hardware, i.e., programmable packet processors. In this work, we highlight corresponding challenges, demonstrate how to tackle them, and provide techniques enabling the implementation of such AQM algorithms on different high speed P4-programmable data plane hardware targets. In addition, we provide measurement results created on different P4-programmable data plane targets. The resulting latency measurements reveal the feasibility and the constraints to be considered to perform Active Queue Management within these devices. Finally, we release the source code and instructions to reproduce the results in this paper as open source to the research community.

Time-Sensitive Networking emerged as a convergent Ethernet-based real-time networking standard for industrial applications. To support real-time, jitter-free isochronous traffic the corresponding TSN mechanism denoted Time Aware Shaper requires special hardware support. In this work, we propose a path to building TSN networks on top of programmable switches. Specifically, we show here how to leverage a data structure amenable to programmable data planes known as Push-in First-out (PIFO) queue to support TSN traffic scheduling for isochronous real-time, as well as, best effort traffic.

The accurate and timely knowledge of a network's internal state is essential for various network management operations like routing, resource allocation, or even intrusion detection. This especially holds true for highly flexible, programmable networks that quickly react to dynamic conditions. However, current approaches of state monitoring in such networks rely on per-rule counter information. Due to limited rule space, their granularity is strongly limited. This generally yields an aggregated and therefore altered representation of the network state. Utilizing the programmability of today's data planes, we tackle this problem and present a novel approach to increase the measurement granularity up to per-application statistics. For demonstration purposes, we show how our approach greatly improves the estimation of the Flow Size Distribution.

In Time-Sensitive Networks (TSN) applications with the highest real-time flow requirements are deployed using the Time-Aware Shaper which requires careful planning and scheduling of flows before deployment. Such deployments lack support for dynamic industrial scenarios such as modular machine assembly and reconfiguration, which require a flexible transition between real-time tasks. In contrast, state-of-the-art techniques rely on flow rescheduling and deployment in conjunction with undesired network downtime. Existing works on adapting schedules to traffic admissions are limited in their ability to choose suitable flows to account for future tasks. In this paper, we aim to leverage the flexibility of scheduler configurations to enable TSN dynamic reconfigurability at runtime. We propose a notion of flexibility for TSN Time-Aware Shaper schedules which we utilize to decide the admissibility of consecutive real-time tasks.

Cooperative Vehicular Maneuvering (CVM) significantly improves traffic safety and efficiency, but relies on wireless information exchange between cooperating vehicles. As wireless links are unreliable and the communication resources are limited, the performance of CVM degrades depending on the communication quality. We propose a novel model to represent the imperfectness of communication, formalize CVM at an intersection, and evaluate the performance degradation of CVM under varying communication conditions. From our analytical perspective, we can derive the requirements for maneuver coordination. Our results provide a valuable resource for the design of future communication technologies and dissemination strategies.

Large-scale telecommunications providers have to continuously challenge and evolve their network infrastructure to efficiently serve growing markets demands. They must increase performance, lower time-to-market, provide new services, and lower the cost of the infrastructure and its operation. Network Functions Virtualization (NFV) on commodity hardware offers an attractive, low-cost platform to establish innovations much faster than with purpose-built hardware products. Unfortunately, implementing NFV on commodity processors does not match the performance requirements of the high-throughput data plane components in large carrier access networks. In this article, we propose a way to offer residential network access with programmable packet processing architectures. Based on the highly flexible P4 programming language, we present a design and open source implementation of a BNG data plane that meets the challenging demands of Broadband Network Gateways in carrier-grade environments. The proposed evaluation results show the desired performance characteristics and our proposed design together with upcoming P4 hardware can offer a giant leap towards highest performance NFV network access.

Recent advances in quality adaptation algorithms leave adaptive bitrate (ABR) streaming architectures at a cross-roads: When determining the sustainable video quality one may either rely on the information gathered at the client vantage point or on server and network assistance. The fundamental problem here is to determine how valuable either information is for the adaptation decision. This problem becomes particularly hard in future Internet settings such as Named Data Networking (NDN) where the notion of a network connection does not exist. In this paper, we provide a fresh view on ABR quality adaptation for QoE maximization, which we formalize as a decision problem under uncertainty, and for which we contribute a sparse Bayesian contextual bandit algorithm denoted CBA. This allows taking high-dimensional streaming context information, including client-measured variables and network assistance, to find online the most valuable information for the quality adaptation. Since sparse Bayesian estimation is computationally expensive, we develop a fast new inference scheme to support online video adaptation. We perform an extensive evaluation of our adaptation algorithm in the particularly challenging setting of NDN, where we use an emulation testbed to demonstrate the efficacy of CBA compared to state-of-the-art algorithms.

We present a novel data-driven approach to perform smooth Wi-Fi/cellular handovers on smartphones. Our approach relies on data provided by multiple smartphone sensors (e.g., Wi-Fi RSSI, acceleration, compass, step counter, air pressure) to predict Wi-Fi connection loss and uses Multipath TCP to dynamically switch between different connectivity modes. We train a random forest classifier and an artificial neural network on real-world sensor data collected by five smartphone users over a period of three months. The trained models are executed on smartphones to reliably predict Wi-Fi connection loss 15 seconds ahead of time, with a precision of up to 0.97 and a recall of up to 0.98. Furthermore, we present results for four DASH video streaming experiments that run on a Nexus 5 smartphone using available Wi-Fi/cellular networks. The neural network predictions for Wi-Fi connection loss are used to establish MPTCP subflows on the cellular link. The experiments show that our approach provides seamless wireless connectivity, improves quality of experience of DASH video streaming, and requires less cellular data compared to handover approaches without Wi-Fi connection loss predictions.

In the aftermath of large-scale disasters, critical communication infrastructure is often destroyed. Ad hoc networks can restore wireless communication with basic functionalities, especially for civilians in the affected areas. However, as humans form groups and tend to stay around important locations like shelters in such situations, the network is highly intermittent. Autonomous Unmanned Aerial Vehicles can act as controllable and highly mobile data carriers between separated network clusters to enable delay-tolerant inter-cluster communication. A possible heterogeneous set of usable aerial vehicles and the necessity to adapt the system to various environments requires the system to be highly flexible. Combined with severe constraints in energy usage or number of available vehicles, there is a need to increase the efficiency of inter-cluster flights. In this paper, we present approaches to optimize inter-cluster flights based on communication performance and energy efficiency. The resulting optimization model is a powerful tool for operators to adjust system settings to match required demands.

Recent approaches to tiled 360° adaptive bitrate video streaming present significant bandwidth savings at little risk of stalling when only parts of the video, e.g., the current and predicted viewport, are transferred in high quality while the rest of the 360° video tiles are transferred in a lower quality. While this is currently feasible for video on demand scenarios, it poses a difficult problem for 360° live streaming as naive methods produce a considerable overhead owing to the lack of tiling support in existing hardware encoders.

Virtual reality has been gaining popularity in recent years fueled by the proliferation of affordable consumer-grade devices such as Oculus Rift, HTC Vive, and Samsung VR. Amongst the various VR applications, 360° video streaming is currently one of the most popular ones. However, it poses a series of challenges to the serving content distribution systems. One challenge is the significantly increased bandwidth requirement for streaming such content in real time. Recent research has shown that only streaming the content that is in the user's (field-of-view) FoV in high quality can lead to strong bandwidth savings. This can be achieved by analyzing the viewers head orientation and movement based on sensor information. Alternatively, historic information from users that watched the content in the past can be considered to prefetch 360° video data in high quality assuming the viewer will direct the FoV to these areas. This paper presents a 360° video streaming system that transitions between sensor- and content-based predictive mechanisms. We evaluate the effects of our system on the Quality of Experience (QoE) of such a VR streaming system and show that the perceived quality can be increased between 50% and 80% compared to systems that only apply either one of the two approaches.

Countless novel approaches to communication protocols, overlay networks, and distributed middleware are published every year, yet the adoption of such novel findings in the global Internet landscape progresses at a slow pace. Many of such new communication mechanisms excel (only) under specific deployment conditions, while user mobility and application usage patterns lead to dynamic operation conditions. This mismatch is one reason that makes a wide deployment of new specialized mechanisms particularly hard as observed, for example, for multipath transport protocol extensions until the emergence of multipath transmission control protocol (TCP). This paper formalizes the concept of Transitions, i.e., a method to instrumentalize adaptivity at runtime in communication systems. It allows to exchange communication mechanisms in a running system to optimize the communication quality. In the following, we describe the building blocks required to: 1) capture the features and relations within a communication system and 2) express and optimize the decision making process in such a system. We show how this concept maps intuitively to the Internet model which makes a protocol-independent deployment of applications feasible in the future Internet.

In this special issue, we have collected and presented recent works on innovative approaches and emerged technologies for coping with dynamicity, heterogeneity, and the scale, which have been central to (or even enablers of) recent advances in communications and networking technologies. At a time of an ever-increasing demand for networking resources and a larger scale, communication networks have faced challenges due to the heterogeneity of the demands, the diversity of communication mechanisms, the high dynamicity of the environments, the virtualization of functions, and the stringent and dynamic quality requirements. In recent years, there have been notable advancements in research and development of concepts and methods for highly adaptive and scalable communication networks.This special issue focuses on recent advances in the field of adaptive and scalable communications.

QUIC is the emerging transport layer protocol, providing encrypted, stream-multiplexed, low-latency data transfer. In this paper, we propose multipath-enabled QUIC (MPQUIC) to leverage multiple network interfaces, such as WiFi and LTE on today's mobile devices. We show how our MPQUIC design conceptually evolves beyond existing multipathing protocols, such as MPTCP, as it provides fine-grained stream-to-path scheduling, reduced head-of-line blocking, and faster subflow establishment. We present an userland implementation of MPQUIC that is deployable without operating system changes. Our evaluation results show that MPQUIC increases throughput in comparison to traditional QUIC, TCP and even the currently de facto multipath transport protocol MPTCP. First real world measurements confirm that MPQUIC is deployable in the Internet to reduce download times. Moreover, we show that MPQUIC's conceptual advantages over MPTCP efficiently reduce head-of-line blocking in heterogeneous environments. With multipathing support, QUIC is ready to become the universal stream transport protocol in today's Internet.

Network state monitoring is a fundamental task for network management. However, determining the full network state in Software defined Networks requires disproportionately too many resources. This stems from the discrepancy between the established methods used for state monitoring compared to the varying contribution in terms of information obtained from every additionally monitored network node. This relationship may even become more complicated depending on the network state information of interest. One solution to overcome bottlenecks by reducing the overall monitoring footprint is the use of spatial sampling, which allows the estimation of the network state based a fraction of the overall state. In this work, we propose schemes to place a small number of measurement points in the SDN network to maximize the obtained network state information. Considering different conditions, we utilize routing information and graph theoretic centrality metrics, respectively, to estimate the amount of information a node provides. Based on this knowledge, we, furthermore, develop a mechanism to place multiple measurement points while avoiding redundant measurements. For demonstration purpose, we use the developed mechanisms to estimate the Flow Size Distribution in SDN environments. An emulative evaluation taking several known topologies shows the effectiveness of spatial sampling using the proposed scheme.

Direct ad hoc connections among mobile devices can be utilized for emergency communication in times when communication infrastructure is unavailable due to blackouts or natural disasters. However, the quality of the resulting mobile ad hoc network strongly depends on the number of devices involved. Thus, to sustain a fully functional emergency communication network, devices need to recharge using external resources (e.g., battery packs, solar panels). Access to these resources needs to be coordinated such that the overall network lifetime is increased. We propose an auction-based resource reservation protocol for a decentralized resource allocation service. Through an extensive simulation study we show that our approach (i) efficiently coordinates the competition for resources, leading to a network lifetime comparable to a global allocation approach (98.8%) and (ii) delays the time until the first node runs out of energy by a factor of 1.4 compared to related work. This increases the value of the emergency communication network significantly, aiding more people over extended periods of time.

The Information-Centric Networking (ICN) paradigm is deemed to enable simpler and more efficient networking interaction by moving from a strict connection based relationship between client and server to an interest-based relationship between user and content. Hence, addressing shifts to content objects rather than any specific copy or location of the content. In order to achieve this new way of addressing the client uses the content name, which is propagated into the network. As a result, a higher efficiency is expected since ICN network nodes (e.g., routers) may reply to such requests using copies from their own caches, or different sources hosting a content object may be used in parallel. Thus, this concept promises better support for device mobility and implicit caching, and it provides inherent multicast support.However, the simplicity of this concept comes at a price. As established applications, such as adaptive bitrate video streaming, have been designed and optimized having a client-server networking environment in mind. In particular, the quality adaptation algorithms used by today's de-facto streaming standard Dynamic Adaptive Streaming over HTTP (DASH) uses bandwidth estimation techniques that are specifically designed for a client-server networking environment where all video segments are retrieved from the same host.This paper addresses issues related to adaptive video streaming in an ICN environment. It analyzes the video streaming behavior of state-of-the-art video quality adaptation algorithms such as PANDA and BOLA in emulated ICN environments. The analysis focuses on the impact ICN chunk-based throughput measurements and ICN caches have on quantitative measurements of Quality-of-Experience (QoE). The paper provides a detailed investigation of the chunk-based throughput estimation showing that it behaves fundamentally different due to ICN caching. Based on these results we provide extensions to existing adaptation algorithms (e.g., PANDA) that can significantly improve the QoE in ICN environments.

Music belongs to one of the most popular content categories overall, and it is nowadays mainly consumed using online streaming services. With YouTube being the largest source of traffic in most networks about half of all YouTube requests address music videos. To cope with the continuously growing demand for content and thus increasing network traffic, YouTube operates its own CDN, a globally distributed network of caches. This allows serving content from locations close to the users, which circumvents potential network bottlenecks and increases the user-perceived QoE due to reduced latency. Recently, proactive caching and prefetching has shown superior performance results compared with traditional reactive caching schemes such as LRU and LFU. Due to the substantial footprint of music videos on today's Internet, we propose a novel proactive caching strategy specifically for music videos. This strategy incorporates two key observations: i) Music genre and mood popularity varies over the course of the day and ii) A video's past views are predictive for its future popularity development. For the classification task, we use a Convolutional Neural Network while investigating several predictive models for the popularity estimation. The proposed caching system can increase the cache hit rate up to 4.5% which is substantial for caching systems.

Content delivery networks (CDNs) carry more than half of the video content in today's Internet. By placing content in caches close to the users, CDNs help increasing the Quality of Experience, e.g., by decreasing the delay until a video playback starts. Existing works on CDN cache performance focus mostly on distinct caching metrics, such as hit rate, given an abstract workload model. Moreover, the nature of the geographical distribution and connection of caches is often oversimplified. In this work, we investigate the performance of cache hierarchies while taking into account the presence of a mixed content workload comprising multiple categories, e.g., news, comedy, and music. We consider the performance of existing caching strategies in terms of cache hit rate and deterioration costs in terms of write operations. Further, we contribute a design and an evaluation of a content category-aware caching strategy, which has the benefit of being sensitive to changing category-specific content popularity. We evaluate our caching strategy, denoted as ACDC (Adaptive Content-Aware Designed Cache), using multiple caching hierarchy models, different cache sizes, and a real world trace covering one week of YouTube requests observed in a large European mobile ISP network. We demonstrate that ACDC increases the cache hit rate for certain hierarchies up to 18.39% and decreases transmission latency up to 12%. Additionally, a decrease in disk write operations up to 55% is observed.

