In recent years, Dynamic Adaptive Streaming over HTTP (DASH) has emerged as a popular adaptive video streaming technique to improve the bandwidth utilization. Moreover, DASH with segment-based flexibility also brings a potential benefit for the end user's Quality of Experience (QoE)1. Despite the tremendous popularity of technology like DASH, video delivery over the mobile networks is still facing some serious challenges.

In recent years, an unprecedented growth in the usage of mobile devices for web browsing poses a challenge for the service providers to assure the user-perceived quality. In the context of web quality of experience (QoE), quality perception is mostly dominated by the page load time (PLT). HTTP/2 protocol, with the server push feature, promises to address the design limitations of HTTP/1.1 that inhibit optimal web performance. However, it remains largely unclear if HTTP/2 can really improve web QoE for mobile browsing. In this paper, we experimentally investigate the web QoE with HTTP/2. We assess the web QoE for several popular websites on a controlled testbed emulated with real 4G/LTE and 3G network traces. Our experiments investigate the impact of both network latency and packet loss ratio on the mobile web QoE. The results clearly show 24% improvement in the PLT, on an average, with HTTP/2 over mobile networks. However, we identify that HTTP/2 with server push is necessarily not the fail-safe solution for improving mobile web QoE under all conditions. We noticed that HTTP/2 loads the web pages slower than HTTP/1.1 when the network packet loss ratio is more than 2%. Our study could be used as the basis to derive a set of guidelines on the usage of the HTTP/2 server push to improve the end-user web QoE, especially in mobile devices.

Dynamic adaptive streaming over HTTP (DASH) is widely used for video streaming on mobile devices. Ensuring a good quality of experience (QoE) for mobile video streaming is essential, as it severely impacts both the network and content providers' revenue. Thus, a good rate adaptation algorithm at the client end that provides high QoE is critically important. Recently, a segment size-aware rate adaptation (SARA) algorithm was proposed for DASH clients. However, its performance on mobile clients has not been investigated so far. The main contributions of this article are twofold: (1) We discuss SARA's implementation for mobile clients to improve the QoE in mobile video streaming, one that accurately predicts the download time for the next segment and makes an informed bitrate selection, and (2) we developed a new parametric QoE model to compute a cumulative score that helps in fair comparison of different adaptation algorithms. Based on our subjective and objective evaluation, we observed that SARA for mobile clients outperforms others by 17% on average, in terms of the Mean Opinion Score, while achieving, on average, a 76% improvement in terms of the interruption ratio. The score obtained from our new parametric QoE model also demonstrates that the SARA algorithm for mobile clients gives a better QoE among all the algorithms.

With the widespread use of dynamic adaptive streaming over HTTP (DASH) for delivering videos in the Internet, assuring an acceptable quality of experience (QoE) to the end-user is vital. Due to the use of conventional TCP for DASH, the QoE gets affected by well-known characteristics of mobile networks. MultiPath TCP (MPTCP), an extension of TCP, addresses the several limitations of TCP by utilizing the bandwidth on two or more network paths simultaneously. In this work, we investigate the influence of MPTCP on the QoE in mobile networks. We implement three common DASH adaptation algorithms on an emulated DASH over TCP testbed and assess the QoE using objective metrics. The experimental results demonstrate a significant improvement in the QoE by using MPTCP for DASH.

Judicious usage of battery during video streaming on mobile devices is crucial for its longer operational lifetime. In this paper, we conduct experiments to measure the energy footprint of popular dynamic adaptive streaming over HTTP (DASH) rate adaptation algorithms implemented on a mobile device. We analyzed the inherent trade-offs between energy consumption and quality of experience (QoE) with these rate adaptation algorithms. Our experimental results demonstrate that, the adaptation algorithms having lower energy consumption do not necessarily provides better QoE in terms of average bitrate played and number of playback Interruptions. Our results also highlight the category of rate adaptation algorithms that can save energy while ensuring a reasonable QoE.

HTTP based adaptive streaming technologies have become the primary vehicle for delivering live video content on the Internet. The WebRTC stack has opened up the possibility of creating a purely browser based and plugin free mechanism of utilizing peer to peer upload bandwidth to assist HTTP based streaming systems and hence make them easier to scale. Accordingly, we have implemented a WebRTC-based peer assisted framework for HTTP live streaming. We have further experimentally evaluated its performance with varying peer density. Our experimental results reveals that our framework reduces more than three fourth of the server load by serving the segment request from the neighbouring peers.

