Traditional media is delivered using segmented video, with variable bitrates, over protocols such as MPEG-DASH. This works well for media experiences with a single, or very few, pre-produced variants. When the number of possible variants increases, however, it results in an explosion of pre-produced whole-experience videos in a one-per-variant relationship; this in turn causes high storage costs and poor re-use of otherwise separable media assets. The paradigm of object-based media (OBM) offers a solution by keeping media entities distinct after production, allowing them to be combined flexibly at the point of consumption. We examine the delivery and playback of OBM using a novel WebAssembly-based media player running in the browser. This approach allows the selective render offload of parts of an experience into the edge/cloud, by migrating associated code from the browser. Using three diverse exemplars of OBM we present a common meta-data format to capture flexible experiences, and measure the performance of our delivery pipeline in a range of on-device and offloaded scenarios. As far as we are aware this is the first such study of generalised OBM media delivery.

Quality of Experience (QoE) is a key component in adaptive bitrate (ABR) streaming. Whilst the effects of delivery disruptions—such as changes in video quality or rebuffering—have been extensively studied, the impact of playback rate variations remains relatively unexplored. Existing work has examined the QoE impact of playback rate in isolation, without comparing it to other common ABR streaming artifacts such as video quality variations, rebuffering, or seeking. Moreover, the role of gradual playback rate transitions has not been explored. This article addresses these gaps through four large-scale subjective studies that provide a systematic QoE evaluation of playback rate. We compare the acceptability of playback rate changes against quality degradations and rebuffering, and assess rate increases relative to seeking, both of which are strategies for maintaining the desired latency in low-latency streaming. We further investigate how gradual versus instantaneous playback rate transitions affect QoE. Through our subjective studies, we identify levels of slowed-down playback that are imperceptible to users and can be combined with video quality adaptation in ABR algorithms to reduce rebuffering. Moreover, we identify imperceptible rates of speeded-up video playback, which can be used as part of catch-up mechanisms to maintain a desired latency in live streaming, offering a less detrimental alternative to seeking events, which we found to significantly degrade QoE. This work presents the first systematic comparison of playback rate variations with video quality degradation, rebuffering and seeking. The findings extend our understanding of QoE in adaptive video streaming and provide actionable design guidelines for video players to improve the user experience of streaming services.

Quality of Experience (QoE) is a crucial component of adaptive bitrate (ABR) streaming, with the effects of abrupt changes in playback quality or rebuffering, caused by delivery disruptions, being widely studied. However, the collective ABR community has a limited understanding of the effects of changes in playback rate on QoE. In this pioneering work, we investigate two aspects of playback rate fluctuations. In particular, we carry out two subjective studies to assess if a change in playback rate is more or less acceptable than a drop in video quality or a rebuffering event. Furthermore, we examine the effect of the transition in playback rate on QoE, comparing gradual and instant variations. Our subjective studies recruited 120 participants who evaluated 102 test sequences. In summary, we find that playback rate drops of 0.8-0.9 are imperceptible for most content, and rated similarly to a video quality drop to medium level. In contrast, lower playback rates of 0.6-0.7 were perceived as poorly as rebuffering events. Gradual changes in playback rate can offer better QoE, but only in limited cases depending on the content, target playback rate, as well as magnitude of change.

Video streaming continues to be the largest service delivered on the internet. This includes gaming videos, delivered both on-demand and live, where gaming footage is usually accompanied by a video of the player overlaid on top of the gameplay - resulting in Picture-In-Picture (PiP) content. Currently, PiP content is usually combined into a single video before being delivered to the client via technologies such as HTTP Adaptive Streaming (HAS). In this study, we investigated the QoE importance of gameplay and player elements in PiP gaming videos by varying the video quality of these elements individually. We conducted a subjective study, testing nine quality permutations based on three quality levels across three pieces of content from different gaming genres, with 30 participants recruited using an ethical crowdsourcing platform. We found that gameplay was significantly more important in terms of overall QoE, while the player element made a difference in only a few cases.

Recent multimedia experiences using techniques such as DASH allow the streaming delivery to be adapted to suit network context. Object Based Media (OBM) provides even more flexibility as distinct media objects are streamed and combined based on user preferences, allowing the experience to be personalised for the user. As adaptation can lead to degradation, modelling and measuring Quality of Experience (QoE) are crucial to ensure a perceptibly-optimal user experience. QoE models proposed for DASH include quality-related factors from single video-object streams and hence, are unsuitable for multi-video OBM experiences. In this paper, we propose an objective method to quantify QoE for video-based OBM experiences. Our model provides different strategies to aggregate individual object QoE contributions for different OBM experience genres. We apply our model to a case study and contrast it with the QoE levels obtained using a standard QoE model for DASH.

Changes in content consumption patterns of audiences has revealed an ever-increasing appetite for richer and more engaging experiences. From live-streaming to interactive branching stories, there is a growing trend of users seeking personalised experiences. Object-based media experiences provide more meaningful encounters for the young and old; tailoring these to their interest, and making them part of the story. However, creating and distributing these experiences at scale to audiences is challenging to content-providers due to device and experience heterogeneity introducing complexity in the delivery chain. In this demo, we demonstrate how using cross-platform approaches, game-engine-like runtimes, and cloud-based rendering can be combined to provide universal access to rich immersive experiences. A cross-platform runtime and build-process is used to develop experience presentation capabilities and target multiple device platforms from a single code-base. Where low-computing availability prohibits the execution of such experiences, cloud-based rendering is harnessed to still achieve playback on low-end devices without significant loss in quality of experience.

Security is one of the biggest challenges facing organisations in the modern hyper-connected world. A number of theoretical security models are available that provide best practice security guidelines and are widely utilised as a basis to identify and operationalise security requirements. Such models often capture high-level security concepts (e.g., whitelisting, secure configurations, wireless access control, data recovery, etc.), strategies for operationalising such concepts through specific security controls, and relationships between the various concepts and controls. The threat landscape, however, evolves leading to new tacit knowledge that is embedded in or across a variety of security incidents. These unknown knowns alter, or at least demand reconsideration of the theoretical security models underpinning security requirements. In this paper, we present an approach to discover such unknown knowns through multi-incident analysis. The approach is based on a novel combination of grounded theory and incident fault trees. We demonstrate the effectiveness of the approach through its application to identify revisions to a theoretical security model widely used in industry.

The innate dynamicity and complexity of mobile ad-hoc networks (MANETs) has resulted in numerous ad-hoc routing protocols being proposed. Furthermore, numerous variants and hybrids continue to be reported in the literature. This diversity appears to be inherent to the field-it seems unlikely that there will ever be a ‘one-size-fits-all’ solution to the ad-hoc routing problem. However, typical deployment environments for ad-hoc routing protocols still force the choice of a single fixed protocol; and the resultant compromise can easily lead to sub-optimal performance, depending on current operating conditions. In this paper we address this problem by exploring a framework approach to the construction and deployment of ad-hoc routing protocols. Our framework supports the simultaneous deployment of multiple protocols so that MANET nodes can switch protocols to optimise to current operating conditions. The framework also supports finer-grained dynamic reconfiguration in terms of protocol variation and hybridisation. We evaluate our framework by using it to construct and (simultaneously) deploy two popular ad-hoc routing protocols (DYMO and OLSR), and also to derive fine-grained variants of these. We measure the performance and resource overhead of these implementations compared to monolithic ones, and find the comparison to be favourable to our approach.