As a step towards fully autonomous driving, Advanced Driver Assistance Systems provide convenience-and safety-related functions to drivers. In addition to data gathered by local sensors, these systems rely on events generated by other vehicles that need to be disseminated to a potentially large audience. Today, this geocast-functionality relies either on subscriptions covering certain areas (e.g., cities) or on individual route-based subscriptions. While the former exhibits suboptimal precision in filtering, the latter introduces significant complexity and assume that routes are known in advance. We propose a prediction-based assessment of the relevance of events without requiring prior route knowledge. Relevance is modeled based on the street network and spatio-temporal characteristics of events. We evaluate our approach in a realistic city setting, relying on the SUMO vehicular mobility simulator. Our first results show that relevance-aware information dissemination reduces the communication overhead by 68%, while at the same time achieving near perfect recall compared to route-based subscrintions.

Mobile applications increasingly rely on frequent and accurate position updates-e.g., with GPS-or Wi-Fi-assisted localization techniques-to provide for functionality to their users. The service quality and acceptance of the application depend strongly on the localization accuracy and the introduced costs, in form of the resource consumption, of the used localization technique. Current mechanisms for location retrieval, however, are limited to non-mobile scenarios or still introduce high costs while obtaining the location. In this work, we propose a collaborative location retrieval service for location-based services in mobile scenarios that combines the location information of a subset of users with the connectivity information between users to enable accurate and cost-efficient location estimations. We evaluate a prototype of our solution to study the impact of service compositions in changing environments and to assess the potential of our proposed service compared to the current state-of-the-art used within location-based services. Our results reveal that, depending on the localization technique, the costs can be reduced significantly while the achieved sensing accuracy and fairness among users improves strongly at the same time.

A decisive advantage of software-defined networking (SDN) is its support for flexible network reconfigurations. Considering that, software-defined networks require accurate and timely data-plane state information. Network monitoring mechanisms usually require considerable resources on SDN controllers as well as on the data-plane elements. In this paper, we propose an optimization of the statistic transmission to reduce costs on both control- and data-plane regardless of the used monitoring application and statistic provisioning tool. To this end, we intercept the statistic message exchange and 1) aggregate multiple requests coming from different monitoring applications/controllers, 2) filter irrelevant statistic messages with respect to their information gain before delivering them to the control applications, and 3) deploy statistic caching. The proposed system, denoted STATISTIC REQUEST RELAY, forms a logically centralized statistic relay between controllers and the managed data-plane network. Our evaluation shows that the number of statistics processed on controllers as well as statistic requests on switches is reduced significantly while the performance penalty is negligible when using statistic aggregation and filtering as proposed here.

State-of-the-art software-defined wide area networks (SD-WANs) provide the foundation for flexible and highly resilient networking. In this work, we design, implement, and evaluate a novel architecture (denoted as SABR) that leverages the benefits of software-defined networking (SDN) to provide network-assisted adaptive bitrate streaming. With clients retaining full control of their streaming algorithms, we clearly show that by this network assistance, both the clients and the content providers benefit significantly in terms of quality of experience (QoE) and content origin offloading. SABR utilizes information on available bandwidths per link and network cache contents to guide video streaming clients with the goal of improving the viewer’s QoE. In addition, SABR uses SDN capabilities to dynamically program flows to optimize the utilization of content delivery network caches. Backed by our study of SDN-assisted streaming, we discuss the change in the requirements for network-to-player APIs that enables flexible video streaming. We illustrate the difficulty of the problem and the impact of SDN-assisted streaming on QoE metrics using various well-established player algorithms. We evaluate SABR together with state-of-the-art dynamic adaptive streaming over HTTP (DASH) quality adaptation algorithms through a series of experiments performed on a real-world, SDN-enabled testbed network with minimal modifications to an existing DASH client. In addition, we compare the performance of different caching strategies in combination with SABR. Our trace-based measurements show the substantial improvement in cache hit rates and QoE metrics in conjunction with SABR indicating a rich design space for jointly optimized SDN-assisted caching architectures for adaptive bitrate video streaming applications.

YouTube is the most popular platform for streaming of user-generated videos. Nowadays, professional YouTubers are organized in so-called multichannel networks (MCNs). These networks offer services such as brand deals, equipment, and strategic advice in exchange for a share of the YouTubers’ revenues. A dominant strategy to gain more subscribers and, hence, revenue is collaborating with other YouTubers. Yet, collaborations on YouTube have not been studied in a detailed quantitative manner. To close this gap, first, we collect a YouTube dataset covering video statistics over 3 months for 7,942 channels. Second, we design a framework for collaboration detection given a previously unknown number of persons featured in YouTube videos. We denote this framework, for the detection and analysis of collaborations in YouTube videos using a Deep Neural Network (DNN)-based approach, as CATANA. Third, we analyze about 2.4 years of video content and use CATANA to answer research questions guiding YouTubers and MCNs for efficient collaboration strategies. Thereby, we focus on (1) collaboration frequency and partner selectivity, (2) the influence of MCNs on channel collaborations, (3) collaborating channel types, and (4) the impact of collaborations on video and channel popularity. Our results show that collaborations are in many cases significantly beneficial regarding viewers and newly attracted subscribers for both collaborating channels, often showing more than 100% popularity growth compared with noncollaboration videos.

Video streaming is responsible for the largest portion of traffic in fixed and mobile networks. Yet, forecasts expect this amount to grow further. Especially for mobile devices connected to cellular networks, high QoE video streaming can be a challenge as the user data volume is metered and eventually limited. Also, the connection quality may vary severely. Prefetching videos is an approach to mitigate this issue. Here, videos that the user is likely to watch in advance are prefetched on the user's smartphone, e.g., while he is connected to WiFi. However, this approach can only be efficient if only the videos that are interesting for the respective user are prefetched. This constitutes a major estimation and prediction challenge. To this end, this paper presents three contributions: First, a user study over multiple months that draws valuable insights on the user video request behavior. Second, we propose a novel privacy-preserving prefetching framework denoted vFetch that prefetches videos based, e.g., on the user's affinity of YouTube channels. Third, a trace-based evaluation and parameter study that demonstrates vFetch's efficiency with a hit rate of ~50% for a 50 GB cache.

Human activity patterns such as communication and cooperation rely in large parts on smartphone-based interaction. Day-to-day available communication means are taken for granted. But in scenarios where communication infrastructure is broken, such as in the aftermath of a disaster, communication establishment becomes crucial. In those post-disaster conditions ubiquitous mobile devices carried by humans can be used to establish basic ad-hoc communication services in order to aid first responders or to organize volunteers. However, these services rely heavily on the runtime of the utilized mobile devices and therefore network failure and communication capability show a strong dependency on the lifetime of mobile devices. In this paper, the potentials of decentralized resource allocation strategies in mobile networks, with harsh post-disaster conditions, are examined. Considering energy resources to prolong functioning of basic post disaster communication services, different resource allocation strategies are proposed. Through an extensive simulation study we show that (i) the proposed strategies for resource allocation lead to significant improvement of the lifetime of the mobile devices (up to 7.8%) and (ii) the time in which a stable service quality (w.r.t. to the received messages) is provided can be extended by 80% compared to the baseline.

Crowd sensing exploits users' smart devices and human mobility to collect information on a large scale. To realize a crowd sensing campaign, sensing tasks with spatio-temporal requirements are distributed to the devices that can provide the requested information. Typically, the distribution of sensing tasks relies on a centralized communication infrastructure such as cloud servers. However, such an approach will be unsuitable if access to communication infrastructure is restricted, for example in disaster relief scenarios. To fill this gap, we propose a distributed context-aware framework for disseminating sensing tasks, based on the Named Data Networking (NDN) paradigm. By adding context attributes to Interest packets, we allow a device to utilize this information to make forwarding decisions autonomously, thus guiding the sensing tasks towards the suitable sensing devices. Through intensive evaluation, we show that our framework achieves a timely delivery of sensing tasks, while keeping the communication overhead to a minimum compared to pure geo forwarding and flooding approaches.

The advent of the Internet of Things (IoT), with modern sensors and sensor-based devices, will significantly stimulate the development of context-aware applications. An effective means to extract higher-level contextual information from sensor data is distributed complex event processing (CEP), which facilitates the analysis of real-time data streams coming from heterogeneous and distributed sources. Considering that user context is inherently sensitive information, the preservation of privacy is critical once the processing of user context takes place over several (possibly malicious) devices, especially in collaborative scenarios. In this paper, we tackle this issue by introducing a trust-based approach for the placement and execution of CEP operators in a distributed environment. We propose a trust management model based on communication interactions among the users. Furthermore, we incorporate trust recommendations using a cosine-based similarity check in order to overcome collusion and on-off attacks. We developed a smartphone-based distributed CEP system called TrustCEP to evaluate our approach for trust management. Based on the evaluation of TrustCEP, we observe that our approach induces a minimal increase in average battery consumption compared to privacy-negligent approaches.

Multipath TCP enables remarkable optimizations for throughput, load balancing, and mobility in today's networks. The design space of Multipath TCP scheduling, i.e., the application-aware mapping of packets to paths, is largely unexplored due to its inherent complexity. Evidence in this paper suggests that an application-aware scheduling decision, if leveraged right, pushes Multipath TCP beyond throughput optimization and thereby provides benefits for a wide range of applications.

The current body of research on Dynamic Adaptive Streaming over HTTP (DASH) contributes various adaptation algorithms aiming to optimize performance metrics such as the Quality of Experience. Intuitively, the heterogeneity of the streaming environment and the underlying technologies lead many of the developed approaches to possess clear performance affinities denoted here as sweet spots. We observe, however, that systematic comparisons of these algorithms are usually conducted within homogeneous player environments.

State-of-the-art Software Defined Wide Area Networks (SD-WANs) provide the foundation for flexible and highly resilient networking. In this work we design, implement and evaluate a novel architecture (denoted SABR) that leverages the benefits of SDN to provide network assisted Adaptive Bitrate Streaming. With clients retaining full control of their streaming algorithms we clearly show that by this network assistance, both the clients and the content providers benefit significantly in terms of QoE and content origin offloading. SABR utilizes information on available bandwidths per link and network cache contents to guide video streaming clients with the goal of improving the viewer's QoE. In addition, SABR uses SDN capabilities to dynamically program flows to optimize the utilization of CDN caches.; [email protected] by our study of SDN assisted streaming we discuss the change in the requirements for network-to-player APIs that enables flexible video streaming. We illustrate the difficulty of the problem and the impact of SDN-assisted streaming on QoE metrics using various well established player algorithms. We evaluate SABR together with state-of-the-art DASH quality adaptation algorithms through a series of experiments performed on a real-world, SDN-enabled testbed network with minimal modifications to an existing DASH client. Our measurements show the substantial improvement in cache hitrates in conjunction with SABR indicating a rich design space for jointly optimized SDN-assisted caching architectures for video streaming applications.

Using cloud computing for IT service provisioning has become a common practice over the last years. Besides basic infrastructure services, more advanced multimedia services with high Quality of Service (QoS) requirements are offered. To fulfill such requirements, appropriate cloud resources must be used for service provisioning. In this paper, we analyze different heuristic approaches to speed up the selection procedure of cloud resources while ensuring a high solution quality at the same time. In the work at hand, we present a Best-of-Breed approach, which is assembled by simple heuristics. Further, we adopt an advanced metaheuristic approach, i.e., tabu search, for the given problem and compare it with the former mentioned approach. With our approaches, we offer the means for a cloud provider to select appropriate resources from a large pool to facilitate QoS-aware multimedia service provisioning.

Multiple offloading techniques are used in today's communication systems. Most approaches rely on cellular offloading to reduce the burden on the cellular infrastructure, especially in crowded situations. While the load on the cellular infrastructure decreases, network participants that are actively involved in the networking effort by device-to-device communication carry the load of a majority of devices. Though, by focusing on the cellular medium for offloading, the increased number of public available network access points remains mostly unused by most approaches. Incorporating access points for offloading entails numerous advantages, such as a reduced load on the cellular data plan of mobile users. In this work, the potentials of multi-dimensional offloading are assessed using the example of a state-of-the-art adaptive monitoring system that, so far, only employs cellular and device-to-device offloading. We show that the system can benefit from adding additional components and protocols that enable multi-dimensional offloading. Through an extensive simulation study we show that combining different offloading techniques leads to significant improvements regarding the achieved service quality (up to 15-fold) and the responsiveness (up to 5-fold), while reducing the load on the mobile nodes by at least 35% even in scenarios with good cellular connectivity.

The increasing capabilities of modern smartphones lead to the design of mobile social applications focusing on direct interaction between users. Ranging from mobile social networks to fully-fledged augmented reality games, these applications usually operate on contextual information to identify relevant content - most notably, the user's physical location. The resulting locality properties of the interaction between users are not well reflected by the cloud-based, centralized infrastructure utilized in today's mobile applications. Thus, data that is relevant to a group of nearby users is downloaded multiple times via the cellular network. Due to capped and/or expensive data tariffs, this can have severe impact on the user acceptance of such applications. To address this issue, we propose the concept of stateless gateways to augment cloud-based mobile social applications. A stateless gateway is chosen by the cloud to distribute information to nearby interested parties, without requiring any additional state information on the gateway itself. We integrate the concept into a location-based publish/subscribe system and show the resulting performance and cost characteristics through extensive evaluations. Our results show that the stateless concept enables frequent gateway switches, lowering the load on the cellular network by 70% for the scenario of a mobile augmented reality game. At the same time, our system achieves better fairness characteristics among participants due to a more efficient utilization of gateway nodes compared to a less flexible assignment of gateways.

Instant sharing of user-generated video recordings has become a widely used service on platforms such as YouNow. Yet, it still poses technical challenges, as mobile upload speed and capacities are limited. One proposed solution to address these issues is video composition. It allows switching between multiple video streams-selecting the best source for a given time-for composing a live video of a better overall quality for viewers. Previous approaches require visual analysis of the video streams, usually limiting the scalability of the system. In contrast, our work allows the stream selection to be realized solely on context information, based on video-and service-quality aspects from sensor and network measurements. The implemented monitoring service for context-aware upload of video streams is evaluated in varying network conditions, with diverse user behavior, including camera shaking and user mobility. We show that a higher efficiency for video upload as well as QoE for viewers can be achieved.

With a plethora of sensors and ubiquitous access to the Internet, modern smartphones have enabled a broad range of context-based applications. Most applications make use of the user's physical location to filter relevant content. However, filtering based on dynamic contextual information results in high complexity of the filtering process. This limits the applicability of existing publish/subscribe systems, as they rely on aggregation of filters and fast decentralized matching and forwarding. In this work, we propose a mechanism for transitions between different filter schemes for location-based services. Our mechanism adapts the filtering process to the dynamics in user behavior and resulting load by trading computational complexity at the broker against communication overhead and computational complexity at the mobile client. We integrate our mechanism into an existing publish/subscribe system and evaluate transitions between a context-based filter scheme and two channel-based filter schemes, showing the applicability of our approach.

Today, mobile nodes use multiple Internet access networks inefficiently. State-of-the-art network selection strategies distribute data traffic to available networks, but ignore an important second dimension: time. Time selection offers the opportunity to plan usage of future-available networks for delay-tolerant data traffic. We hypothesize, that concurrent selection of network and time leads to synergy effects, which reduce transmission cost and boost connectivity performance. To assess data distribution to wireless networks and time, we propose a novel rating model for joint network and time selection. The proposed model rates the satisfaction of Quality-of-Service (QoS) application requirements and trades off conflicting optimization goals. Moreover, we analyze the impact of time in network selection and present three network selection schedulers, which differ in their time selection strategy. Evaluation of the results reveals a strong impact of time selection on network performance. This gives evidence, that our initial hypothesis holds and forward-looking scheduling strategies provide a substantial benefit over state-of-the-art approaches.

