Abstract: This work addresses the problem of application-layer congestion control in multi-robot systems (MRS). It is motivated by the fact that many MRS constrain the amount of transmitted data in order to avoid congestion in the network and ensure that critical messages get delivered. However, such constraints often need to be manually tuned and assume constant network capabilities. We introduce the adaptive goodput constraint, which smoothly adapts to varying communication conditions. It is suitable for long-term communication planning, where rapid changes are undesirable. We analyze the introduced method in a simulation-based study and show its practical applicability using mobile robots.

Abstract: This work addresses the problem of what information is worth sending in a multi-robot system under generic constraints, e.g., limited throughput or energy. Our decision method is based on Monte Carlo Tree Search. It is designed as a transparent middleware that can be integrated into existing systems to optimize communication among robots. Furthermore, we introduce techniques to reduce the decision space of this problem to further improve the performance. We evaluate our approach using a simulation study and demonstrate its feasibility in a real-world environment by realizing a proof of concept in ROS 2 on mobile robots.

Abstract: Due to the growing importance of optimizing the quality and efficiency of video streaming delivery, accurate assessment of user-perceived video quality becomes increasingly important. However, due to the wide range of viewing distances encountered in real-world viewing settings, the perceived video quality can vary significantly in everyday viewing situations. In this paper, we investigate and quantify the influence of viewing distance on perceived video quality. A subjective experiment was conducted with full HD sequences at three different fixed viewing distances, with each video sequence being encoded at three different quality levels. Our study results confirm that the viewing distance has a significant influence on the quality assessment. In particular, they show that an increased viewing distance generally leads to increased perceived video quality, especially at low media encoding quality levels. In this context, we also provide an estimation of potential bitrate savings that knowledge of actual viewing distance would enable in practice. Since current objective video quality metrics do not systematically take into account viewing distance, we also analyze and quantify the influence of viewing distance on the correlation between objective and subjective metrics. Our results confirm the need for distance-aware objective metrics when the accurate prediction of perceived video quality in real-world environments is required.

Abstract: In per-title encoding, to optimize a bitrate ladder over spatial resolution, each video segment is downscaled to a set of spatial resolutions, and they are all encoded at a given set of bitrates. To find the highest quality resolution for each bitrate, the low-resolution encoded videos are upscaled to the original resolution, and a convex hull is formed based on the scaled qualities. Deep learning-based video super-resolution (VSR) approaches show a significant gain over traditional upscaling approaches, and they are becoming more and more efficient over time. This paper improves the per-title encoding over the upscaling methods by using deep neural network-based VSR algorithms. Utilizing a VSR algorithm by improving the quality of low-resolution encodings can improve the convex hull. As a result, it will lead to an improved bitrate ladder. To avoid bandwidth wastage at perceptually lossless bitrates, a maximum threshold for the quality is set, and encodings beyond it are eliminated from the bitrate ladder. Similarly, a minimum threshold is set to avoid low-quality video delivery. The encodings between the maximum and minimum thresholds are selected based on one Just Noticeable Difference. Our experimental results show that the proposed per-title encoding results in a 24% bitrate reduction and 53% storage reduction compared to the state-of-the-art method.

Abstract: Infrastructure-as-a-service (IaaS) Clouds concurrently accommodate diverse sets of user requests, requiring an efficient strategy for storing and retrieving virtual machine images (VMIs) at a large scale. The VMI storage management requires dealing with multiple VMIs, typically in the magnitude of gigabytes, which entails VMI sprawl issues hindering the elastic resource management and provisioning. Unfortunately, existing techniques to facilitate VMI management overlook VMI semantics (i.e at the level of base image and software packages), with either restricted possibility to identify and extract reusable functionalities or with higher VMI publishing and retrieval overheads. In this paper, we propose Expelliarmus, a novel VMI management system that helps to minimize VMI storage, publishing and retrieval overheads. To achieve this goal, Expelliarmus incorporates three complementary features. First, it models VMIs as semantic graphs to facilitate their similarity computation. Second, it provides a semantically-aware VMI decomposition and base image selection to extract and store non-redundant base image and software packages. Third, it assembles VMIs based on the required software packages upon user request. We evaluate Expelliarmus through a representative set of synthetic Cloud VMIs on a real test-bed. Experimental results show that our semantic-centric approach is able to optimize the repository size by 2.3 - 22 times compared to state-of-the-art systems (e.g. IBM’s Mirage and Hemera) with significant VMI publishing and slight retrieval performance improvement.

