Abstract With the proliferation of consumer virtual reality (VR) headsets and creative tools, content creators are experimenting with new forms of interactive audience experience using immersive media. Understanding user attention and behaviours in virtual environment can greatly inform the creative processes in VR. We developed an abstract VR painting and an experimentation system to study audience art encounters through eye gaze and movement tracking. The data from a user experiment with 35 participants reveal a range of user activity patterns in art exploration. Deep learning models are used to study the connections between the behavioural data and the audience’s background. The work also introduced new integrated methods to visualise user attention for content creators.

There is growing interest in point cloud content due to its central role in the creation and provision of interactive and immersive user experiences for extended reality applications. However, it is impractical to stream uncompressed point cloud sequences over communication networks to end systems because of their high throughput and low latency requirements. Several novel compression methods have been developed for efficient storage and adaptive delivery of point cloud content. However, these methods primarily focus on data metrics and neglect the influence on the actual Quality of Experience (QoE). In this paper, we conduct a user study with 102 participants to analyze the QoE of point cloud sequences and develop a QoE model that can enhance the quality of point cloud content distribution under dynamic network conditions. Our analysis is based on user opinions regarding two representative point cloud sequences, three different frame rates, three viewing distances, and two state-of-the-art point cloud compression libraries, Draco and V-PCC. The results indicate that the proposed models can accurately predict the users' quality perception, with frame rate being the most dominant QoE factor.

Accessing match statistics through second screen while watching soccer matches on TV has grown into a popular practice. Although early works have shown how gestures on touch screens performed under distracting environments, little is known regarding how specific gestures (swiping and tapping) to retrieve information on second screen affect the viewing experience of soccer games on TV. For this, a mixed-method user study, which included prototype tests of watching short clips of a soccer match, questionnaires and short interviews, was conducted with 28 participants. The results revealed that the number of people who preferred tapping was more than the number of people who favored swiping under two different second screen activity time scenarios i.e. On-Play or Off-Play. However, neither swiping nor tapping yield better performance of recalling verbatim match stats and exact comparisons in both On-Play and Off-Play. Participant evaluations in On-Play and interviews give us clues regarding such difference.

Cyber-Physical Systems (CPS) are formed through interconnected components capable of computation, communication, sensing and changing the physical world. The development of these systems poses a significant challenge, since they have to be designed in a way to ensure cyber-security without impacting their performance. This article presents the Security Cost Modelling Framework (SCMF) and shows supported by an experimental study how it can be used to measure, normalise, and aggregate the overall performance of a CPS. Unlike previous studies, our approach uses different metrics to measure the overall performance of a CPS and provides a methodology for normalising the measurement results of different units to a common Cost Unit . Moreover, we show how the Security Costs can be extracted from the overall performance measurements, which allows us to quantify the overhead imposed by performing security-related tasks. Furthermore, we describe the architecture of our experimental testbed and demonstrate the applicability of SCMF in an experimental study. Our results show that measuring the overall performance and extracting the security costs using SCMF can serve as basis to redesign interactions to achieve the same overall goal at less costs.

In times of Industry 4.0 and cyber-physical systems (CPS) providing security is one of the biggest challenges. A cyber attack launched at a CPS poses a huge threat, since a security incident may affect both the cyber and the physical world. Since CPS are very flexible systems, which are capable of adapting to environmental changes, it is important to keep an overview of the resulting costs of providing security. However, research regarding CPS currently focuses more on engineering secure systems and does not satisfactorily provide approaches for evaluating the resulting costs. This paper presents an interaction-based model for evaluating security costs in a CPS. Furthermore, the paper demonstrates in a use case driven study, how this approach could be used to model the resulting costs for guaranteeing security.

In Industry 4.0, Cyber-Physical Systems (CPS) are formed by components, which are interconnected with each other over the Internet of Things (IoT). The resulting capabilities of sensing and affecting the physical world offer a vast range of opportunities, yet, at the same time pose new security challenges. To address these challenges there are various IoT Frameworks, which offer solutions for managing and controlling IoT-components and their interactions. In this regard, providing security for an interaction usually requires performing additional security-related tasks (e.g. authorisation, encryption, etc.) to prevent possible security risks. Research currently focuses more on designing and developing these frameworks and does not satisfactorily provide methodologies for evaluating the resulting costs of providing security. In this paper we propose an initial approach for measuring the resulting costs of providing security for interacting IoT-components by using a Security Cost Modelling Framework. Furthermore, we describe the necessary building blocks of the framework and provide an experimental design showing how it could be used to measure security costs at runtime.