Recently, a number of offloading approaches have been proposed to reduce the burden on the cellular infrastructure, especially during peak hours. Ranging from pure data offloading concepts using local caches to fully-fledged services operating on ad hoc networks, these approaches are mostly tuned towards their performance. Consequently, cache hit ratios, achieved throughput, or end-to-end latencies, are prominent evaluation metrics. However, when utilizing users' resources to improve the performance of a shared service, the fairness with respect to the resources contributed by individual users should be considered as well. Resource consumption, e.g., the battery lifetime, can vary significantly between individual users, depending on their contributions. This effect can have a significant impact on user acceptance and, thus, the usability of the overall system. In this paper, we examine the trade-off between overall system performance and fairness w.r.t. resource utilization for a state-of-the-art monitoring service relying on offloading. To bridge the identified gap between performance and fairness, we propose a number of protocol adjustments to increase the system's fairness. Through an extensive simulation study we show that the proposed mechanisms lead to improvements in the overall achieved fairness of up to 60%, with below 4% degradation in service quality.

User-generated content, such as short video snippets or tweets, is increasingly used in event coverage even by professional media outlets. Especially in unforeseen events, or when dealing with large crowds, these snippets provide unique perspectives on the scene. While uploading a tweet does not impose much load on the communication system, uploading live video at today's camera resolutions consumes a significant amount of resources. At the same time, only a fraction of the uploaded streams is suitable for event coverage (e.g., shakiness of the video, focus on the scene, obstructions). By identifying the set of relevant streams early, and postponing the upload of other content, the available network resources can be dedicated to the upload of the most relevant streams. In this paper, we propose a set of strategies to collaboratively upload the most relevant streams at high quality by utilizing freed resources. We argue that these strategies can be exchanged during runtime to adapt to user dynamics and network heterogeneity, and present initial findings on the performance of our system.

The increasing capabilities of mobile communication devices are changing the way people interconnect today. Similar trends in the communication technology domain are leading to the expectation that data and media are available anytime and everywhere. A result is an increasing load on communication networks. In dynamic mobile networks that particularly rely on wireless communication such data requirements paired with environmental conditions like mobility or node density increase the risk of network failure. Consequently, monitoring is crucial in mobile networks to ensure reliable and efficient operation. Current monitoring mechanisms mostly rely on a static architecture and exhibit problems to handle the changes of mobile networks and environmental conditions over time. In this paper, an adaptive monitoring mechanism is presented to overcome these limitations. The mechanism exploits the connectivity and resource characteristics of mobile communication devices to (i) reconfigure its monitoring topology and (ii) adapt to changes of mobile networks and environmental conditions. Through evaluations we show that our proposed solution reduces the achieved relative monitoring error by a factor of six and represents a robust and reliable monitoring mechanism for these challenging environments.

Existing measurement frameworks typically assume that the communication protocols and mechanisms running on the devices do not change during network operation. However, recent research efforts show that by enabling devices to switch between protocols and mechanisms at runtime the overall network performance can be improved. In this paper, a novel measurement framework that enables the continuous and consistent measurement of monitoring metrics even across such adaptations in networks is presented. The framework exploits monitoring metrics locally on the devices (i) irrespectively of the used mechanisms or protocols on the devices and (ii) allows other mechanisms and applications in the network to adapt to changes by referring monitoring information from the framework. A proof-of-concept prototype of the measurement framework is used to show that the work represents a promising step towards protocol-independent, adaptive monitoring in dynamic networks.

Currently discussed handover protocols do not provide the means to allow holistic flow handover scheduling. However, flow scheduling leads to a performance boost resulting from efficient parallel network use and a match of network characteristics to application requirements. Mobile IPv6 with flow binding extension and route optimization fulfills most requirements. However, control data is redundantly transmitted to every communication partner. This forbids coordination of parallel data flows and, therefore, scheduling. We introduce a new publish-subscribe-based control data routing which makes Mobile IPv6 compatible with centralized flow scheduling and furthermore reduces overhead via the wireless channels. The result offloads computationally intensive tasks of scheduling to servers in the Internet and moves handover control to the same. The resulting handover protocol is an enabler for client-centric scheduling and paves the way towards this promising topic.

Recent studies show that an increasing number of over-the-top live streams is delivered over the Internet. For the delivery of those streams, the dynamically changing and potentially large number of users imposes a major challenge. Flash crowds, where the number of users multiplies or significantly drops in a very small time frame, can cause serious degradations in the streaming performance. Due to the missing support for global network-layer multicast, overlay-based approaches have been broadly studied, showing that, with relaxed time constraints, they can scale well with the number of users. Yet, to support flash crowds, scaling has to happen quickly to keep up also with rapidly changing populations. Only a few approaches exist that focus on this aspect by influencing the streaming topology and, so far, it is not clear if and how these mechanisms can be applied to state-of-the-art hybrid streaming systems. Therefore, in this paper, TOPT is proposed, integrating new as well as existing mechanisms in a common framework. The evaluation shows that the streaming topology, indeed, plays a major role during flash crowds. The lightweight and decentralized tree-forming and topology optimization mechanisms of TOPT, combined with tracker extensions to attach new peers in batches, greatly help improving the streaming performance in terms of reduced playback interruptions by more than 60% and slight reduction in communication overhead at an acceptable increase in average startup delays by 24%.

Today's smartphones feature sophisticated computational capabilities as well as a plethora of sensors, enabling new kinds of applications. One popular example are pervasive mobile multiplayer games, where interactions with other users or physical objects in the real world are part of the gameplay. This induces a notion of locality, as a user's actions affect other nearby users. However, this locality in the interaction is not reflected in the underlying communication system. Events triggered by users are sent via the cellular connection to a remote data center, where they are processed and then distributed to other players, again via the cellular link. In this work, we demonstrate an event dissemination system that utilizes the available local communication interfaces of today's smartphones to distribute events in groups of nearby players. The system executes transitions between different communication interfaces (e.g., Bluetooth or Wi-Fi Direct) and the utilized dissemination protocol depending on the size and density of the group of players, thereby exploiting the characteristics of the chosen interface. Attendees can experience the resulting benefits in terms of latency and update frequency by playing our mobile pervasive multiplayer game TowerWorld at the venue.

Cloud infrastructure is increasingly used for the provision of sophisticated multimedia services, such as cloud gaming or Desktop as a Service, with stringent Quality of Service demands. Serving these service demands results in the need to cost-efficiently select and capacitate data centers. In the work at hand, we introduce the corresponding Cloud Data Center Capacitation Problem and propose two optimization approaches. Through a quantitative evaluation, we demonstrate that an exact solution approach is only practically applicable to small problem instances, whereas a heuristic based on LP relaxation achieves significant reductions in computation time of about 80% while retaining a favorable solution quality, with cost increases of approximately 5% or less.

While cloud computing provides a high level of flexibility, it also implies a shift of responsibility to the cloud provider and thus, a loss of control for cloud consumers. Although existing means such as service level agreements or monitoring solutions offered by cloud providers aim to address this issue, there is still a low degree of trust on consumer side that cloud providers properly measure compliance against SLAs. A solution lies in designing reliable means for monitoring cloud-based services from a consumer's perspective. We already proposed such a monitoring approach in our former work. However, our experiments revealed that our approach is sensitive to network impairments. Hence, in the work at hand, we introduce the Robust Cloud Monitor Placement Problem and present a formal optimization model. Based on the model, we propose an initial optimization approach, that allows to obtain an exact solution using off-the-shelf algorithms.

While cloud computing promises virtually unlimited resource supplies, smaller providers may not be able to offer sufficient physical IT capacity to serve large customers. A solution is cloud collaborations, in which multiple providers unite forces in order to conjointly offer capacities in the market. Unfortunately, both the QoS and security properties of such collaborations will be determined by the “weakest link in the chain”, hence resulting in a trade-off between the cumulative capacity and the non-functional characteristics of a cloud collaboration. In this position paper, we examine how cloud collaborations can be optimally composed in a QoS- and security-aware fashion within a market scenario involving multiple cloud providers and users. We propose a Mixed Integer Programming-based exact optimization approach named CCCP-EXA. Based on a quantitative evaluation, we find that the practical applicability of CCCP-EXA is limited to small-scale problem instances and conclude that the development of tailored heuristic approaches is required.

Today's cloud environments are very heterogeneous. This cloud heterogeneity, as the consequence of lacking cloud standards, builds technical and security barriers between cloud providers and blocks them from intended cloud collaborations within cloud marketplaces. A cloud broker, who acts on behalf of cloud providers, matches compatible collaborative partners according to their requirements and attempts to support the optimal exchange of cloud resources between them. The fulfillment of security requirements in cloud collaborations usually involves providing risk assessments, which are still very time-consuming and not applicable for ad hoc cloud collaborations within cloud marketplaces. Aiming to design and develop a security model for trading with cloud services, we identify in this paper concepts, mechanism and available tools that can support establishing of security-aware cloud markets. Furthermore, we introduce our information security governance driven cloud brokerage model with security labeling of tradable cloud products that can be the next step in the standardization process of tradable cloud products and optimize the selection of collaborative cloud partners.

In collaborative digital learning scenarios with small groups (3-6 users), the role of the instructor is vital as he/she is responsible for preparation of the setting, observation, coaching, moderation and adaptation. Currently, in multiplayer Serious Games, the role of the instructor is only insufficiently considered. Only very few approaches for integrating or supporting instructors in collaborative multiplayer Serious Games exist today, to the best of our knowledge. In this paper, we propose a concept for integration and support of instructors in team-based collaborative 3D multiplayer Serious Games. Our approach is based on Game Mastering principles known from roleplay games. It combines those principles with concepts for collaborative learning scenarios. We applied our concept to the existing 3D multiplayer Serious Game Woodment and tested it in a vocational school with 26 players in four groups (age: m= 19.12; sd= 2.03). Results indicate that an instructor using our Game Master framework to moderate and adapt the game at runtime can have a positive effect on both the players’ learning success and perceived user experience. Moreover, a positive effect on players’ gaming behavior can be observed.

In recent times, the working society has been plagued by a work-life imbalance as a result of the added flexibility introduced by advanced information and communication technology. A technically viable approach to improve one's work-life balance is to control the communication mediums depending on the respective user contexts, and consequently help the users maintain their concentration. To achieve this, an important prerequisite is the efficient exchange of context information among the users. Therefore, this paper motivates a novel decentralized approach which facilitates context data exchange as per prevailing conditions on privacy and confidentiality. We discuss the governing criteria surrounding user contexts and draw the main design challenges with respect to the proposed system, accordingly.

The problem of selecting services from a set of functionally appropriate ones under Quality of Service constraints - the Service Selection Problem - is well-recognized in the literature based on deterministic parameters. However, Quality of Service may rather follow a stochastic distribution and, thus, may change at runtime. In order to cope with differing Quality of Service, we present a heuristic approach for efficiently addressing the Service Selection Problem in conjunction with stochastic Quality of Service attributes. Accounting for penalty cost which accrue due to Quality of Service violations, our approach reduces the impact of stochastic Quality of Service behavior on total cost significantly.

Monitoring in mobile ad hoc networks (MANETs) constitutes a crucial service, as it enables the adaptation to the changing conditions in those networks based on the monitored state. Many monitoring mechanisms rely on a hierarchical structure, which must be maintained and suffers from sparsely populated networks, where the hierarchy might not be correctly established. Contrary to this structured design, other mechanisms rely on a simple, flat topology using gossiping to aggregate information. However, current gossip-based approaches provide inaccurate results, since they cannot handle the characteristics of MANETs. To overcome these problems and to exploit the flat topology and the robust communication pattern of gossiping for the monitoring of MANETs, this paper introduces Mobi-G. Mobi- G is a flat approach that gossips to exchange information instead of gossiping to aggregate them. It consists of a flexible protocol that exploits the characteristics of wireless communication, handles the mobility of nodes, and operates even in sparsely populated networks to provide accurate results at minimum cost.

The rising number of mobile devices and their increasing computational capabilities enable new interactive context-sensitive applications. Popular examples are augmented reality games such as Google's Ingress, where users interact with each other in the real world while being part of the game at the same time. This local interaction pattern in the real world as well as in the game is not reflected in the underlying communication pattern. Every locally generated game event is first transferred to a backend server via a cellular connection, from where it is then further disseminated to all players within the given area of interest. This communiation pattern introduces significant delays and limits the interactivity of the game. In this work, we propose an event dissemination system that exploits the locality characteristics of mobile augmented reality games to (i) enable and configure local peer-to-peer dissemination of events when appropriate and (ii) reconfigure or replace the utilized peer-to-peer protocol to adapt to a wide range of requirements. Through extensive evaluation we show that the proposed system decreases the delivery delay by a factor of eight compared to the existing communication pattern, leading to significantly increased information accuracy.

Dear TOMM

Cloud computing is increasingly used to deliver multimedia services with stringent Quality of Service (QoS) requirements, rather than simple infrastructure. Due to these requirements, the QoS-aware, cost-efficient selection of data centers arises as a new research challenge. In our ongoing work, we examine the corresponding Cloud Data Center Selection Problem and propose an exact optimization approach. A brief evaluation indicates that the proposed approach is primarily suited for small problem instances due to its high computational complexity, and hence highlights the need for the development of heuristic optimization approaches.

While cloud computing permits access to a large pool of experimental infrastructure, the most common form - virtual machines - has been shown to exhibit substantial deficits with respect to the accuracy of time measurements. In our ongoing work, we provide a detailed analysis of these deficits based on various machine configurations. Preliminary results indicate that not the use of virtualization as such, but the potentially uncontrollable utilization of the physical host is a decisive factor for the accuracy of time measurements.

Determining the energy consumption in large-scale overlay simulations is still an open issue as most existing simulation frameworks are agnostic to that aspect. Especially simulations including mobile devices, such as smartphones or tablet PCs, can benefit from having a energy consumption model in simulations such that newly developed large-scale overlay mechanisms can be evaluated with respect to their energy consumption on mobile devices. Therefore, this paper proposes a component-based energy consumption model, which is based on measurements of existing smartphones. The model causes little computational overhead, thus, being suitable for large-scale simulations. A brief evaluation shows that using our model, the energy consumption can be estimated with a mean error of ±4.7%. Furthermore, the measurements conducted to derive the model show that WiFi and Bluetooth communication are one, respectively two, orders of magnitude more energy efficient than cellular communication.

Mobile ad hoc networks (MANETs) represent a crucial alternative to deploy applications in urban areas. In those networks, it is inevitable that all nodes are aware of the current system state to adapt their behavior according to the varying conditions. However, existing decentralized monitoring solutions for MANETs only locate the required information at a set of nodes, which are in charge of serving the remaining network, while the availability of information depends on the accessibility of those nodes. To avoid these limitations, BlockTree is a novel, fully decentralized monitoring approach for MANETs that leverages each node's resources to capture and distribute the system state to all nodes. Exploiting its hierarchical structure, BlockTree introduces the concept of location-aware monitoring delivering detailed as well as aggregated information. Through robust communication paired with the stateless design, BlockTree provides accurate results in the presence of fast moving nodes or over an error-prone communication medium.

Energy constitutes a scarce resource in wireless sensor networks, making energy-efficient operation mandatory. Data transmission has been identified as one of the most energy consuming operations. Consequently, different approaches to reduce data transmissions have been proposed, like data filtering. Recently, the value of information of sensor data has been identified for data filtering, explicitly incorporating application-specific and context-dependent information needs. The filtering is done according to the benefit a data transmission would induce at the recipient. We propose an on-mote filtering approach, which relies on local multi-step assessment of sensor data with forecasting and assessing value of information. We apply our approach to logistics transport processes and evaluate it concerning number of data transmissions and energy efficiency. Our simulation results showed that with our approach the number of data transmissions and the energy consumption can be reduced by over 25% to over 60%, while simultaneously accounting for user-specific information desires.