Dynamic adaptive streaming over HTTP (DASH) is gaining popularity for video streaming over the Internet. DASH uses a rate adaptation algorithm to adapt the bitrate played continuously based on the network conditions. Most of the algorithms use buffer occupancy, throughput, or a combination thereof to adapt the bitrate. In the literature, the Quality of Experience (QoE) of users is measured objectively using metrics such as, number of interruptions and their duration, average bitrate played, and the number of bitrate switches. In this work, we propose a score-based approach to assess the user experience of different rate adaptation algorithms objectively. We experimented with five algorithms implemented using an HTML5 player under varying bandwidth and network conditions. Our results demonstrate that algorithms considering both measured bandwidth and playback buffer occupancy lead to better QoE even under low bandwidth conditions. We show that buffer-based algorithms do not work well in networks with low bandwidth. Algorithms that only try to improve the bitrate played often end up with more interruptions or bitrate switches when bandwidth fluctuates. Due to the mutual dependency among the objective metrics, most of the algorithms do not necessarily improve overall QoE while selecting appropriate bitrate.

Cognitive Radio has been the key technology for dynamic spectrum access in wireless networks. Cognitive Radio seems to be a promising solution to the radio spectrum overcrowding problem as well. Cognitive Radio Network allows opportunistic usage of the spectrum holes by enabling the coexistence of licensed (primary) users and unlicensed (secondary) users. The existing wireless legacy network protocols limit the productive utilization of spectrum holes by the secondary users. The contribution of this paper is a cross-layer based location-aware forwarding protocol, using a distributed TDMA MAC, for ad-hoc Cognitive Radio Networks. The distributed TDMA based MAC protocol constructs TDMA schedules by exchanging three rounds of control messages with collision avoidance among secondary users as a fundamental goal. Exchange of control messages takes place over a common control channel in a distributed fashion. The MAC protocol also uses the service of network layer, which classifies the available channels and selects the best ranked channel and passes this information to the MAC sub-layer for effective communication. The proposed location-aware forwarding protocol constructs request zone for making decisions regarding data packet forwarding with highest packet delivery ratio, by confining the flooding of packets, as a key objective. Simulation results show the efficacy of the proposed cross-layer scheme.

With the widespread use of dynamic adaptive streaming over HTTP (DASH) for online video streaming, ensuring the user's quality of experience (QoE) is of importance to both service and network providers to improve their revenue. DASH aims to adapt the bitrate based on the available bandwidth, while minimizing the number of playback interruptions. This is typically achieved with a rate adaptation algorithm, that chooses an appropriate representation for the next video segment. Most of the algorithms use buffer occupancy, measured throughput, or a combination of these to decide the best representation for next segment. In this paper, we investigate the influence of rate adaptation algorithms on the QoE metrics. We implement five different rate adaptation algorithms and experimentally evaluate them under varying bandwidth and network scenarios. We use objective metrics such as, playback start time, average bitrate played, number of bitrate switching events, number of interruptions and duration of the interruptions to assess the QoE. Our results demonstrate that algorithms that consider both throughput and buffer occupancy results in better QoE. Further, we observe that algorithms considering segment size remove the interruptions alongside improving average bitrate played. We observe that due to the mutual dependency of QoE metrics, most of the algorithms do not necessarily improve QoE while selecting the best bitrate.

Cognitive Radio (CR) seems to be a promising solution to radio spectrum overcrowding problem. Cognitive Radio Network (CRN) allows opportunistic uses of spectrum holes by enabling the coexistence of licensed (primary) users and unlicensed (secondary) users. Data dissemination in a CRN is very useful to propagate non-urgent messages in order to limit cost and complexity of the network. MAC protocols in existing legacy wireless networks do not support the coexistence of licensed and secondary users. This limits the productive utilization of spectrum holes by secondary users. In this paper, we propose a distributed TDMA based MAC protocol for data dissemination in multi-hop ad-hoc CRNs. Our protocol aims at not only ensuring highest message reachability but also avoiding collision among secondary users. It classifies the set of available channels based on both primary radio unoccupancy and number of cognitive radio neighbours having the channel in their available channel set. The secondary users prepare a TDMA schedule using a distributed approach. Secondary users select the best channel from the available channel set using a channel selection strategy. This increases data dissemination reliability in multi-hop ad-hoc CRNs. Simulation results show the efficacy of proposed method. © 2013 IEEE.