Distributed Renewable Energy Sources (DRESs) such as wind and solar are becoming a promising alternative for the energy supply in modern (smart) electricity grids as part of future sustainable smart cities. Successful integration of DRESs requires efficient, resilient, and secure communication in order to satisfy the highly challenging and real-time constraints of smart city applications. Regardless of the various research solutions proposed in this context within the last decade, the relevant standardization is a non-trivial issue and is still in its infancy. In this position paper, we briefly review the currently employed DRES communications standards and identify the gaps in their present status. Finally, we discuss and suggest potential pathways for further improvement.

Networked systems form the backbone of modern society, underpinning critical infrastructures such as electricity, water, transport and commerce, and other essential services (e.g., information, entertainment, and social networks). It is almost inconceivable to contemplate a future without even more dependence on them. Indeed, any unavailability of such critical systems is - even for short periods - a rather bleak prospect. However, due to their increasing size and complexity, they also require some means of autonomic formation and self-organization. This paper identifies the design principles and open research issues in the twin fields of self-organization and resilience for networked systems. In combination, they offer the prospect of combating threats and allowing essential services that run on networked systems to continue operating satisfactorily. This will be achieved, on the one hand, through the (self-)adaptation of networked systems and, on the other hand, through structural and operational resilience techniques to ensure that they can detect, defend against, and ultimately withstand challenges.

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.

HTTP adaptive video streaming matches video quality to the capacity of a changing context. A variety of schemes that rely on buffer state dynamics for video rate selection have been proposed. However, these schemes are predominantly based on heuristics, and appropriate models describing the relationship between video rate and buffer levels have not received sufficient attention. In this paper, we present a QoE-aware video rate evolution model based on buffer state changes. The scheme is evaluated within a real-world Internet environment. The results of an extensive evaluation show an improvement in the stability, average video rate and system utilisation, while at the same time a reduction in the start-up delay and convergence time is achieved by the modified players.

Resilience is an essential property for critical networked environments such as utility networks (e.g. gas, water and electricity grids), industrial control systems, and communication networks. Due to the complexity of such networked environments achieving resilience is multi-dimensional since it involves a range of factors such as redundancy and connectivity of different system components as well as availability, security, dependability and fault tolerance. Hence, it is of importance to address resilience within a unified framework that considers such factors and further enables the practical composition of resilience mechanisms. In this paper we firstly introduce the concepts and principles of Multi-Level Resilience (MLR) and then demonstrate its applicability in a particular cloud-based scenario.

Cloud computing is now extremely popular because of its use of elastic resources to provide optimized, cost-effective and on-demand services. However, clouds may be subject to challenges arising from cyber attacks including DoS and malware, as well as from sheer complexity problems that manifest themselves as anomalies. Anomaly detection techniques are used increasingly to improve the resilience of cloud environments and indirectly reduce the cost of recovery from outages. Most anomaly detection techniques are computationally expensive in a cloud context, and often require problem-specific parameters to be predefined in advance, impairing their use in real-time detection. Aiming to overcome these problems, we propose a technique for anomaly detection based on data density. The density is computed recursively, so the technique is memory-less and unsupervised, and therefore suitable for real-time cloud environments. We demonstrate the efficacy of the proposed technique on a dataset created in our cloud testbed. The dataset consists of feature vectors obtained from a physical cloud testbed network experiencing migration under controlled traffic conditions modelling scenarios combining normal network use with network-based attacks. The obtained results, which include precision, recall, accuracy, F-score and G-score, show that network level attacks are detectable with high accuracy.

Named Data Networking (NDN) is a novel architecture expected to overcome limitations of the current Internet. User mobility is one of the most relevant limitations to be addressed. NDN supports consumer mobility by design but fails to offer the same level of support for producer mobility. Existing approaches to extend NDN are host-centric, which conflicts with NDN principles, and provide limited support for producer mobility. This paper proposes a content-centric strategy that replicates and pushes objects proactively, and unlike previous approaches, takes full advantage of NDN routing and caching features. We compare the proposed strategy with default NDN mechanisms regarding content availability, consumer performance, and network overhead. The evaluation results indicate that our strategy can increase the hit rate of objects by at least 46% and reduce their retrieval time by over 60%, while not adding significant overhead.

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.