Digital Games which incorporate movements of the player`s body in their gameplay are becoming more and more popular. An increasing number of doctors and physical therapists use such games for training exercises, although these games are not designed to achieve predefined training goals. Various studies show that the training effects of these games are small in comparison with classic exercises. Therapists request more accessible and more flexible games. In this paper we present an adaptive game for fall prevention based on the adaptation and exergame analysis framework StoryTecRT which allows the adaptation of parameters which impact accessibility, acceptance and training load of a game. This paper includes an insight into the framework and the implementation as well as first evaluation results.

Location-based services have become increasingly popular in the recent years due to the vast deployment of position-aware devices such as smartphones and tablet PCs and the ubiquitous availability of fast Internet connectivity. Existing location-based services are realized as cloud services, which cause considerably high costs. Furthermore, they are not location-aware leading to unnecessary long transmission paths between the users and the cloud infrastructure. The concept of Peer-to-Peer has proven to be a valid alternative for realizing the functionality of location-based services, which resulted in a plethora of approaches for location-based search [1], [4], [5]. Existing concepts, however, suffer from two major drawbacks: (i) they are not robust against high peer churn and (ii) they do not allow for the persistent storage of location-based data. To this end, in this demo we present the prototype of the overlay Geodemlia [3], which allows for both: the persistent storage of location-based information as well as the reliable search even under high churn rates. Location-based information in Geodemlia is stored in a location-aware way, reducing the length of the transmission path for store and search operations.

Existing peer-to-peer (p2p) overlays for location-based services suffer from two major drawbacks: (i) they do not store data persistently under peer churn and (ii) they do not allow for the fast retrieval of large files, especially under asymmetric link conditions. This tremendously limits the use of current and future p2p location-based services as users are not able to share larger files such as high resolution pictures or video snippets. To overcome these two problems, we present GeoSwarm: a reliable multi-source download scheme for p2p location-based services. GeoSwarm combines the strengths of a BitTorrent-like download scheme with the locality awareness of an overlay for location-based search and its built-in replication mechanism. Thereby, a robust and fast download as well as a reliable storage of location-related multimedia content is achieved. Through extensive evaluation, we show that 95% of all downloads in GeoSwarm are carried out successfully even under churn, while downloads benefit from a 100% increased throughput in comparison to traditional single-source downloads.

The evolution of multimedia applications has drastically changed human life and behaviors. New communication technologies lead to new requirements for multimedia synchronization. This article presents a historical view of temporal synchronization studies focusing on continuous multimedia. We demonstrate how the development of multimedia systems has created new challenges for synchronization technologies. We conclude with a new application-dependent, multilocation, multirequirement synchronization framework to address these new challenges.

No abstract available.

Auctioning constitutes a market-driven scheme for the allocation of cloud-based computing capacities. It is practically applied today in the context of Infrastructure as a Service offers, specifically, virtual machines. However, the maximization of auction profits poses a challenging task for the cloud provider, because it involves the concurrent determination of equilibrium prices and distribution of virtual machine instances to the underlying physical hosts in the data center. In the work at hand, we propose an optimal approach, based on linear programming, as well as a heuristic approach to tackle this Equilibrium Price Auction Allocation Problem (EPAAP). Through an evaluation based on realistic data, we show the practical applicability and benefits of our contributions. Specifically, we find that the heuristic approach reduces the average computation time to solve an EPAAP by more than 99.9%, but still maintains a favorable average solution quality of 96.7% in terms of cloud provider profit, compared to the optimal approach.

Bridging the gap between diagnosis and learning in the classroom is the focus of our software tool PEDALE. It allows the usage of open-format questions, knowledge sharing and peer review of other students' solutions through the exchange of hand-written notes. A pilot study with teacher educators proved the potential for diagnostic support for teachers and at the same time promoting adaptive individual learning and exchange among students. The results indicate crucial design issues and future improvements, as well as the requirement of a teacher panel, providing a supervision of the learning scenario.

The challenge of optimally selecting services from a set of functionally appropriate ones under Quality of Service (QoS) constraints -- the Service Selection Problem -- has been extensively addressed in the literature based on deterministic parameters. In practice, however, Quality of Service QoS parameters rather follow a stochastic distribution. In the work at hand, we present an integrated approach which addresses the Service Selection Problem for complex workflows in conjunction with stochastic Quality of Service parameters. Accounting for penalty cost which accrue due to Quality of Service violations, our approach reduces the impact of stochastic QoS behavior on total cost significantly.

IEEE 802.11s is an emerging standard for wireless mesh networks. Networks based on IEEE 802.11s directly benefit from existing security mechanisms in IEEE 802.11. This limits the attack surface of IEEE 802.11s significantly for adversaries that cannot authenticate with the network. Mesh networks are, however, often conceived for community network scenarios, which are inherently more open than managed infrastructure networks. This openness entails an increased risk of insider attacks, i.e., attacks by compromised stations that can authenticate with the network. Currently, IEEE 802.11s is lacking adequate protection against such insider attacks. In this paper, we hence derive an attack model for insider attacks and present two insider attack strategies to which IEEE 802.11s networks are prone, namely impairing the network performance and preventing communication between a pair of nodes. We design countermeasures that allow to defend the wireless network against both types of attacks. Our implementations only incur marginal computational and memory overheads, while the network security is measurably strengthened.

Energy-efficient operation is mandatory in wireless sensor networks due to the limited energy budget of sensor nodes. Considering the potential application of wireless sensor networks in logistics, cost efficiency is another major requirement due to high cost pressure. To save on data transmissions within such sensor deployments, which account for the major part of energy consumption and monetary costs, we develop a method for data filtering based on an in-network determination of transmission relevance of sensor data. Our approach explicitly incorporates interdependencies between wireless sensor nodes and their measurements and data transmissions. It contributes to efficiency in wireless sensor networks by filtering out irrelevant data and enables a subsequent reduction of unnecessary transmissions from a network-wide view, while being able to still offer real-time data provision with sufficient data fidelity to stakeholders. The benefits of our approach are indicated by preliminary evaluation results.

Existing peer-to-peer overlay approaches for location-based search have proven to be a valid alternative to client-server-based schemes. One of the key issues of the peer-to-peer approach is the high churn rate caused by joining and leaving peers. To address this problem, this paper proposes a new location-aware peer-to-peer overlay termed Geodemlia to achieve a robust and efficient location-based search. To evaluate Geodemlia, a real world workload model for peer-to-peer location-based services is derived from traces of Twitter. Using the workload model, a system parameter analysis of Geodemlia is conducted with the goal of finding a suitable parameter configuration. In addition, the scalability and robustness of Geodemlia is compared to a state-of-the-art tree-based approach by investigating the performance and costs of both overlays under an increasing number of peers, an increasing radius of area searches, an increasing level of churn as well as for different peer placement and search request schemes. The evaluation results reveal that in contrast to the tree-based approach, Geodemlia provides on average a 46% better success ratio as well as a 18% better recall at a moderate higher traffic overhead of 13 bytes/s and an increased average response time of 0.2 s.

Decentralized monitoring mechanisms enable obtaining a global view on different attributes and the state of Peer-to-Peer systems. Therefore, such mechanisms are essential for managing and optimizing Peer-to-Peer systems. Nonetheless, when deciding on an appropriate mechanism, system designers are faced with a major challenge. Comparing different existing monitoring mechanisms is complex because evaluation methodologies differ widely. To overcome this challenge and to achieve a fair evaluation and comparison, we present a set of dedicated benchmarks for monitoring mechanisms. These benchmarks evaluate relevant functional and non-functional requirements of monitoring mechanisms using appropriate workloads and metrics. We demonstrate the feasibility and expressiveness of our benchmarks by evaluating and comparing three different monitoring mechanisms and highlighting their performance and overhead.

In tree-structured data collection sensor networks, packets are routed towards a sink node by iteratively choosing a node's immediate parent node as the next hop. It is however beyond the scope of these routing protocols to transfer messages along the reverse path, i.e., from the sink to individual nodes in the network. In this paper, we present CBFR, a novel routing scheme that builds upon collection protocols to enable efficient point-to-point communication. We propose the use of space-efficient data structures known as Bloom filters to efficiently store routing tables on the networked devices. In particular, each node in the collection tree stores the addresses of its direct and indirect child nodes in its local Bloom filter. A packet is forwarded down-tree only if the node's local filter indicates the presence of the packet's destination address among the node's descendants. In order to cater for the presence of mobile nodes, we apply the concept of counting Bloom filters to allow for the removal of elements from the filter by means of gradual forgetting. The effectiveness of our approach in achieving both high delivery rates and low overhead is demonstrated by means of simulations and experiments.

No abstract available.

No abstract available.

No abstract available.

The phenomenon of online social networks reaches millions of users in the Internet nowadays. In these, users present themselves, their interests and their social links which they use to interact with other users. We present in this paper LifeSocial.KOM, a p2p-based platform for secure online social networks which provides the functionality of common online social networks in a totally distributed and secure manner. It is plugin-based, thus extendible in its functionality, providing secure communication and access-controlled storage as well as monitored quality of service, addressing the needs of both, users and system providers. The platform operates solely on the resources of the users, eliminating the concentration of crucial operational costs for one provider. In a testbed evaluation, we show the feasibility of the approach and point out the potential of the p2p paradigm in the field of online social networks.

Contrary to simple Web content, standard Web services do not offer their clients the possibility to use cached information without the risk that it may be out-of-date. This feature has not been worth its costs in realistic Web service usage scenarios until now. However, its absence may pose restrictions and impede possible benefits in a future scenario, where mediators are both willing and able to effectively minimize the amount of wirelessly transmitted data in the Internet of Services. This paper describes how developments in the Internet of Services start to motivate the automatic enablement of safe (i.e., always up-to-date) client-side caching for Web services. It presents our solution for generically adding this feature to any Web service, and, based on new experiments, reveals the limits beyond which the approach can offer significant benefits.

Research in learning and competence development shows the benefits of peer support and access to peers' solutions for learning and understanding. We propose a concept for task-focused knowledge exchange in a learner network using a digital learning environment that supports creation of ad-hoc (sub)communities by matching learning opportunities. Structural results from Social Network Analysis (SNA) are incorporated in the derived models of community-based learning in (sub)communities. The approach, research questions and the planned evaluation setup are described.

Most current smart metering solutions aim at in creasing user awareness for their household's electrical energy consumption. Although some smart meters make use of wireless data transfers between their sensor and display units, their integration into existing wireless sensor networks is hampered by proprietary communication interfaces and their lack of re programmability. Furthermore, the sole availability of aggregate consumption values renders current meters insufficient for novel application scenarios like smart home automation, for which information at device-level granularity and high resolution is vital. We address these shortcomings of existing solutions by presenting SmartMeter.KOM, our wireless sensor node capable of determining the current consumption of individual electrical appliances at high resolution. The platform is based on low-power hardware and incorporates a reprogrammable microcontroller which allows developers to easily deploy new algorithms. Its IEEE 802.15.4-compliant radio transceiver makes its integration with existing sensor networks possible, and thus enables their integration in smart buildings. We demonstrate the versatility of SmartMeter.KOM by presenting prototypical implementations of smart applications and identifying further research directions.

As wireless sensor nodes are mostly battery- powered, energy-efficient operation is a necessity to use their confined energy budget optimally. This is especially true in the logistics domain, where timely and accurate monitoring of containers is required, while the cost pressure is high. Thus, besides the need for energy efficiency, wireless sensor network deployments in logistics require cost efficiency as well. As data transmission represents the most expensive operation in terms of energy consumption and monetary costs, we present a concept for the local determination of transmission relevance in this paper. By omitting irrelevant events from transmission, the amount of data to transmit is effectively reduced. Our approach employs concepts from the business economics sector and is based on the use of scoresheets, which evaluate information on a wireless sensor node to decide whether they are "worth" transmitting or not. Thus, a scoresheet-based approach provides a viable solution for local filtering to realize energy-and cost-efficient operation of a wireless sensor network while maintaining the benefits of data fidelity and real-time event notifications.

The lookup mechanism used to locate services in Peer-to-Peer systems can be attacked with little effort due to its decentralized and self-organizing nature. Security mechanisms aiming at rendering the lookup mechanism more robust mostly require a high amount of network resources. These mechanisms cannot be applied without adaptations when network resources are limited. In this paper, we introduce a novel approach to increase lookup robustness in mobile Peer-to-Peer networks. Here, network resources are limited by the mobile ad hoc network that is used as communication substrate. Our approach harnesses cross-layer information provided from the mobile ad hoc underlay to the Peer-to-Peer overlay. We derive analytical models to compare our approach to existing security mechanisms and validate our results by means of simulation. Our core findings how that our approach consumes less resources than existing mechanisms while the robustness remains at a comparable level.

The efficient production of Serious Games typically requires the collaboration of technical and game development experts, i.e. game developers and domain experts such as pedagogues or sports experts. For the use case of exergames with educational aspects, we demonstrate how an authoring tool for Serious Games can be specialized for collaborative authoring by defining roles of users and providing different views on the created game to each user group carrying out different tasks in the production of the game.

P2P Video-on-Demand (VoD) based on Scalable Video Coding (SVC) (the scalable extension of the H.264/AVC standard) is gaining momentum in the research community, as it provides elegant adaptation to heterogeneous resources and network dynamics. The major question is, how do the adaptation algorithms and designs affect the overall perceived performance of the system? Better yet, how can the performance of an SVC-based VoD system be defined? This paper explores the impact and trade-offs of SVC-based quality adaptation with focus on the SVC layer selection algorithms, which are performed at different streaming stages. We carry out extensive experiments to evaluate the performance in terms of session quality (start-up delay, video stalls) and delivered SVC video quality (layer switches, received layers), and find out that these two metrics exhibit a trade-off. Our analysis and conclusions give multimedia providers insights on how to design and fine-tune their VoD system in order to achieve best performance.

There are currently two concurrent trends in the Internet. First, the number of Internet users and their connection speeds are increasing rapidly. Second, Internet-based applications are dominating how people receive information, communicate, and entertain themselves. Therefore, we are witnessing an enormous increase in IP-based multimedia traffic, which is putting an enormous strain on the network. Additionally, router and network virtualization are gaining importance, enabling more intelligent networks. Therefore, we argue that networks should not be merely bystanders to this multimedia revolution. In this paper we present a media-aware network solution based on router virtualization that aims at striking a balance between intelligence and adaptation at the edge and in the core of the network. Using an extensive simulative study, we demonstrate that our media-aware network not only helps in enhancing streaming performance during bottlenecks, but also minimizes the side effects of congestions on user perceived quality, making it a need for future Internet multimedia applications.

Peer-to-peer overlays for Networked Virtual Environments have recently gained much research interest, resulting in a variety of different approaches for spatial information dissemination. Although designed for the same purpose, the evaluation methodologies used by particular authors differ widely. This makes any comparison of existing systems difficult, if not impossible. To overcome this problem we present a benchmarking methodology which allows for a fair comparison of those systems. We, therefore, define a common set of workloads and metrics. We demonstrate the feasibility of our approach by testing four typical systems for spatial information dissemination and discovering their specific performance profiles.

This article investigates a scenario of reuse in which existing learning resources serve as preliminary products for the creation of new learning resources. Authors should be able to reuse learning resources and also parts of them at different levels of granularity in a modular way. The requirements of multigranularity reuse are analyzed and compared to existing solutions. A concept for modular, multigranularity reuse is presented in this article. It is also shown how this kind of reuse can be achieved in practise.

No abstract available.