Abstract: We incorporate communication into the multi-UAV path planning problem for search and rescue missions to enable dynamic task allocation via information dissemination. Communication is not treated as a constraint but a mission goal. While achieving this goal, our aim is to avoid compromising the area coverage goal and the overall mission time. We define the mission tasks as: search, inform, and monitor at the best possible link quality. Building on our centralized simultaneous inform and connect (SIC) path planning strategy, we propose two adaptive strategies: (1) SIC with QoS (SICQ): optimizes search, inform, and monitor tasks simultaneously and (2) SIC following QoS (SIC+): first optimizes search and inform tasks together and then finds the optimum positions for monitoring. Both strategies utilize information as soon as it becomes available to determine UAV tasks. The strategies can be tuned to prioritize certain tasks in relation to others. We illustrate that more tasks can be performed in the given mission time by efficient incorporation of communication in the path design. We also observe that the quality of the resultant paths improves in terms of connectivity.

Abstract: Small drones are being utilized in monitoring, transport, safety and disaster management, and other domains. Envisioning that drones form autonomous networks incorporated into the air traffic, we describe a high-level architecture for the design of a collaborative aerial system consisting of drones with on-board sensors and embedded processing, coordination, and networking capabilities. We implement a multi-drone system consisting of quadcopters and demonstrate its potential in disaster assistance, search and rescue, and aerial monitoring. Furthermore, we illustrate design challenges and present potential solutions based on the lessons learned so far.

Abstract: The papers in this special issue focus on the deployment of video over future networks. The past decade has seen how major improvements in broadband and mobile networks have led to widespread popularity of video streaming applications, and how the latter now becomes the major driving force behind exponentially growing Internet traffic. This special issue seeks to investigate these future Internet technologies through the prism of its most prevalent application, that of video communications. video.

Abstract: Small drones are being utilized in monitoring, delivery of goods, public safety, and disaster management among other civil applications. Due to their sizes, capabilities, payload limitations, and limited flight time, it is not far-fetched to expect multiple networked and coordinated drones incorporated into the air traffic. In this paper, we describe a high-level architecture for the design of a collaborative aerial system that consists of drones with on-board sensors and embedded processing, sensing, coordination, and communication&networking capabilities. We present a multi-drone system consisting of quadrotors and demonstrate its potential in a disaster assistance scenario. Furthermore, we illustrate the challenges in the design of drone networks and present potential solutions based on the lessons we have learned so far.

Abstract: This paper describes a design framework for TCPfriendly and media-friendly rate control algorithms for multimedia streaming applications. The idea of this framework is to start from TFRC’s (TCP-Friendly Rate Control) transmission rate and then alter this transmission rate so that it tracks the media characteristics of the stream (e.g., bitrate) or other application characteristics like the client buffer fill level. In this way, the media-friendly property of the algorithm is achieved. We give three rules that guide how the TFRC throughput should track the evolution of the stream’s media characteristics and remain TCPfriendly in the long term. We also present, as proof of concept, four simple media-friendly and TCP-friendly congestion control algorithms built using the aforementioned framework. These congestion control algorithms are better suited for multimedia streaming applications than traditional TCP congestion control or smooth congestion control algorithms like TFRC. We have performed evaluations of two of the four proposed media-friendly and TCP-friendly congestion control algorithms under various network conditions and validated that they represent viable transport solutions, better than TFRC, for variable bitrate video streams. More specifically, our two media-friendly and TCPfriendly congestion control algorithms maintained a TCP-friendly throughput in the long term in all experiments and avoided an empty buffer at the client side in situations when TFRC could not achieve this.

Abstract: The core problem for any adaptive video streaming solution, particularly over wireless networks, is the detection (or even prediction) of congestion. IEEE 802.11 is especially vulnerable to fast movement and change of antenna orientation. When used in UAV networks (Unmanned Aerial Vehicles), the network throughput can vary widely and is almost impossible to predict. this paper evaluates an approach originally developed by Kofler for home networks, in a single-hop UAV wireless network setting: the delay between the sending of an IEEE 802.11 packet and the receipt of its corresponding acknowledgement is used as an early indicator of the link quality and as a trigger to adapt (reduce or increase) the video stream' s bitrate. Our real-world flight-tests indicate, that this avoids congestion and can frequently avoid the complete loss of video pictures which happens without adaptation.

Abstract: The navigation features of video players are often used for interactive search in videos, when users want to find a specific segment. Especially non-experts make use of these navigation facilities because they typically do not have any video retrieval tool at hand and - maybe more important - the navigation features of video players are very easy to use. However, in order to design professional video browsing tools that allow for better search performance but still provide ease of use, we need to know how users search with common video players. Therefore, we analyze logging data from a user study with 17 participants that performed Known Item Search tasks with an HTML5 video player. We classify search behavior by type of interaction and speed of interactive search and discuss what we can learn for the design and development of professional video search tools.