Cloud services are prominent within the private, public and commercial domains. Many of these services are expected to be always on and have a critical nature; therefore, security and resilience are increasingly important aspects. In order to remain resilient, a cloud needs to possess the ability to react not only to known threats, but also to new challenges that target cloud infrastructures. In this paper we introduce and discuss an online cloud anomaly detection approach, comprising dedicated detection components of our cloud resilience architecture. More specifically, we exhibit the applicability of novelty detection under the one-class support Vector Machine (SVM) formulation at the hypervisor level, through the utilisation of features gathered at the system and network levels of a cloud node. We demonstrate that our scheme can reach a high detection accuracy of over$90$percent whilst detecting various types of malware and DoS attacks. Furthermore, we evaluate the merits of considering not only system-level data, but also network-level data depending on the attack type. Finally, the paper shows that our approach to detection using dedicated monitoring components per VM is particularly applicable to cloud scenarios and leads to a flexible detection system capable of detecting new malware strains with no prior knowledge of their functionality or their underlying instructions.

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.

Networked infrastructures underpin most social and economical interactions nowadays and have become an integral part of the critical infrastructure. Thus, it is crucial that heterogeneous networked environments provide adequate resilience in order to satisfy the quality requirements of the user. In order to achieve this, a coordinated approach to confront potential challenges is required. These challenges can manifest themselves under different circumstances in the various infrastructure components. The objective of this paper is to present a multi-level resilience approach that goes beyond the traditional monolithic resilience schemes that focus mainly on one infrastructure component. The proposed framework considers four main aspects, i.e. users, application, network and system. The latter three are part of the technical infrastructure while the former profiles the service user. Under two selected scenarios this paper illustrates how an integrated approach coordinating knowledge from the different infrastructure elements allows a more effective detection of challenges and facilitates the use of autonomic principles employed during the remediation against challenges.

Resilience is the ability of the network to maintain an acceptable level of operation in the face of anomalies, such as malicious attacks, operational overload or misconfigurations. Techniques for anomaly traffic classification are often used to characterize suspicious network traffic, thus supporting anomaly detection schemes in network resilience strategies. In this paper, we extend the PReSET toolset to allow the investigation, comparison and analysis of algorithms for anomaly traffic classification based on machine learning. PReSET was designed to allow the simulation-based evaluation of resilience strategies, thus enabling the comparison of optimal configurations and policies for combating different types of attacks (e.g., DDoS attacks, worms) and other anomalies. In such resilience strategies, policies written in the Ponder2 language can be used to activate/reconfigure traffic classification modules and other mechanisms (e.g., traffic shaping), depending on monitored results in the simulation environment. Our results show that PReSET can be a valuable tool for network operators to evaluate anomaly traffic classification techniques in terms of standard performance metrics.

The past two decades have seen a shift in the multimedia consumption behaviours from that of collectivism and passivity, to individualism and activity. This paper introduces the architectural design, implementation and user evaluation of a second screen application, which is designed to supersede the traditional user control interface for primary screen interaction. We describe how NSMobile, our second screen application, can be used as a pervasive multimedia platform by integrating user experiences on both the second screen and primary screen. The quantitative and qualitative evaluation of user interactions with interactive TV content also contributes to the future design of second screen applications.

Adaptive bitrate selection adjusts the quality of HTTP streaming video to a changing context. A number of different schemes have been proposed that use buffer state in the selection of the appropriate video rate. However, models describing the relationship between video quality levels and buffer occupancy are mostly based on heuristics, which often results in unstable and/or suboptimal quality. In this paper, we present a QoE-aware video rate evolution model based on buffer state changes. The scheme is evaluated within a real world Internet environment, where it is shown to improve the stability of the video rate. Up to 27% gain in average video rate can be achieved compared to the baseline ABR. The average throughput utilisation at a steady-state reaches 100% in some of the investigated scenarios.

The world's computing infrastructure is increasingly differentiating into self-contained sub-systems (e.g. Internet of Things installations, clouds, VANETs, ...), which are post-hoc composed to generate value-added functionality (“systems of systems”). Today, however, such system-of-systems composition is typically carried out in an ad-hoc and infrastructure-dependent manner, with obvious associated disadvantages. In this paper, we propose a generalised system-of-systems-oriented programming approach that enables programmers to manage the composition of systems without a need for intimate knowledge of their internals, and also facilitates dynamic and spontaneous system composition, as systems discover each other opportunistically in their environment.