Abstract The class of Wireless Mesh Networks (WMN) supports an ample set of applications including wireless community networks, radio access networks in rural or metropolitan areas, or wireless backbones for factory/process automation. Guaranteeing security is crucial for within these application scenarios. While contemporary wireless technologies, such as the IEEE 802.16 or the IEEE 802.11s standard, provide the basic protocol mechanisms for mesh networking, they lack in comprehensive security mechanisms. Additionally, novel security features of the above standards such as per‐link encryption break existing security solutions that rely on overhearing of the wireless channel. We close this gap by developing a holistic approach toward securing WMNs with particular focus on the network layer. We perform a threat analysis and then develop solutions (1) guaranteeing the integrity and authenticity of routing messages, (2) to locally and globally detect misbehavior of nodes in forwarding data or routing messages even for settings that do not allow for overhearing the channel, and (3) to dynamically manage reputation of nodes throughout the network. The combination of these building blocks enables to provide for secure, self‐organizing WMNs. As a proof‐of‐concept, we tailor and implement our solutions for the setting of a realistic IEEE 802.16 mesh network; we discuss the protection achieved and assess selected performance trade‐offs for the developed mechanisms. Copyright © 2010 John Wiley & Sons, Ltd.

Abstract The IEEE 802.16 standard (WiMAX) specifies a MeSH mode which permits the deployment of Wireless Mesh Networks (WMNs) supporting carrier‐grade QoS. The network operator for such planned WMNs is interested in maximizing the traffic admitted in the WMN and simultaneously supporting QoS. Recently network coding has emerged as a promising technique for increasing the throughput in WMNs. This paper proposes CORE, which addresses the problem of jointly optimizing the routing, scheduling, and bandwidth savings via network coding. Prior solutions are either not applicable in the 802.16 MeSH mode or computationally too costly to be of practical use in the WMN under realistic scenarios. CORE's heuristics, in contrast, are able to compute solutions for the above problem within a operator definable maximum computational cost, thereby enabling the computation and near real‐time deployment of the computed solutions. We analyze the performance of CORE's heuristics via a thorough simulation study covering the typical usage scenarios for WMNs. The results presented demonstrate that CORE is able to increase the number of flows admitted considerably and with minimal computational costs. We also see that CORE successfully increases the number of network coding sessions which can be established in the WMN. Further, the results provide insights into limiting factors for the gains which can be obtained in different typical usage scenarios for WMNs. Copyright © 2010 John Wiley & Sons, Ltd.

Understanding and discussing the security aspects of IT systems during their development is challenging for both domain specialists and IT experts - neglecting this aspect leads to communication problems and, eventually, to less secure systems. An important factor for these challenges is the distribution and variety of basic IT security concepts, attacks, and countermeasures, e.g., in the standard literature. In this paper, we propose a generic metamodel for IT security capturing both its major concepts and their relationships to each other. With a focus on attacks, we show how this model is applied to different scenarios in distributed systems, i.e., Peer-to-Peer systems, Service-oriented Architectures, and Mobile ad hoc Networks. This allows for a better understanding of IT security in general and attacks in particular, thus, enabling effective communication between different parties during the development of security-critical IT systems.

The area of context-aware computing has received much attention in the last decade. However, many systems to determine a user’s context are focused on integrating a confined set of sensors into their decision-making algorithms, and lack extensibility for new and novel sources of context information. This limitation however has often resulted in monolithic software systems, reasoning on the user’s context from a static set of pre- defined rules. Therefore, most of these systems can not adapt to the user during runtime, and have not found wide adoption in reality. Unlike the existing approaches, we present a concept for a context-aware system circumventing these limitations by providing generic abstraction layers among its components. We show a concept for an extensible context-aware system with autonomous adaptation to changes in the user’s preferences, and provide arguments for our design decisions. After presenting the constraints for all participating entities, including sensors, middleware, and actuation and/or application frontends, we describe ContextFramework. KOM, an example implementation of the proposed concept.

Energy consumption is responsible for a large fraction of costs in today's content distribution networks. In upcoming decentralized architectures based on set-top boxes (STB), acting as tiny servers, idle times can dominate distribution costs, since no cooling costs occurs and the Internet access is often paid in a flat-rate manner. The often assumed always-on property of STBs provides high availability but might also waste up to 93% of the baseline energy. In this paper we consider suitable standby policies that reduce energy consumption but still allow offloading content servers significantly. We devise optimal and heuristic standby policies and evaluate them in a realistic scenario to show that a near-optimal behavior can be reached by utilizing the specific features of STBs.

BitTorrent has become the de-facto standard for peer-to-peer content delivery, however, it has been found that it suffers from one fundamental problem: the long-term availability of content. Previous work has attributed this to what is termed the seeder promotion problem in which peers refuse to continue serving content after their own download has completed. As of yet, no deployed solution exists to this problem. In this paper, we objectively investigate the solution space for dealing with the seeder promotion problem. Specifically, both single-torrent and cross-torrent approaches are investigated to ascertain which is superior based on three key metrics: availability, performance, and fairness. To achieve this, two large-scale BitTorrent measurement studies have been performed which include 46K torrents and 29M users. Through these, we first quantify the seriousness of the seeder promotion problem before exploiting the data logs to execute accurate trace-based simulations for the different solutions considered. Using the results, we ascertain and describe the different trade-offs between the four general solutions: extending seeding times, cross-torrent bartering, local persistent histories, and global shared histories. We find that single-torrent solutions are profoundly impractical when considering the user behaviour observed in our studies. In contrast, we discover that the different cross-torrent approaches can offer a far more effective solution for satisfying (to varying degrees) the need for high availability, good performance, and fairness between users.

Personal knowledge acquisition in a world where people have to acquire knowledge for task completion on the job constantly is done increasingly based on Web resources. Web resources ranging from mainly text based forms like Wikis up to multimedia resource like videos document knowledge and can be used for knowledge acquisition. Due to the participation of communities in creating content in Web 2.0 applications the mass of available resources increases steadily. Searching for high quality and reliable resources using a search engine becomes impossible. Thus, recommending relevant resources becomes more and more important. For this learning scenario, we present and compare different approaches for recommendation of multimedia resources we integrated in an application for collaborative management of Web resources for learning purposes, called CROKODIL.

The peer-to-peer paradigm shows the potential to provide the same functionality and quality like client/server based systems, but with much lower costs. However, the resources, e.g. storage space, CPU power and online time, provided by the peers are unreliable due to churn. In order to enable churn resistant reliable services using the resources in p2p systems, we propose in this paper a distributed mechanism termed P3R3O.KOM. The mechanism allows to reserve, monitor and use resources provided by the unreliable p2p system and maintains long-term resource reservations through controlled redundant resource provision. Evaluation shows that using KAD measurements on the prediction of the lifetime of peers allows for 100% successful reservations under churn with very low traffic overhead. This approach marks a first step for the building of a reliable p2p-based SOA and future p2p-based clouds.

Simulation has become an important evaluation method in the area of Peer-to-Peer (P2P) research due to the scalability limitations of evaluation test beds such as Planet Lab or G-Lab. Current simulators provide various abstraction levels for different underlay models, such that applications can be evaluated at different granularity. However, existing simulators suffer from a lack of interoperability and portability making the comparison of research results extremely difficult. To overcome this problem, we present an approach for a generic application interface for discrete-event P2P overlay network simulators. It enables porting of the same implementation of a targeted application once and then running it on various simulators as well as in a real network environment, thereby enabling a diverse and extensive evaluation. We established the feasibility of our approach and showed negligible memory and runtime overhead.

Securing the routing service of Mobile Ad-hoc Networks (MANET) is a basic requirement for application scenarios such as emergency response operations. In this paper we analyze the effects of routing attacks on the Ad-hoc On-demand Distance Vector (AODV) protocol. We present results of a testbed-based analysis to consider real-world characteristics of hardware as well as wireless communications. As AODV is shown to produce unstable multi-hop routes, we design and implement a mechanism to address this issue. We then present an evaluation of three selected types of malicious behavior. Our results show that our protocol-variant delivers a reliable ad-hoc routing service. Yet, it is strongly affected by routing attacks.

Nodes in wireless sensor networks are generally confined in the energy budget available for their operation, hence energy-aware application design is mandatory to achieve long node lifetimes. Radio transmissions represent an inherent, but energetically costly characteristic of sensor networking. Significant reductions in the overall energy consumption can thus be achieved by reducing both the number of packet transmissions as well as the corresponding packet lengths. Data compression is a viable approach to conserve energy by increasing the information density within packets and thus transmitting shorter packets on the radio. We investigate the compression of packet headers in wireless sensor networks in this paper. Inspired by technologies used in the Internet and characteristics stemming from existing sensor network deployments, we propose a novel scheme for stateful header compression. Our scheme is specifically designed to consider both static and mobile leaf nodes, and can thus be applied in a majority of sensor network deployments. We analyze our scheme in different settings and show that its application leads to reductions of the required transmission energy and thus extended node lifetimes.

Recently, there has been much interest in positioning based on the widespreading WLAN technology, notably observed in the increasing number of hotspots and mobile devices equipped with WLAN interface. One technique to use WLAN for positioning is location fingerprinting, where WLAN networks in preselected sample locations are collected and used as fingerprints for those locations. However, to collect such fingerprints, existing services typically need to employ many skilled wardrivers who scan networks in the streets. This approach turns out to be very costly, especially when a large scale system coverage with acceptable positioning accuracy is required. Therefore, we propose WBroximity as a novel solution for the aforementioned concerns. With WBroximity, not only WLAN but also Bluetooth fingerprints are collected, therefore benefitting from the short range of Bluetooth to enable more precise positioning. Furthermore, such hybrid fingerprints are collected by using the paradigm of participatory sensing, thus cutting the extra costs needed to employ special personnel for this task, and allowing the system coverage to expand to wherever participants reach. In this paper, we present the technical details of realizing WBroximity as a location provider and its usage for collecting real fingerprint datasets. We evaluate the achieved accuracy in light of combining WLAN and Bluetooth, and the inherent aspects of participatory sensing, like number of participants and quality of participation. We give also an initial design and evaluation of a countermeasure to mitigate the effects of malicious participation.

Energy is limited in wireless sensor networks due to mostly battery-operated wireless sensor nodes. Consequently, an efficient energy usage significantly enhances the lifetime of a wireless sensor network. In this paper, we propose a cross-layer optimization concept that exploits business knowledge in the logistics domain to adapt communication by business relevancy. A corresponding information value is assessed for each detected event. Energy and communication costs can be saved by dropping or postponing the transmission of less relevant event information, without negative impact on the business and application level.

In this paper, we describe a set of personalized exergames which combine methods and concepts of serious games, adaptation and personalization, authoring and sensor technologies. Compared to existing systems, the set of games does not only keep track of the user's vital state, but also directly integrates vital parameters into the gameplay and supports the training and motivation for sustainable physical activity in a playful manner.

Available objective Quality of Experience (QoE) assessment methods for speech and audio quality evaluation are not directly usable for quality rating of professional broadband audio communication applications over IP such as audio contribution links for broadcasting. To fill this gap, we designed a dedicated non-intrusive parametric QoE model for conversational quality rating based on the E-model approach. With this the QoE of Audio Contribution over IP (ACIP) can be monitored. Moreover, the estimated QoE scores can be used for a perceptually-driven Quality of Service (QoS) optimization for ACIP, which has different requirements and characteristics compared to Voice over IP (VoIP). In this paper, we present our ACIP QoE model and propose an objective QoE metric for assessing the listening-only quality in ACIP. The latter is used by us for intrusive QoE evaluations, which are necessary for the derivation of a parametric QoE model. Our experimental methodology is illustrated in depth and we give exemplified results. Finally, we demonstrate the application of our model in perceptually-driven QoS optimization.

P2P streaming has attracted much attention recently with promises for higher revenues and better load distribution. Still, the majority of P2P video streaming systems today employ the one-size-fits-all concept where the same video bit-rate is offered to all users. Here the promising H.264/Scalable Video Coding (SVC) standard is seen as a necessity in not only supporting heterogeneous resources, but also in reducing the impact of P2P dynamics on the perceived Quality-of-Experience (QoE). In this demonstration we present our streaming application that uses SVC to adapt to different user requirements and resources. The application employs a novel QoE- aware layer selection algorithm that maximizes flexibility through SVC while taking impact on QoE into consideration.

Online social networks with millions of users are very popular nowadays. They provide a platform for the users to present themselves and to interact with each other. In this paper, we present a totally distributed platform for social online networks based on the p2p paradigm, called LifeSocial.KOM. It provides the same functionality as common online social networks, while distributing the operational load on all participating nodes. LifeSocial.KOM is plugin-based and extendible, provides secure communication and user-based data access control and integrates a monitoring component which allows the users and operators to observe the quality of the distributed system.

BitTorrent suffers from one fundamental problem: the long-term availability of content. This occurs on a massive-scale with 38% of torrents becoming unavailable within the first month. In this paper we explore this problem by performing two large-scale measurement studies including 46K torrents and 29M users. The studies go significantly beyond any previous work by combining per-node, per-torrent and system-wide observations to ascertain the causes, characteristics and repercussions of file unavailability. The study confirms the conclusion from previous works that seeders have a significant impact on both performance and availability. However, we also present some crucial new findings: (i) the presence of seeders is not the sole factor involved in file availability, (ii) 23.5% of nodes that operate in seedless torrents can finish their downloads, and (iii) BitTorrent availability is discontinuous, operating in cycles of temporary unavailability.

Mobile Web services lie on the intersection of two big IT trends, namely Service-oriented Architectures (SOA) and mobile applications. So, their usage is likely to expand dramatically in the next years. However, the heavyweight nature of service-orientation in terms of the messaging-overhead that is necessary in order to achieve interoperability and loose-coupling comes in contrast with the lightweight nature of mobile devices and with the need to transmit wirelessly as few data as possible. This study categorizes the mechanisms that have been designed in order to bridge this gap, provides comparisons, discusses the results of related experiments, and introduces the future scenario in which the insights of the study can be exploited.

In recent years, a number of approaches to semantic Web service matchmaking have been proposed. Most of these proposals are based on discrete and thus relatively coarse Degrees of Match (DoMs). However, different basic assumptions regarding the generalization and specialization of semantic concepts in ontologies and their subsequent rating in matchmaking exist. Hence, most matchmakers are only properly suitable if these assumptions are met. In this paper, we present an approach for mapping subsumption reasoning-based DoMs to a continuous scale. Instead of determining the numerical equivalents of the formerly discrete DoMs manually, these values are automatically derived using a linear regression model. This permits not only easy combination with other numerical similarity measures, but also allows to adapt matchmaking to different basic assumptions. These notions are implemented and tested in LOG4SWS.KOM-a matchmaker for SAWSDL that provides very good evaluation results with respect to Information Retrieval metrics such as precision and recall.

P2P Streaming has attracted much attention recently with promises for more revenues and better load distribution. In parallel, social networking has changed how people interact using the web. One interesting use-case for next generation IPTV is Social TV. In such a system, users are able to watch some media stream and interact with each other at the same time. While deploying P2P Social TV, one inherent problem in P2P streaming systems remains, how to incite users to contribute. In this demonstration we show how social networks can be used to build new incentive mechanisms. Rather than making social relations a mere addition, we build our streaming system on top of a user's social network. This design greatly simplifies the system and requires no further entities for management. In this demonstration we present the first version of StreamSocial that, based on a plug-in based design, allows users to stream videos while performing social interactions.

No abstract available.

A recommender system can be used to suggest users potentially interesting content based on their previous consumption behavior. Such services already became common in centralized systems, such as Amazon, and approaches exist for decentralized recommender systems. However, common P2P recommender systems expose the userpsilas preferences in the whole system. This is not desirable if privacy is required.Realization of a recommender system in a private P2P environment is not a trivial task, since we cannot gather the user data at central servers or just spread them in the community. In this work we propose a private file sharing application based on social contacts. Instead of gathering all the information about users at one place the users exchange information only with their social contacts. We show how a personalized recommender system can be built in such an environment.

