Video streaming is an increasingly popular way to consume media content. Adaptive video streaming is an emerging delivery technology which aims to increase user QoE and maximise connection utilisation. Many implementations naively estimate bandwidth from a one-sided client perspective, without taking into account other devices in the network. This behaviour results in unfairness and could potentially lower QoE for all clients. We propose an OpenFlow-assisted QoE Fairness Framework that aims to fairly maximise the QoE of multiple competing clients in a shared network environment. By leveraging a Software Defined Networking technology, such as OpenFlow, we provide a control plane that orchestrates this functionality. The evaluation of our approach in a home networking scenario introduces user-level fairness and network stability, and illustrates the optimisation of QoE across multiple devices in a network.
Inadequate Internet access is widening the digital divide between town and countryside, degrading both social communication and business advancements in rural areas. Wireless mesh networking can provide an excellent framework for delivering broadband services to such areas. With this in mind, Lancaster University deployed a WMN in the rural village of Wray over a three-year period, providing the community with Internet service that exceeds many urban offerings. The project gave researchers a real-world testbed for exploring the technical and social issues entailed in deploying WMNs in the heart of a small community.
Example citation: Mu, M., Broadbent, M., Farshad, A., Hart, N., Hutchison, D., Ni, Q. and Race, N. (2016) A scalable user fairness model for adaptive video streaming over SDNassisted future networks. IEEE Journal on Selected Areas in Communications. (Accepted)It is advisable to refer to the publisher's version if you intend to cite from this work. The growing demand for online distribution of high quality and high throughput content is dominating today's Internet infrastructure. This includes both production and user-generated media. Among the myriad of media distribution mechanisms, HTTP adaptive streaming (HAS) is becoming a popular choice for multi-screen and multi-bitrate media services over heterogeneous networks. HAS applications often compete for network resources without any coordination between each other. This leads to Quality of Experience (QoE) fluctuations on delivered content, and unfairness between end users. Meanwhile, new network protocols, technologies and architectures, such as Software Defined Networking (SDN), are being developed for the future Internet. The programmability, flexibility and openness of these emerging developments can greatly assist the distribution of video over the Internet. This is driven by the increasing consumer demands and QoE requirements. This paper introduces a novel user-level fairness model UFair and its hierarchical variant UFair HA , which orchestrate HAS media streams using emerging network architectures and incorporate three fairness metrics (video quality, switching impact and cost efficiency) to achieve user-level fairness in video distribution. The UFair HA has also been implemented in a purposebuilt SDN testbed using open technologies including OpenFlow. Experimental results demonstrate the performance and feasibility of our design for video distribution over future networks. Version: Accepted version
Decisions that we make about email legitimacy can result in a pernicious threat to security of both individuals and organisations. Yet user response to phishing emails is far from uniform; some respond while others do not. What is the source of this diversity in decision-making? From a psychological perspective, we consider cognitive and situational influences that might explain why certain users are more susceptible than others. Alongside an email judgment task employed as a proxy for fraud susceptibility, 224 participants completed a range of cognitive tasks. In addition, we manipulated time pressure for email legitimacy judgments. We identify cognitive reflection and sensation seeking as significant, albeit modest, predictors of susceptibility. Further to this, participants asked to make quicker responses made more judgment errors. We conclude there are cognitive signatures that partially contribute to email fraud susceptibility, with implications for efforts to limit online security breaches and train secure behaviors.
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