Data with high security requirements is being processed and stored with increasing frequency in the Cloud. To guarantee that the data is being dealt in a secure manner we investigate the applicability of Assurance methodologies. In a typical Cloud environment the setup of multiple layers and different stakeholders determines security properties of individual components that are used to compose Cloud applications. We present a methodology adapted from Common Criteria for aggregating information reflecting the security properties of individual constituent components of Cloud applications. This aggregated information is used to categorise overall application security in terms of Assurance Levels and to provide a continuous assurance level evaluation. It gives the service owner an overview of the security of his service, without requiring detailed manual analyses of log files.

Software-defined networking provides abstractions and a flexible architecture for the easy configuration of network devices, based on the decoupling of the data and control planes. This separation has the potential to considerably simplify the implementation of resilience functionality (e.g., traffic classification, anomaly detection, traffic shaping) in future networks. Although software-defined networking in general, and OpenFlow as its primary realisation, provide such abstractions, support is still needed for orchestrating a collection of OpenFlow-enabled services that must cooperate to implement network-wide resilience. In this paper, we describe a resilience management framework that can be readily applied to this problem. An important part of the framework are policy-controlled management patterns that describe how to orchestrate individual resilience services, implemented as OpenFlow applications.

Due to the lack of multicast services in the Internet, applications based on single-source, multiple-destination transfers such as video conferencing, IP radio, and IPTV must use unicast. This type of traffic exhibits high redundancy with temporal clustering of duplicated packets. The redundancy originates from multiple transfers of the same data chunk over the same link. We propose CacheCast, a link-layer caching mechanism that eliminates the redundant data transmissions using small caches on links. CacheCast's underlying principles are simplicity and reliability. It is a fully distributed and incrementally deployable architecture. It consists of small caches on links that act independently and a server support that simplifies the link cache operation. Our analysis indicates that transfers of the same data to multiple destinations with CacheCast can achieve near-multicast efficiency in terms of consumed link bandwidth. The implementation of CacheCast proves its feasibility, efficiency, and the improvements of the server.

Data-sets derived from subjective experiments are often exploited to construct objective quality models using parametric statistics such as MOS and multiple regression. In this paper, using data type and normality tests, we verify that non-normally distributed user opinion scores in nominal or ordinal responses should not be analysed using parametric statistics. The paper introduces a number of non-parametric statistics for valid model building and parameter estimation based on user opinion scores. A set of modelling results are also presented to demonstrate the effectiveness of non-parametric statistics.

This paper proposes a new delivery-centric abstraction. A delivery-centric abstraction allows applications to generate content requests agnostic to location or protocol, with the additional ability to stipulate high-level requirements regarding such things as performance, security, resource consumption and monetary cost. A delivery-centric system therefore constantly adapts to fulfil these requirements, given the constraints of the environment. This abstraction has been realised through a delivery-centric middleware called Juno, which uses a reconfigurable software architecture to (i) discover multiple sources of an item of content, (ii) model each source's ability to provide the content, then (iii) adapt to interact with the source(s) that can best fulfil the application's requirements. Juno therefore utilises existing providers in a backwards compatible way, supporting immediate deployment. This paper evaluates Juno using Emulab to validate its ability to adapt to its environment.

A content-centric network is one which supports host-to-content routing, rather than the host-to-host routing of the existing Internet. This paper investigates the potential of caching data at the router-level in content-centric networks. To achieve this, two measurement sets are combined to gain an understanding of the potential caching benefits of deploying content-centric protocols over the current Internet topology. The first set of measurements is a study of the BitTorrent network, which provides detailed traces of content request patterns. This is then combined with CAIDA's ITDK Internet traces to replay the content requests over a real-world topology. Using this data, simulations are performed to measure how effective content-centric networking would have been if it were available to these consumers/providers. We find that larger cache sizes (10,000 packets) can create significant reductions in packet path lengths. On average, 2.02 hops are saved through caching (a 20% reduction), whilst also allowing 11% of data requests to be maintained within the requester's AS. Importantly, we also show that these benefits extend significantly beyond that of edge caching by allowing transit ASes to also reduce traffic.

Network resilience strategies aim to maintain acceptable levels of network operation in the face of challenges, such as malicious attacks, operational overload or equipment failures. Often the nature of these challenges requires resilience strategies comprising mechanisms across multiple protocol layers and in disparate locations of the network. In this paper, we address the problem of resilience management and advocate that a new approach is needed for the design and evaluation of resilience strategies. To support the realisation of this approach we propose a framework that enables (1) the offline evaluation of resilience strategies to combat several types of challenges, (2) the generalisation of successful solutions into reusable patterns of mechanisms, and (3) the rapid deployment of appropriate patterns when challenges are observed at run-time. The evaluation platform permits the simulation of a range of challenge scenarios and the resilience strategies used to combat these challenges. Strategies that can successfully address a particular type of challenge can be promoted to become resilience patterns. Patterns can thus be used to rapidly deploy resilience configurations of mechanisms when similar challenges are detected in the live network.