We present an analytical model combining geometric and stochastic approaches to describe the effects of attacks and countermeasures on MANETs. In particular, we focus on the packet loss that can be charged to the misbehavior as well as to the countermeasures as a primary metric. For this, we model the entire chain of (1) MANET routing, (2) attack, (3) intrusion detection, and (4) intrusion response. We validate the models proposed by means of simulation.

Central trusted instances as well as predefined security policies are not available in spontaneously established peer-to-peer environments. The former can be addressed by joint decision processes based on threshold cryptography. To compensate the latter, users can be involved directly in security- relevant decisions. In this case, minimizing the number of users involved is a necessary optimization goal to keep user-based joint decisions feasible for real-world deployment. Still, a certain redundancy has to be introduced when taking into account users that do not provide their decision in a reasonable amount of time. In this paper we scrutinize different interaction schemes for joint decision processes. We develop stochastic models that describe the outcome subject to the number of users requested and the probability with which one user provides his decision in time. The derived closed-form representation of the models serves as a tool for governing the decision process, allowing for a real-time minimization of the number of users involved.

Pricing of services, especially in a SOA and grid environment with contractual relationships gain importance in recent years. For the resource planning, i.e. the allocation and orchestration of existing services, service pricing has a major influence. An orchestrator of services may face various pricing models from different service providers with e.g. long-term or short-term contracts, fixed or variable expenses for service invocation. Price as an important non-functional property of services lacks of a systematic investigation in this context, although it directly affects a service orchestrator's business targets. An appropriate categorization of pricing models is essential for this purpose. This paper proposes a classification of pricing models for services in a SOA environment from a resource planning perspective, i.e. for service selection. Moreover, the impact of different pricing models on service allocation, respectively selection, and further implications for an intermediary, acting as a service orchestrator, are presented.

Resource planning for service-based workflows becomes crucial considering a large amount of workflow execution requesters in a SOA or Grid environment. Especially, business process management and performance management of service-based workflows are of high importance avoiding performance degradation. The need for efficient resource planning techniques forces intermediaries, acting as workflow orchestrators, to use efficient heuristics for the determination of service invocation plans for workflows at short computation times. This paper presents an optimization approach for the resource planning problem and proposes an efficient heuristical solution solving the addressed optimization problem at a high solution quality and at a short computation time.

Peer-to-peer (P2P) applications have recently attracted a large number of Internet users. Traditional P2P systems however, suffer from inefficiency due to lack of information from the underlay, i.e. the physical network. Although there is a plethora of research on underlay awareness, this aspect of P2P systems is still not clearly structured. In this paper, we provide a taxonomic survey that outlines the different steps for achieving underlay awareness. The main contribution of this paper is presenting a clear picture of what underlay awareness is and how it can be used to build next generation P2P systems. Impacts of underlay awareness and open research issues are also discussed.

The peer-to-peer paradigm is used in more and more advanced applications. One of the next areas that promise a success for the p2p paradigm lies in the upcoming trend of social networks. However, several security issues have to be solved in p2p-based social network platforms. We present in this paper a practical solution that establishes a trust infrastructure, enables authenticated and secure communication between users in the social network and provides personalized, fine grained data access control. We implemented our solution in a p2p based platform for social networks and show that the solution is practical and lightweight both in time consumption and traffic overhead.

The IEEE 802.16 standard recently introduced an additional relay mode of operation permitting coverage extension of the point-to-multipoint (PMP) based WiMAX networks. Relays can further aid in increasing the achievable data rates for subscriber stations (SS) in the network. Although bandwidth management and scheduling have been studied in some detail in traditional IEEE 802.16 PMP networks, the corresponding study for relay networks is far from complete. A trivial extension to the scheduling and bandwidth allocation algorithms used in the PMP mode for the relay networks leads to inefficient bandwidth utilization and allocation. Of particular interest here is the possibility of spatial reuse of allocated blocks of bandwidth which is permissible in relay networks. This paper investigates and designs bandwidth allocation and scheduling algorithms for IEEE 802.16 based relay networks, considering the support for spatial reuse to additionally improve the throughput while at the same time supporting quality of service (QoS). We research the issues which need to be considered when designing bandwidth allocation algorithms for relay networks. Finally, as a proof of concept we provide a thorough simulation study to investigate the performance of the designed algorithms. The results validate the design choices we presented, and also provide insights into areas for further research in WiMAX relay networks.

The IEEE 802.16 standard specifies a mesh mode of operation which permits the setup of wireless mesh networks (WMN) with per-link QoS support. The standard specifies both distributed as well as centralized reservation schemes. Distributed scheduling is highly flexible, and enables operation of the WMN even in the absence of a central controlling instance or base station. A systematic study of strategies for distributed scheduling in the IEEE 802.16 MeSH mode is, however, missing. In this paper we model the individual links in the 802.16 WMN and design and derive efficient strategies for distributed scheduling to reserve bandwidth required for transmission on the modelled link. Additionally, we evaluate our proposed reservation model using simulations, study the impact of key parameters and identify issues for further research in WiMAX based WMNs.

In wireless sensor networks, energy is commonly a scarce resource, which should be used as sparingly as possible to allow for long node lifetimes. It is therefore mandatory to put a focus on the development of energy-efficient applications. In this paper, we analyze the achievable energy gains when packet payloads are compressed prior to their transmission. As the radio transceiver chips are the predominant power consumers on most current sensor node platforms, we present how local compression of data can be successfully employed to preserve energy. We compare two lossless mechanisms to eliminate redundancies in the packets with regard to the overall energy savings. The results prove that data compression is a viable approach to reduce a platform's energy consumption, as it can reduce the radio transmission durations of packets and thus shorten the duty cycles of the radio device.

As the principle of service-orientation is gaining ground in a significant number of emerging solutions, the definition of standards coupled with the appearance of new architectures bring a new era in software development. New technologies enable the usage and composition of services in mobile environments, such as PDAs or common cell phones, thus paving the way for "mobile SOA". However, the lack of middleware and technical solutions and the limitation of SOA appliance only within enterprise systems have forced mobile SOA to remain primitive. Mobile services are being rather used with mashup techniques.

Recently, the development in the area of decentralized systems and infrastructureless networks opened avenues for novel applications. A prominent example is the support of on-site units in large scale emergency response scenarios. Here, a combination of peer-to-peer systems and mobile ad hoc networks forms a communication substrate for offering enhanced services beyond the borderlines of the 'traditional' infrastructure-based client/server world. More representatives of the decentralized/infrastructureless domain such as service oriented architectures and mesh and sensor networks also already left their starting blocks.

The peer-to-peer paradigm shows the potential to provide the same functionality and quality like client/server based systems, but with much lower costs. In order to control the quality of peer-to-peer systems, monitoring and management mechanisms need to be applied. Both tasks are challenging in large-scale networks with autonomous, unreliable nodes. In this paper we present a monitoring and management framework for structured peer-to-peer systems. It captures the live status of a peer-to-peer network in an exhaustive statistical representation. Using principles of autonomic computing, a preset system state is approached through automated system re-configuration in the case that a quality deviation is detected. Evaluation shows that the monitoring is very precise and lightweight and that preset quality goals are reached and kept automatically.

Existing approaches for modelling the Internet delay space predict end-to-end delays between two arbitrary hosts as static values. Further, they do not capture the characteristics caused by geographical constraints. Peer-to-peer (P2P) systems are, however, often very sensitive to the underlying delay characteristics of the Internet, since these characteristics directly influence system performance. This work proposes a model to predict lifelike delays between a given pair of end hosts. In addition to its low delay computation time, it has only linear memory costs which allows large scale P2P simulations to be performed. The model includes realistic delay jitter, subject to the geographical position of the sender and the receiver. Our analysis, using existing Internet measurement studies reveals that our approach seems to be an optimal tradeoff between a number of conflicting properties of existing approaches.

In wireless sensor networks, the energy consumption of participating nodes has crucial impact on the resulting network lifetime. Data compression is a viable approach towards preserving energy by reducing packet sizes and thus minimizing the activity periods of the radio transceiver. In this paper, we propose a compression framework utilizing a stream-oriented compression scheme for sensor networks. It is specifically tailored to the capabilities of employed nodes and network traffic characteristics, which we determine in a characterization of WSN traffic patterns. To mitigate the inapplicability of traditional compression approaches, we present the squeeze KOM compression layer. By shifting data compression into a dedicated layer, only minor modifications to applications are required, while efficient data transfer between nodes is provided. As a proof-of-concept, we implement a stream-based compression algorithm on sensor nodes and perform an experimental analysis to determine the potential gains under realistic traffic conditions. Results indicate that our presented lossless stream-oriented payload compression leads to considerable savings.

The term web genre denotes the type of a given web resource, in contrast to the topic of its content. In this research, we focus on recognizing the web genres blog, wiki and forum. We present a set of features that exploit the hierarchical structure of the web page's HTML mark-up and thus, in contrast to related approaches, do not depend on a linguistic analysis of the page's content. Our results show that it is possible to achieve a very good accuracy for a fully language independent detection of structured web genres.

Abstract With their wireless and infrastructureless nature, mobile ad hoc networks offer new possibilities for communication, but also new possibilities for attacks. An intrusion detection system combined with intrusion response mechanisms is a promising approach which mitigates the effects of attacks, but cannot be taken directly from wired or infrastructure‐based environments. In this paper, we propose an intrusion response mechanism for mobile ad hoc networks that excludes detected adversaries from the network based on their geographical position. To this end, we establish geographical quarantine zones, which block communication around misbehaving nodes. Thus, we depart from the assumption that attacks can be uniquely bound to addresses. Without loss of generality, we show how our approach can be used together with the AODV routing protocol to provide an intrusion response to a combination of Blackhole and Sybil attacks. In a series of simulation studies, we compare our approach with a ‘traditional’, address‐based intrusion response strategy. Copyright © 2008 John Wiley & Sons, Ltd.

Performance evaluation and execution management of service-oriented workflows became quite important in order to avoid performance degradation. Performance measurement is crucial to ensure that workflow execution remains feasible and that SLA violations due to overload are avoided. Network calculus as a well-known system theory for deterministic queuing systems can be used to describe the worst-case performance behavior of a workflow in order to plan workflow control in advance. Concerning business processes with high repetition rates the workflow controller has to be able to serve all incoming requests with an optimal composition of Web services. Thus, this paper presents a formal worst-case calculation model using the concepts of network calculus. Furthermore, optimization problems based on the worst-case scenario are introduced in order to minimize the worst-case delay and to maximize the throughput of the Web services invoked with minimal costs.

In order to ease the development and maintenance of more complex P2P applications, which combine multiple P2P functionality (e.g. streaming and dependable storage), we suggest to extend structured P2P systems with a dedicated information management layer. This layer is meant to generate statistics on the whole P2P system and to enable capacity-based peer search, which helps the individual functionality layers in the P2P application to find suitable peers for layer-specific role assignment. We present in this paper SkyEye.KOM, an information management layer applicable on DHTs, which fulfills these desired functionality. SkyEye.KOM builds an over-overlay, which is scalable by leveraging the underlying DHT, easy to deploy as simple add-on to existing DHTs and efficient as it needs O(log N) hops per query and to place peer-specific information network wide accessible. Evaluation shows that SkyEye.KOM has a good query performance and that the costs for maintaining the over-overlay are very low.

Network virtual environments (NVE) are an evolving trend combining millions of users in an interactive community. A distributed NVE platform promises to lower the administration costs and to benefit from research done in the peer-to-peer (p2p) domain. In order to reuse existing mature p2p overlays for NVEs, a comparative evaluation has to be done in the same environment (e.g. resources of peers, peer behavior, churn, etc.), using appropriate test cases (scenarios) and observing relevant performance metrics. In this paper we present a benchmarking approach for p2p overlays in the context of NVEs. We define related quality attributes, scenarios, and metrics and use them to evaluate Chord and Kademlia as most popular p2p overlays and assess their suitability to NVE.

Online community platforms and multimedia content delivery are merging in recent years. Current platforms like Facebook and YouTube are client-server based which result in high administration costs for the provider. In contrast to that peer-to-peer systems offer scalability and low costs, but are limited in their functionality.In this paper we present a framework for peer-to-peer based multimedia online communities. We identified the key challenges for this new application of the peer-to-peer paradigm and built a plugin based, easily extendible and multi-functional framework. Further, we identified distributed linked lists as valuable data structure to implement the user profiles, friend lists, groups, photo albums and more. Our framework aims at providing the functionality of common online community platforms combined with the multimedia delivery capabilities of modern peer-to-peer systems, e.g. direct multimedia delivery and access to a distributed multimedia pool.

The IEEE 802.16 standard specifies a MeSH mode which permits the deployment of Wireless Mesh Networks (WMNs) supporting carrier-grade QoS. The network operator for such planned WMNs is interested in maximizing the traffic admitted in the WMN and simultaneously supporting QoS. Recently network coding has emerged as a promising technique for increasing the throughput in WMNs. This paper proposes CORE, which addresses the problem of jointly optimizing the routing, scheduling, and bandwidth savings via network coding. Prior solutions are either not applicable in the 802.16 MeSH or computationally too costly to be of practical use in the WMN under realistic scenarios. COREpsilas heuristics, in contrast, are able to compute solutions for the above problem within a operator definable maximum computational cost, thereby enabling the computation and near real-time deployment of the computed solutions. We analyze the performance of COREpsilas heuristics via a thorough simulation study covering the typical usage scenarios for WMNs. The results presented demonstrate that CORE is able to increase the number of flows admitted considerably and with minimal computational costs. Further, the results provide insights into limiting factors for the gains which can be obtained in different usage scenarios.

Future buildings and environments are envisioned to provide ambient intelligence, adapting to a userpsilas preferences based on information about his context and status. Smart heterogeneous sensor networks are well suited data sources for such environments, because they allow for dynamic adaptation to newly added sensor types and novel tasks. Realistic verification of protocols and algorithms for smart networks poses special constraints on testbeds, necessitating support for heterogeneous platforms and mobility in the network. These distinct requirements limit the usability of many known testbeds of purely homogeneous nature. In this paper, we determine a minimum set of premises for smart heterogeneous sensor network testbeds and evaluate existing architectures with respect to these requirements. We then present our tubicle node platform, an integrated sensor network node providing inherent support for heterogeneity and fulfilling the determined set of requirements in their entirety. A set of twenty tubicles forms the basis for our TWiNS.KOM testbed. Specifically designed for heterogeneity, the architecture allows rapid validation of smart sensor network algorithms and quick experimental setup.

Delay tolerant applications allow time to be used as an additional degree of freedom for security mechanisms in mobile ad hoc networks. By introducing artificial delays for the communication of delay tolerant applications, we optimize the point in time for starting or continuing a transmission. We develop mechanisms to exploit the knowledge on the proximity of the sender, the receiver, and intermediate, relaying nodes to misbehaving nodes detected. We propose different strategies for delayed transmission and provide a performance analysis based on a series of simulation studies. Our results show that we reduce the effects of misbehavior by keeping away data from misbehaving nodes.

Multimedia streaming of mostly user generated content is an ongoing trend, not only since the upcoming of Last.fm and YouTube. A distributed decentralized multimedia streaming architecture can spread the (traffic) costs to the user nodes, but requires to provide for load balancing and consider the heterogeneity of the participating nodes. We propose a DHT-based information gathering and analyzing architecture which controls the streaming request assignment in the system and thoroughly evaluate it in comparison to a distributed stateless strategy. We evaluated the impact of the key parameters in the allocation function which considers the capabilities of the nodes and their contribution to the system. Identifying the quality-bandwidth tradeoffs of the information gathering system, we show that with our proposed system a 53% better load balancing can be reached and the efficiency of the system is significantly improved.

