No abstract

In HTTP Adaptive Streaming (HAS), video content is temporally divided into multiple segments, each encoded at several quality levels. The client can adapt the requested video quality to network changes, generally resulting in a smoother playback. Unfortunately, live streaming solutions still often suffer from playout freezes and a large end-to-end delay. By reducing the segment duration, the client can use a smaller temporal buffer and respond even faster to network changes. However, since segments are requested subsequently, this approach is susceptible to high round-trip times. In this letter, we discuss the merits of an HTTP/2 push-based approach. We present the details of a measurement study on the available bandwidth in real 4G/LTE networks, and analyze the induced bit rate overhead for HEVCencoded video segments with a sub-second duration. Through an extensive evaluation with the generated video content, we show that the proposed approach results in a higher video quality (+7.5%) and a lower freeze time (-50.4%), and allows to reduce the live delay compared to traditional solutions over HTTP/1.1.

No abstract

Nowadays, the Internet of Things (IoT) continues to expand at enormous rates. Smart Cities powered by connected sensors promise to transform public services from transportation to environmental monitoring and healthcare to improve citizen welfare. Furthermore, over the last few years, Fog Computing has been introduced to provide an answer to the massive growth of heterogeneous devices connected to the network. Nevertheless, providing a proper resource scheduling for delay-sensitive and data-intensive services in Fog Computing environments is still a key research domain. Therefore, in this paper, a network-aware scheduling approach for container-based applications in Smart City deployments is proposed. Our proposal has been validated on the Kubernetes platform, an open source orchestrator for the automatic management and deployment of micro-services. Our approach has been implemented as an extension to the default scheduling mechanism available in Kubernetes, enabling Kubernetes to make resource provisioning decisions based on the current status of the network infrastructure. Evaluations based on Smart City container-based applications have been carried out to compare the performance of the proposed scheduling approach with the standard scheduling feature available in Kubernetes. Results show that the proposed approach achieves reductions of 80% in terms of network latency when compared to the default scheduling mechanism.