There is a gap between the increasing complexity of computer networks and the human operators ability to manage them. This gap, likely to become bigger in the coming years, needs to be addressed by more dynamic and autonomic management techniques. The ultimate aim is to provide the network with the functionality to manage itself. This paper outlines an architecture which provides support to facilitate self-organisation in a network's management/control plane. The central element of this research is a novel message-passing framework, facilitating de-composition and dynamic composition of services. The overall design of the autonomic network management architecture is first introduced but the focus is on the communication protocols and interactions between Atomic Functional Blocks, the basic auto-nomic management elements that provide a network management service.

In recent years, the ubiquity of multimedia services along with the proliferation of mobile devices and the demand for new audio and video applications are changing the lifestyle of users.The multimedia era is allowing users to create, distribute, and access content in ubiquitous way and cost-effectively, while providers explore new ways to increase their revenues.The efficient delivery of real-time multimedia services over emerging diverse and heterogeneous systems is a challenging research goal.The interoperability of applications, transport and network protocols as well as the demand for improved Quality of Experience (QoE) create new challenges and opportunities for further research on novel communication protocols, architectures, and methods to efficiently support current and future multimedia networking systems.In 2010, the Third International Future Multimedia Networking (FMN 2010) workshop was organized in Kraków, Poland and achieved a success attracting numerous submissions from various countries.FMN 2010 produced a high quality peer reviewed technical programme with an acceptance rate at around 24% and addressed important aspects of future multimedia systems with a focus on QoE.Authors of selected papers from FMN 2010 were invited to submit extended versions of their papers in order to be considered for inclusion in this Special issue on Future Multimedia.

This article proposes a new delivery-centric abstraction which extends the existing content-centric networking API. A delivery-centric abstraction allows applications to generate content requests agnostic to location or protocol, with the additional ability to stipulate high-level requirements regarding such things as performance, security, and resource consumption. Fulfilling these requirements, however, is complex as often the ability of a provider to satisfy requirements will vary between different consumers and over time. Therefore, we argue that it is vital to manage this variance to ensure an application fulfils its needs. To this end, we present the Juno middleware, which implements delivery-centric support using a reconfigurable software architecture to: (i) discover multiple sources of an item of content; (ii) model each source’s ability to provide the content; then (iii) adapt to interact with the source(s) that can best fulfil the application’s requirements. Juno therefore utilizes existing providers in a backwards compatible way, supporting immediate deployment. This article evaluates Juno using Emulab to validate its ability to adapt to its environment.

Peer-to-Peer (P2P) technologies provide efficient and low-cost delivery for commercial and user-generated content. Although a number of audio-visual content distribution services have been developed using P2P-based mechanisms, it is still a challenge to guarantee satisfactory user experience on high quality video streaming services due to the dynamic nature of P2P distribution. An objective assessment service is the key enabler of service quality monitoring and management. However, this complex task can not be achieved by any individual objective model that only captures a certain aspect of service quality. This paper introduces a multimodal quality evaluation framework that is specifically designed and implemented for the assessment of video streaming services in P2P-based IPTV systems. Results of initial experiments show the effectiveness of this framework.

In recent years, the ubiquity of multimedia services along with the proliferation of mobile devices and the demand for new audio and video applications are changing the life style of users.The multimedia era is allowing users to create, distribute, and access content in ubiquitous way and cost-effectively, while providers explore new ways to increase their revenues.The efficient delivery of real-time multimedia services over emerging diverse and heterogeneous systems is a challenging research goal.The interoperability of applications, transport and network protocols as well as the demand for improved Quality of Service (QoS), Quality of Experience (QoE), and seamless mobility create new challenges and opportunities for further research on novel communication protocols, architectures, and methods to efficiently support current and future multimedia networking systems.In 2009, the Second International Future Multimedia Networking (FMN 2009) workshop was organized in Coimbra, Portugal and achieved exceptional success attracting 64 submissions from 33 countries.FMN 2009 produced a high quality peer reviewed technical programme with an acceptance rate at around 25% and addressed important aspects of future multimedia systems with a focus on Autonomic Content Networks.Authors of selected papers from FMN 2009 were invited to submit extended versions of their papers in order to be considered for inclusion in this Special issue on Future Multimedia.These papers were peer-reviewed again and then further revised by the authors.