Resource allocation and resource planning, especially in a SOA and grid environment, become crucial. Particularly, in an environment with a huge number of workflow consumers requesting a decentralized cross-organizational workflow, performance evaluation and execution-management of service-oriented workflows gain in importance. The need for an effective and efficient workflow management forces enterprises to use intelligent optimization models and heuristics to compose workflows out of several services under real-time conditions. This paper introduces the required architecture workflow performance extension - WPX.KOM for resource planning and workload prediction purposes. Furthermore, optimization approaches and a high-performance heuristic solving the addressed resource planning problem with low computational overhead are presented.

Multimedia creation and consumption is highly intensive and makes up the majority of Internet traffic nowadays. End-users are able to share their digital content with each other and to build communities based on interests, which often differ drastically according to location. Distributing these media using a central server can be quite expensive for a content provider. Distributed (peer-to-peer like) systems share costs evenly among participants. Thus, distributed multimedia systems will be more important in the future. The global distribution of end-users aggravates high-quality delivery of multimedia content. In this paper, we argue that geographical location-awareness greatly helps distributed multimedia communication. It increases the quality of multimedia content delivery and at the same time satisfies the growing need for more personalized, location-based services. In this paper, as a proof of concept, we introduce an overlay structure for distributed multimedia systems (and similar systems), which is location-aware and uses the locations of its nodes to optimize node-to-node communication for performance and delay. At the same time, the system enables location-based services.

Ubiquitous network connectivity and mobile communications have recently attracted remarkable attention. Wireless multihop networks such as Mobile Ad hoc Networks or Wireless Mesh Networks have been proposed to cater to the arising needs. Various security challenges persist, esp. because these networks build on the premise of node cooperation. Secure routing protocols and mechanisms to detect routing misbehavior in the direct neighborhood exist; however, collusion of misbehaving nodes has not been adequately addressed yet. We presentLeakDetector, a mechanism to detect colluding malicious nodes in wireless multihop networks. In combination with proactive secure multipath routing algorithms,LeakDetectorenables the calculation of the packet-loss ratio for the individual nodes. We perform an experimental analysis, which shows the excellent detection quality ofLeakDetector.

The impact of the peer-to-peer paradigm increases both in research and in industry. Still, serious applications for P2P-based systems are rare. On the other hand, Emergency Call Handling (ECH) is (or will be) a mandatory function for VoIP services. In this paper we investigate international legal and technical requirements of ECH and present ECHoP2P, a solution that fulfills these requirements. Based on Globase.KOM and HiPNOS.KOM, ECHoP2P provides the functionality to determine the closest and (geographically) responsible Emergency Station to a calling peer. Further, Emergency Calls are processed with highest priority in the overlay, so that quality of service guarantees are given. We evaluated ECHoP2P thoroughly and present the quality and costs analysis, identified tradeoffs and effects of optimization parameters. ECHoP2P provides a fully evaluated solution for Emergency Call Handling and for further location-aware applications.

The IEEE 802.16 standard represents the state-of-the-art for quality of service (QoS) aware broadband wireless access networks. Initially the standard provided sophisticated QoS mechanisms only for a static network (i.e. stationary subscribers), but recently the amendment IEEE 802.16e-2005 introduced mobility support for the individual subscriber stations. Network entry is the first step required for nodes to register themselves with the 802.16 network. The performance of the network entry process is crucial to support QoS, especially if node churn is high. In this paper, we develop an analytical model of the network entry process in IEEE 802.16. This model enables us to predict the effect and influence of important protocol parameters for joining the network. Using our model, we show that the selection of correct and appropriate protocol parameters is crucial to support setup-delay sensitive applications such as emergency services or IP-telephony. Our model can be used as a tool to derive the feasible range for individual network parameters in selected application scenarios.

Peer-to-peer and mobile networks gained significant attention of both research community and industry. Applying the peer-to-peer paradigm in mobile networks lead to several problems regarding the bandwidth demand of peer-to-peer networks. Time-critical messages are delayed and delivered unacceptably slow. In addition to this, scarce bandwidth is wasted on messages of less priority. Therefore, the focus of this paper is on bandwidth management issues at the overlay layer and how they can be solved. We present HiPNOS.KOM, a priority based scheduling and active queue management system. It guarantees better QoS for higher prioritized messages in upper network layers of peerto- peer systems. Evaluation using the peer-to-peer simulator PeerfactSim.KOM shows that HiPNOS.KOM brings significant improvement in Kademlia in comparison to FIFO and Drop-Tail, strategies that are used nowadays on each peer. User initiated lookups have in Kademlia 24% smaller operation duration when using HiPNOS.KOM.

Wireless mesh networks (WMNs) build on user nodes to form the network's routing infrastructure. In particular, the correct forwarding behaviour of each intermediate node on a multihop path from a source node to a destination node is crucial for the functioning of the mesh network. However, current secure routing solutions and misbehaviour detection mechanisms are not sufficient and are mostly inapplicable in mesh networks based on state-of-the-art wireless technology. In particular, hop- by-hop per-link encryption mechanisms break solutions that are based on the overhearing of the wireless channel, which leads to severe problems in the presence of misbehaving nodes. We present AntSec, WatchAnt, and AntRep, which together address the above security gap. AntSec guarantees integrity and authenticity of routing messages, WatchAnt detects misbehaviour in forwarding data messages as well as routing messages and in addition is able to cope with per-link encryption at the MAC layer. AntRep is a reputation management system and helps take punitive action against misbehaving nodes. AntSec, WatchAnt, and AntRep are well suited for WMNs with a quasi-static network topology. Through a thorough evaluation we show the improved routing performance of AntSec working together with WatchAnt and AntRep.

Network coding has been successfully applied to contemporary wireless Mesh networks (WMNs) to reduce intra-network interference and enhance the capacity of the WMN. State-of-the-art WMNs, however, introduce features such as explicit per-link bandwidth reservation and per-link encryption, which make the application of prior network coding approaches in these WMNs suboptimal, if not impossible. In this paper we look at the above challenge from a new perspective and present efficient heuristics for tackling the joint QoS routing, scheduling, and network coding problem. An experimental evaluation shows that the designed heuristics are able to yield excellent solutions in real-time, even if we assume dynamically changing traffic in the WMN.

Re-use of digital resources is an important issue in e-Learning scenarios, because only intensive re-use can make e-Learning cost efficient. Besides reusing whole courses, authors often desire to re-use fine grained parts of courses for creating new Learning Resources. The granularity which appears to be most promising for this kind of re-use is the level of information objects. Information objects each have a dedicated didactic function; a set of information objects with different didactic functions are combined into Learning Objects. This paper analyzes how didactic functions of existing information objects can be automatically classified using machine learning technology. The results of such classification methods on a set of Learning Resources from medical science are discussed.

Location based services are becoming increasingly popular as devices that determine geographical position become more available to end users. The main problem of existing solutions to location-based search is keeping information updated requires centralized maintenance at specific times. Therefore, retrieved results do not include all objects that exist in reality. A peer-to-peer (P2P) approach can easily overcome this issue as peers are responsible for the information users are searching for. Unfortunately, current state-of-the-art overlays cannot fulfill the requirements for efficient and fully retrievable location-based search. In this paper we present Globase.KOM, a hierarchical tree-based P2P overlay that enables fully retrievable location-based overlay operations which proved to be highly efficient and logarithmically scalable.

The conception and production of new e-learning content in a corporate environment is expensive and time-consuming. In this paper we propose a content modeling approach as part of an authoring management platform. This platform aims to make the cooperative process of conception and production of e-learning content faster, easier to manage and equips knowledge domain experts with a tool, which does not demand for media and didactic experience

Modular learning resources that can be aggregated to larger learning resources are crucial for the future success of e-learning. Re-use of learning resources will only reach significant numbers, if not only re-use "as-is" is supported, but also aggregation and adaptation to a new teaching or learning context. This paper analyzes requirements on a format for learning resources that supports modularization and aggregation. A suitable format based on SCORM and LOM is proposed and afterwards evaluated by means of a tool implementation

This paper discusses the quality of service (QoS)-aware composition of Web services. The work is based on the assumption that for each task in a workflow a set of alternative Web services with similar functionality is available and that these Web services have different QoS parameters and costs. This leads to the general optimization problem of how to select Web services for each task so that the overall QoS and cost requirements of the composition are satisfied. Current proposals use exact algorithms or complex heuristics (e.g. genetic algorithms) to solve this problem. An actual implementation of a workflow engine (like our WSQoSX architecture), however, has to be able to solve these optimization problems in real-time and under heavy load. Therefore, we present a heuristic that performs extremely well while providing excellent (almost optimal) solutions. Using simulations, we show that in most cases our heuristic is able to calculate solutions that come as close as 99% to the optimal solution while taking less than 2% of the time of a standard exact algorithm. Further, we also investigate how much and under which circumstances the solution obtained by our heuristic can be further improved by other heuristics

The intrinsic properties of the employed graphs in designing peer-to-peer overlay networks are crucial for the performance of the deployed peer-to-peer systems. Several structured topologies have been proposed based on meshes, enhanced rings, redundant tree structures, etc. Among them, de Bruijn graphs are promising alternatives since they provide some crucial asymptotically optimal characteristics. In this paper, we discuss the necessary algorithms and protocol messages to develop efficiently the employed routing procedure of Omicron, which is a hybrid overlay network based on de Bruijn graphs enriched with clustering and role specialization mechanisms. Enhancements of the original de Bruijn structure are advised to cope with the intrinsic issue of uneven distribution of the routing workload. The developed system is evaluated and compared with Chord, which is used as the reference point. The superiority of de Bruijn based overlay networks with respect to scalability is quantitatively demonstrated using simulation experiments. Further, the ability of the two systems to exploit the underlying network is investigated

The IEEE 802.16-2004 standard specifies wireless broad-band networks with optional support for multi-hop mesh operation (mesh mode). The provision and support of high-quality real-time services such as voice over IP is crucial, if wireless networks based on the IEEE 802.16-2004 standard are to challenge wired network services. In this paper we investigate and identify critical factors in enabling real-time services in 802.16 based networks operating in the mesh mode. We present an analytical performance analysis and a simulation study investigating the coordinated centralized scheduling mechanism as specified in the 802.16-2004 standard. Our results show that the scalability and efficiency of such mesh networks with respect to real-time services are at stake. Our results, moreover, aid in the adjustment of critical system parameters allowing for optimized network performance.

Today, we witness a transformation of radio access network topologies from strictly tree-structured towards meshed architectures. Yet, these edge networks follow mostly circuit-switched paradigms to support quality of service applications such as voice or video communication. In this work, we develop a novel quality of service aware routing framework to optimize the performance of edge networks in the packet-switched domain. Starting from the Internet's best-effort routing paradigm and building on related work, we formulate a near-optimal multiclass minimum-delay routing algorithm. Our algorithm optimizes network-wide end-to-end delay and allows for differentiation of service. We exploit two orthogonal dimensions namely multipath routing and class-based service prioritization. We provide a precise description of our algorithm and a detailed experimental analysis against state of the art routing algorithms. Our algorithm is able to achieve excellent performance while maintaining the simplicity of a decentralized and distributed routing algorithm, thus matching the requirements for future radio access networks.

Combining the concepts of caching and transmission control protocol (TCP)-friendly streaming of layer-encoded video bears the problem that those videos might not be cached in full quality. Therefore, we focus in this work on the scheduling of retransmissions of missing segments of a cached video in a manner that allows clients to receive the content in an improved quality. In a first step, we conducted subjective assessments of variations in layer-encoded video with the goal to validate existing quality metrics, including our own, which are based on certain assumptions. A statistical analysis of the subjective assessment validates these assumptions. We also show that the frequently used peak signal-to-noise ratio (PSNR) is not an appropriate metric for variations in layer-encoded video. With the insight from the subjective assessment we develop heuristics for retransmission scheduling and prove their applicability by conducting a series of simulations.

No abstract available.

The dependability of the routing system in ad hoc networks inherently relies on node behavior. In order to support multihop operation in the network, most ad hoc routing algorithms assume well-behaving nodes. However, in reality there may exist constrained, selfish or malicious nodes. We discuss the influence of node misbehavior on the routing process. In particular, we derive a classification for misbehaving nodes and extend an analytical model of the route acquisition process executed by the ad hoc on-demand distance vector (AODV) routing protocol to cover different classes of misbehavior. The validation of the behavior model, and the clarification of the impact misbehaving nodes impose onto the routing process, is completed using an experimental analysis.

Communication is an essential part of our daily life. A multitude of devices enable users to communicate everywhere and anytime. One drawback resulting from this ability is the expectation of a caller to always reach the callee. As a consequence the possibility to restrict "availability for communication" becomes a necessary feature too. Users demand efficient filtering mechanisms to control incoming calls according to their current context. Communication services should become more user centric and consider context information to adapt to the most suitable behavior. This paper investigates the use of context information to enhance existing SIP call control services and services created with the call processing language (CPL). These context-aware communication services are the proposed approach to cope with the demand for a user centric control of incoming calls. The proposed solutions have been implemented as an extended SIP call control service and an extension to the existing CPL syntax. Currently, location information forms the primary source of context information. Different indoor location sensing systems have been evaluated. Finally, two different kinds of service types have been chosen for evaluation as representatives for the variety of service creation approaches especially in a SIP environment.

Quality of Service (QoS) is an area with high academic curiosity. Our long-term goal is to develop a unified mathematical model. This paper is a first step towards this ambitious goal. The most widespread models for network QoS are network calculus and queueing theory. While the strength of queueing theory is its proven applicability to a wide area of problems, Network calculus can offer performance guarantees. We analyse by simulation the benefit of bringing the two of them together, i.e., bounding the stochastic processes of a queue with methods from network calculus. A basic result from network calculus is that enforcing traffic shaping and service curves bounds the buffer. This leads to denying buffer states in queues with infinite buffer. Specifically, we analyse what happens with the probability mass of such buffer states. Finally, we discuss how our results can be used for dimensioning buffers for multiplexed traffic.

We present an admission control scheme which provides per-flow delay and bandwidth guarantees based solely upon simple class-based strict priority queueing. We derive basic properties of the worst-case behaviour in strict priority queueing systems using network calculus. Building upon these properties, a flow admission control scheme is devised. The rationale behind this work is the appealing simplicity as well as the almost ubiquitous availability of strict priority queueing in today's routers and the thus promising applicability of our results for practical purposes in providing quality of service (QoS) in the Internet.

Multi-rate multicast has been proposed as a scalable solution to transmitting video over the Internet to receivers with heterogeneous and dynamic rate requirements. The applicability of an equation-based mechanism to congestion control for a protocol which bases its join and leave actions on the calculation of the TCP response function is investigated. We focus on the rate calculation algorithm proposed in TFRC (TCP-friendly rate control), as it is currently a very promising and mature approach to calculating a TCP-compatible rate. By means of a network simulator and an adjusted TFRC protocol implementation, we show that the TCP-compatible rate calculated with the algorithm as originally proposed tends to be biased when applied in environments with a low degree of statistical multiplexing. To improve the performance of the basic algorithm, we propose a simple heuristic approach.

Currently, we see the evolution of large scale community and metropolitan area networks based on inexpensive wireless local area network technology. We present the results of an experimental analysis, which investigates the potential of quality of service routing mechanisms within this challenging environment. Our investigation is based on a model of a radio access network designed to cover a large city center by means of decentralized and distributed routers, which are tightly meshed. The workload is modeled to reflect the estimated usage patterns based on statistical data collection of user mobility and combined with synthetic traffic matrices. We present results for various routing strategies including shortest path routing, delay constrained routing as well as various multipath quality of service routing variants. Moreover, we investigate different traffic distributions. Our findings are, that multipath routing is able to enhance the utility of the network significantly.

