Mobile Edge Computing (MEC) and Fog are emerging computing models that extend the cloud and its services to the edge of the network. The emergence of both MEC and fog introduce new requirements, which mean their supported deployment models must be investigated. In this paper, we point out the influence and strong impact of the extended cloud (i.e., the MEC and fog) on existing communication and networking service models of the cloud. Although the relation between them is fairly evident, there are important properties, notably those of security and resilience, that we study in relation to the newly posed requirements from the MEC and fog. Although security and resilience have been already investigated in the context of the cloud -to a certain extent -existing solutions may not be applicable in the context of the extended cloud. Our approach includes the examination of models and architectures that underpin the extended cloud, and we provide a contemporary discussion on the most evident characteristics associated with them. We examine the technologies that implement these models and architectures, and analyse them with respect to security and resilience requirements. Furthermore, approaches to security and resilience-related mechanisms are examined in the cloud (specifically, anomaly detection and policy based resilience management), and we argue that these can also be applied in order to improve security and achieve resilience in the extended cloud environment.

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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

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