In recent years, the ubiquity of multimedia services along with the proliferation of mobile devices and the demand for new audio and video applications are changing the life style of users. User demands for multimedia access anywhere, anytime from any device are creating new challenges for research communities from both academia and industry. It is expected that video-based services alone will account for 50 percent of all consumer network traffic in 2012 and we will continue to witness the explosive growth in users sharing multimedia content over the Internet. In this context, new network, application, and user-based approaches must be created to deal with such complex multimedia systems. This paper presents some of the recent advances in multimedia networking focusing primarily on areas that have been receiving attention recently and are expected to continue to generate further interests in coming years. These areas include Quality of Experience (QoE) and various related standardization issues, Content Distribution Networks (CDNs), multimedia communications, mobile Multimedia. This paper also briefly highlights some of the major challenges that still need to be addressed to enable the support and delivery of multimedia services anywhere, anytime over highly heterogeneous infrastructures and user terminal devices.

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.

Due to the lack of multicast services in the Internet, applications based on single source multiple destinations transfers such as video conferencing, IP radio, IPTV must use unicast or application layer multicast. This in turn has several well-known drawbacks. A basic insight is that this type of traffic exhibits high redundancy with temporal clustering of duplicated packets. The redundancy originates from multiple transfers of the same data chunk over the same link. We propose CacheCast-a link layer caching mechanism-that eliminates the redundant data transmissions using small caches on links. CacheCast's underlying principles are simplicity and reliability. It is a fully distributed and incrementally deployable architecture. It consists of small caches on links that act independently. A single cache removes redundant data from a packet on the link entry and recovers the data on the link exit. Thus, link caches are transparent to routers. We show through analysis and simulation that CacheCast achieves near multicast efficiency for superposition of unicast connections. We implemented CacheCast in ns-2 and show that it does not violate the current understanding of "fairness" in the Internet.

Network impairments are unpredictable and highly destructive to the perceptual quality of media content in the IPTV content distribution networks. As a result the existing network QoS based assessment methodologies are not adequate for the IPTV QoE assessment which determines the overall acceptability of a service as perceived by the end user. A discrete perceptual impact evaluation quality assessment framework (DEQA) is introduced in this paper. The proposed framework enables a real-time, non-intrusive assessment service by efficiently recognising and assessing the individual IPTV quality violation events in the distribution network. The discrete perceptual impacts to a media session are aggregated for the overall user level quality evaluation. With its deployment scheme, the DEQA framework also facilitates efficient network diagnosis and QoE management. Recent work on realising the functions of the framework is also presented.

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.

A hierarchical DHT overlay architecture based on P2PSIP is proposed to support a skype-like service. The IETF P2PSIP working group is standardizing a protocol to support any DHT in order to deploy services inside a domain. We extend its functionality to allow the interaction between peers of different domains. Furthermore, we perform an analysis of the routing performance and resource consumption under a skype-like scenario where VoIP calls are more likely to happen among users of the same domain.

The scalability properties of DHT based overlay networks is considered satisfactory. However, in large scale systems this might still cause a problem since they have a logarithmic complexity depending. Further, they only provide a one dimensional structure and do not make use on inherent clustering properties of some applications (e.g. P2PVoIP or locality aware overlays). Thus, structures based on a hierarchical approach can have performance as well as structural advantages. In this paper, a generic hierarchical architecture based on super-peers is presented where a peer ID is composed by a prefix ID and a suffix ID. Prefix ID is only routed at the super-peer level and the Suffix ID at the peer level. We specifically analyse the Routing Performance of this approach within the context of two specific overlays, viz. CAN and Kademlia.

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

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.

Article Share on Media semantics: who needs it and why? Authors: Chitra Dorai Organizers OrganizersView Profile , Andreas Mauthe View Profile , Frank Nack Organizers OrganizersView Profile , Lloyd Rutledge View Profile , Thomas Sikora View Profile , Herbert Zettl View Profile Authors Info & Claims MULTIMEDIA '02: Proceedings of the tenth ACM international conference on MultimediaDecember 2002 Pages 580–583https://doi.org/10.1145/641007.641123Online:01 December 2002Publication History 9citation676DownloadsMetricsTotal Citations9Total Downloads676Last 12 Months8Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access