We present a token-based accounting mechanism that alleviates the free riding problem in P2P networks. The approach is complemented by distributed pricing as a flexible and viable scheme to incite users to share valuable content and to efficiently balance requests among all peers based on economic decisions.

We take an availability-centric view on quality of service (QoS) and propose a model and mechanisms for studying the effectiveness of realistic replication schemes on availability QoS for peer-to-peer (P2P) systems. We especially tackle the dynamic replica placement (RP) problem where our focus is on choosing dynamically the number and location of replicas while (1) meeting different availability QoS requirements for all individual peers and (2) taking the intermittent connectivity of peers explicitly into account. We model P2P systems as a dynamic stochastic graph in which the nodes go up and down depending on their assigned up probability. We develop some simple heuristic algorithms for solving the RP problem, which are fully distributed and adaptive. Through an event-driven simulation study we compare and evaluate the achieved availability QoS of the proposed RP algorithms. Simulation results show that (1) even simple heuristics can achieve reasonably high availability QoS, and (2) satisfying availability QoS requires more replicas than for only increasing the hit rate.

In contrast to classical assumptions in video on demand (VoD) research, the main requirements for VoD in the Internet are adaptiveness, support of heterogeneity, and last but not least high scalability. Hierarchically layered video encoding is particularly well suited to deal with adaptiveness and heterogeneity support for video streaming. A distributed caching architecture is the key to a scalable VoD solution in the Internet. Thus, the combination of caching and layered video streaming is promising for an Internet VoD system, yet, requires thoughts about some new issues and challenges. In this paper, we investigate one particular of these issues: how to deal with retransmissions of missing segments for a cached layered video in order to meet user demands to watch high quality video with relatively few quality variations. We devise a suite of fairly simple retransmission scheduling algorithms and compare these against existing ones by simulative experiments.

A wide variety of biometric based techniques have been proposed but it is quite difficult to classify the approaches according to their application domains and to measure their functionality. Our intention is to classify today's applications in detail for one particular biometric scheme, handwriting. To give individual users with a specific application in mind orientation and a decision tool, we have built a new classification scheme and furthermore define major characteristics for each of the application classes as an evaluation matrix.

The production of interactive multimedia content is in most cases an expensive task in terms of time and cost. It must hence be the goal to optimize the production by exploiting the reusability of interactive multimedia elements. Reusability can be triggered by a combination of reusable multimedia components, together with the appropriate use of metadata to control the components as well as their combination. In this article, we discuss reusability and adaptability aspects of interactive multimedia content in web-based learning systems. In contrast to existing approaches, we extend a component-based architecture to build up interactive multimedia visualization units by the use of metadata for reusability and customizability issues.

Quality of service guarantees for multimedia communication systems have been considered on several abstraction levels. In the multimedia networking field it is typical to identify the minimal QoS requirements of an application to save resources by guaranteeing its functionality. Many of these applications can operate in spite of an imperfect delivery of media data, while other applications such as distributed databases or distributed file systems consider perfect QoS necessary but accept delay. The basic problems of the latter is the consistency of their data, while the former require a consistent perception of the content. More generically, both QoS requirements can be interpreted as a problem of maintaining a consistent system state. Consequently we assume that many distributed applications, including most distributed multimedia applications, can fulfil their tasks in spite of imperfect consistency. Since the application requirements differ widely, the elements that make up "consistency" must be separated and classified. This paper introduces Consistency QoS and proposes a classification of elements that determine an application's consistency requirements. The low level QoS requirements that these separate parameters rely on are shown, and example parameter sets for application classes are given.

Replicating data and services at multiple networked computers increases the service availability of distributed systems. This paper presents the design and implementation architecture of a replication mechanism for a distributed multimedia system medianode which is developed as an infrastructure to share multimedia-enhanced teaching materials among lecture groups. With the replication mechanism, medianode provides enhanced access to presentation materials in both connected and disconnected operation modes. The main contribution of this paper is the identification of new replication requirements in distributed media systems and a multicast-based update propagation mechanism by which not only the update events are signaled, but also the updated data are exchanged between replication managers.

We describe implementation aspects and performance results of an innovative and publicly available RSVP implementation. Much debate exists about the applicability of RSVP as a signalling protocol in the Internet, particularly for a large number of unicast flows. While there has been a significant amount of work published on the theoretical concepts of RSVP signalling and conjectures about its presumed shortcomings, rather little attention has been paid to the implementation details of the core protocol engine. With our work, in spite of being still far from a final judgement, we try to shed light on this issue by presenting certain design details of a new implementation and a study about its performance. One particular result is given by the observation that a relatively cheap router based on PC hardware can sustain the signalling for more than 50,000 unicast flows.

Within a global networked environment, security aspects have become more and more important and access control at network borders is considered essential. For this purpose firewall systems are used which provide a well-established security mechanism to restrict the exchanged traffic to a certain subset of users and applications. In order to cope with the increasing demand for new applications, a firewall must be flexible and extensible to support such new applications and their protocols. RSVP is a dynamic signalling protocol, which has been invented to negotiate resource requirements between end systems and a packet-based communication network. We investigate the interoperation of RSVP with a firewall system in order to support new applications in a generic way. We show how the resulting system flexibility allows for a variety of employment scenarios and incremental deployment of such a technology. We back up our claims by describing a prototype that we have implemented.

In contrast to audio which is often streamed as complete music titles or even as a life feed from a radio station, video in today's Internet is almost only available as small clips and pre-generated programs. Although some of the problems concerning AV streaming are reasonably solved right now, some work in fields like wide area distribution systems need further investigation to make applications like "true video-on-demand" work. Our research and the one of many others is focused on problems that have to be solved to make application like VoD work in the Internet. It is mainly concerned with wide area distribution. We present a platform for experimental VoD research which is thought to support researchers working on VoD and wide area distribution for audio and video content. This platform offers researchers the possibility to implement their ideas without building a complete streaming environment and in addition allows the combination of different implementations. After motivating the development of our platform we present the design of our platform, give an overview of the actual implementation and the existing components that we have already built. Finally, example scenarios for the use of our platform in research are given.

Providing guaranteed QoS necessarily requires allocation of scarce resources. It is conceivable that at least at system edges scarcity of resources, exposed in the form of non-negligible (virtual) costs, will prevail to necessitate explicit allocation of resources as opposed to pure over-dimensioning. An example of this logic is constituted by the Differentiated Services (DiffServ) architecture. Often such resource allocation decisions are done on a multi-period basis because resource allocation decisions at a certain point in time may depend on earlier decisions and thus it can turn out sub-optimal to look at decisions in an isolated fashion. Therefore, we investigate a fairly large and diverse set of (network) QoS problems all of which deal with the problem of multi-period resource allocation at system edges. We devise a taxonomy for the classification of these problems and introduce a common mathematical framework under which these problems can be tackled. The ultimate goal of our work is to strive for solution techniques towards the generalized class of problems such that these are applicable in a number of scenarios which have so far not been regarded in an integrated fashion.

We present the ConnecTable, a new mobile, networked and context-aware information appliance that provides affordances for pen-based individual and cooperative work as well as for the seamless transition between the two. In order to dynamically enlarge an interaction area for the purpose of shared use, a flexible coupling of displays has been realized that overcomes the restrictions of display sizes and borders. Two ConnecTable displays dynamically form a homogeneous display area when moved close to each other. The appropriate triggering signal comes from built-in sensors allowing users to temporally combine their individual displays to a larger shared one by a simple physical movement in space. Connected ConnecTables allow their users to work in parallel on an ad-hoc created shared workspace as well as exchanging information by simply shuffling objects from one display to the other. We discuss the user interface and related issues as well as the software architecture. We also present the physical realization of the ConnecTables.

The production of interactive multimedia content is in most cases an expensive task in terms of time and cost. Hence, optimizing production by exploiting the reusability of interactive multimedia elements is mandatory. Reusability can be triggered by a combination of resuable multimedia components and the appropriate use of metadata to control the components as well as their combination. In this article, we discuss the reusability aspects of interactive multimedia content in web-based learning systems. In contrast to existing approaches, we extend a component-based architecture to build interactive multimedia visualization units with the use of metadata for reusability and customizability. In the three-tier model, the lowest layer of the paradigm corresponds to the programmer (code reusability). The user interface of an educational visualization is located at the top layer where the interaction with the end-user (student) takes place. The educator is located between the top and the bottom layers. This medium layer allows adapting interactive multimedia content according to the needs of the user, applying a predefined set of metadata. The teacher can both adjust the level of explanation and the level of interactivity of an animation, and influence the presentation and the results of the algorithms being illustrated (program reusability). After a theoretical overview, we explain our architecture by giving an example of an application.

Many educational resources and objects have been developed as Java applets or applications, which can accessed by simply downloading them from various repositories. It is often necessary to share these resources in real time, for instance when an instructor teaches remote students how to use a certain resource explains the theory behind it. We have developed some tools for this purpose that emulate a virtual classroom, and are primarily designed for synchronous sharing of resources. They enable participants to share Java objects in real time and also allow the instructor to dynamically manage the telebearing session.

Well engineered Web based courseware and exercises provide flexibility and added value to the students, which goes beyond the traditional text book or CD-ROM based courses. The Multibook project explores the boundaries of customized learning materials by composing learning trails dynamically as learners have set their profile to access a course. In this paper we first give an overview of the core project ideas and illustrate them along our Software Engineering course. Then we present a novel extension to the project's exercise environment with a graph editing component that particularly fits the needs of structure-related assignments.

The support of a single signalling protocol for all components on the data path of a QoS-based transmission cannot necessarily be assumed. We investigate the issues surrounding hierarchically layered network QoS signalling configurations, as e.g. can be found in RSVP over ATM signalling. After introducing and discussing these issues we conclude that many of the decisions involved require understanding the performance characteristics of such layered signalling configurations. We therefore describe the implementation of an RSVP/ATM edge device, which we then use to conduct measurements in a configuration that involves in effect three layered signalling protocols: RSVP and ATM's UNI and PNNI. Using these measurements we review the issues in layering signalling protocols and reinforce design decisions being taken for the edge device mediating between the different mechanisms of the two network QoS architectures.

This panel will discuss a recommendation for curricula guidelines for courses about multimedia. Based on conference input, the guidelines will be modified for review prior to future publication by ACM (with other groups). The recommendation will be one of the main results of a June 2000 Dagstuhl workshop led by 4 of the panelists. Dr. Heller, the 5th panelist, also attended that workshop, and is co-PI with the panel moderator on a directly related NSF project, Curriculum Resources in Interactive Multimedia, CRIM, see http://ei.cs.vt.edu/~crim. Each of the panelists has taught courses about multimedia. Each is interested in developing tools/demonstrations/resources to help in those course. Each has a particular area of interest in the multimedia field. Together they constitute a representative group among those who will contribute to and benefit from curricula resources in multimedia.

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We think that web caches will soon have to better support multimedia demands.In this paper we present a cache server design for internet video on demand (VoD) systems.1.1

ABSTIUCTThe development of new multimedia services and environments requires new concepts both to support the new working process on distributed computers and to protect the multimedia data during the production and the distribution in digital marketplaces.This article addresses copyright protection as a major security demand in digital marketplaces We propose and compare two watermarking techniques for MPEG video with the intention to show the advantages and the possible weakness in the schemes working in the frequency domain and in the spatial domain.To improve the view to the distortion of the watermarked frames we generate a 3D-difference view measuring the changes which were made during watermarking process and/or caused by several damaging attacks. 1.1

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Multimedia communication deals with the transfer, protocols, services, and mechanisms of discrete media data (such as text and graphics) and continuous media data (like audio and video) in/over digital networks. Such a communication requires all involved components to be capable of handling a well-defined quality of service (QoS). The most important QoS parameters are used to request: (1) the required capacities of the involved resources, (2) compliance to end-to-end delay and jitter as timing restrictions, and (3) restriction of the loss characteristics. In this paper, we describe the necessary issues and study the ability of current networks and communication systems to support distributed multimedia applications. Further, we discuss upcoming approaches and systems that promise to provide the necessary mechanisms and consider which issues are missing for a complete multimedia communication infrastructure.

Digital and interactive TV systems will bring hundreds of TV program channels to the people.Then, the use of existing strategies for channel selection will fail: It is neither possible to select the program by "sur@g" through the channels, nor by using printed program guides.This paper describes a new approach towards creation of a Personal Electronic Program Guide (EPG) regarding the individual view preferences of a usez The foundation of individual TV program pre-selection is a classified and categorized TV program description and the maintenance of user profiles describing his viewing preferences.Besides creation of user projiles, an automatic update technique will be introduced.Channel selection events are taken as parameters for an adjustment of user projiles.Personal program pre-selection is done by using intelligent $ltering techniques which apply individual user profiles to the TV program description (so-called matching).An approach to design and realize an EPG proto~pe system will be described in this papex

Researchers have addressed multimedia synchronization from various perspectives. The major issues include how to specify and how to implement synchronization. Especially in the specification area a variety of techniques have been published and implemented. This survey summarizes briefly synchronization requirements, presents a multimedia synchronization reference model, shows details of various specification approaches and applies the reference model to compare existing prominent approaches as case studies.

The evolving multimedia applications generate requirements for complex transport capabilities, i.e., functional features, in the end-to-end communication system such as handling of heterogeneity among communicating terminals, supporting finer levels of user-specifiable quality of data transport service, and synchronization of various data streams for delivery at users in real time. Accordingly, the communication system may be viewed as extending the basic capabilities provided by the backbone network (e.g., bandwidth allocation) into a set of transport capabilities suitable for complex applications. This paper presents: (1) an object-oriented view of the user interface to the communication system with an elegant separation of data transport functionalities, and (2) an approach to the design of underlying transport protocols. The object-orientation decomposes an application-level data transport into a set of network channel objects, with each channel object handling a separate data stream. The object interactions are modeled using a "data-flow programming" style, which allows a richer set of protocols to implement the communication system and offers flexibility to accommodate complex and heterogeneous subscriber services/terminals. The "data-flow programming" method also allows a high degree of communication level parallelism among data transport through channels. The view of a multimedia communication system as a "parameterizable black-box", as underscored in the object-oriented structuring, allows easier interworking of the communication system with existing networks and easier integration of multimedia transport into programming environments.

Multimedia synchronization comprises both the definition and the establishment of temporal relationships among media types. The presentation of 'in sync' data streams is essential to achieve a natural impression, data that is 'out of sync' is perceived as being somewhat artificial, strange, or even annoying. Therefore, the goal of any multimedia system is to enable an application to present data without no or little synchronization errors. The achievement of this goal requires a detailed knowledge of the synchronization requirements at the user interface. The paper presents the results of a series of experiments about human media perception that may be used as 'quality of service' guidelines. The results show that skews between related data streams may still give the effect that the data is 'in sync' and gives some constraints under which jitter may be tolerated. The author uses the findings to develop a scheme for the processing of nontrivial synchronization skew between more than two data streams.

Multimedia is defined as the integrated generation, representation, processing, storage, and dissemination of independent machine-processable information expressed in multiple time-dependent and time-independent media such as data, graphics, drawings, voice, audio, and video. The characteristics of synchronization mechanisms desirable for central and distributed multimedia systems are addressed. The concept of multimedia objects as components of an object-based model for a multimedia system is introduced. The essential new synchronization requirement is restricted blocking together with synchronization features covering real-time aspects. Existing synchronization mechanisms can be altered or new ones defined to meet these requirements.>

This paper presents a system, which generates code for a high speed parallel computer architecture taking as input the tolerance schemes of digital filters. The multi-processor system consists of data-, I/O-processors and a multiport memory. The interconnection network is a crossbar. The data-processors contain a private memory for the program instructions and local register blocks in which intermediate operands are stored. All system components operate synchronously.