Abstract: Secure communication is often based on encryption thus hinges on (public-key) infrastructures that handle all the key-management. This inevitably requires human intervention, thus creating a rather vulnerable point in the system. So it appears desirable to automate key-management tasks to the widest possible extent. In this work, we report on a software implementation of secure multipath transmission. Our system takes a network infrastructure model as input and determines the maximal achievable security for a communication between a chosen sender and receiver, while handling all key-management transparently for the user. The security is information-theoretic, and unlike public-key or symmetric cryptography does neither hinge on computational intractability nor empirical evidence. More importantly, security can be measured in quantitative terms, thus making the results useful in enterprise risk management. Our software computes the risk for a given transmission under multipath transmission and generates simple OmNet++ models to demonstrate the channel construction as practically doable and to measure the additional network overhead. This is for a-priori decision-support and practical guidance for an installation of secure multipath transmission as a high-security transmission service within the enterprise network.

Abstract: Why do people record videos and share them? While the question seems to be simple, user intentions have not yet been investigated for video production and sharing. A general taxonomy would lead to adapted information systems and multimedia interfaces tailored to the users' intentions. We contribute (1) an exploratory user study with 20 participants, examining the various facets of user intentions for video production and sharing in detail and (2) a novel set of user intention clusters for video production, grounded empirically in our study results. We further reflect existing work in specialized domains (i.e. video blogging and mobile phone cameras) and show that prevailing models used in other multimedia fields (e.g. photography) cannot be used as-is to reason about video recording and sharing intentions.

Abstract: Cloud computing is currently gaining enormous momentum due to a number of promised benefits: ease of use in terms of deployment, administration, and maintenance, along with high scalability and flexibility to create new services. However, as more personal and business applications migrate to the cloud, service quality will become an important differentiator between providers. In particular, quality of experience as perceived by users has the potential to become the guiding paradigm for managing quality in the cloud. In this article, we discuss technical challenges emerging from shifting services to the cloud, as well as how this shift impacts QoE and QoE management. Thereby, a particular focus is on multimedia cloud applications. Together with a novel QoE-based classification scheme of cloud applications, these challenges drive the research agenda on QoE management for cloud applications.

Abstract: This discussion paper attempts to propose emergency response and disaster management as worthwhile areas of applied research for the informa-tion system community. The typical requirements, entities and activities in-volved in specifically mobile emergency response operations are summarized. Recent research contributions in this area are exemplarily reviewed in order to give a deeper insight into the role and use of mobile information and communi-cation systems. Finally, the major challenges and research needs regarding in-formation systems are summarized, with a view to draw the attention of infor-mation systems researchers to this interesting and important field.

Abstract: In multimedia applications, XML is being increasingly used to represent metadata; examples are MPEG-7 multimedia description schemes and MPEG-21 usage environment descriptions. As with the media data, the size of, or the overhead induced by, the XML metadata is important, particularly when used on constrained mobile devices. Therefore, compression (binary encoding) of the XML data becomes relevant to reduce this overhead. Within the MPEG-7 standardization effort, a Binary Format for Metadata (BiM) was developed, ´providing good compression efficiency and facilitating random access into, and manipulation of, the binary encoded bit stream. However, using binary encoded XML should not introduce interoperability issues with existing applications, nor add additional complexity to new applications. In this paper we investigate a solution for this issue by handling the binary encoded XML data by the XML parser. As such, applications do not need to be aware of the type of encoding of the XML data. In this paper, we introduce such an XML parser and evaluate its usability in different scenarios. We measure the memory requirements and compare the processing speed of parsing binary encoded XML to plain text XML.

Abstract: This paper presents an inexpensive cluster-based QoS networking testbed that can be employed to \emulate" different networks for multimedia communication ex-periments. Such a network can be built using standard PC and Ethernet hardware and open-source software components, e.g., IP routing and traÆc control avail- able in recent Linux kernels as well as a Differentiated Services package built atop these building blocks. The testbed can exibly be configured to model various link bandwidths as well as IP routers capable of classifying, queuing (with various disciplines), forward-ing and/or dropping packets and shaping traÆc. The QoS components and facilities of the testbed are in-troduced and initial performance analysis experiments and results are reported. A simple video streaming application under QoS control is presented to show the usefulness of the testbed.

Abstract: This paper describes an unconventional way to apply a performance analysis tool for parallel programs (Vampir) to understand and tune the performance of the real-time voice and data communication software running on top of Frequentis’ V4 switch. The execution schedule of the strictly time-triggered V4 switching software is computed off-line; analyzing the schedule to identify e.g. performance bottlenecks used to be a complex and time-consuming process. We present our approach to transform the V4 software schedule’s information into Vampir trace files and use this tool’s facilities to provide a visualization of the schedule. A case study illustrates the benefits of this approach.

Abstract: Low latencies for small messages are an important factor of efficient fine-grained parallel computation. The Active Messages concept provides this minimal overhead by eliminating certain parts of the critical path of sending and receiving messages, that is the context switch into the operating system kernel when using user-mode I/O, and multiple buffering in the network layer. Hardware-supported distributed shared memory (DSM) architectures exhibit various properties that make them particularly useful for an implementation of the aforementioned messaging mechanisms. This paper thus describes the concept, implementation, and the performance of a DSM-based Active Messages layer.