WhatsApp is a very popular mobile messaging application, which dominates todays mobile communication. Especially the feature of group chats contributes to its success and changes the way people communicate. The group-based communication paradigm is investigated in this work, particularly focusing on the usage of WhatsApp, communication in group chats, and implications on mobile network traffic.
Today's Internet services are increasingly accessed from mobile devices, thus being responsible for growing load in mobile networks. At the same time, more and more WiFi routers are deployed such that a dense coverage of WiFi is available. Results from different related works suggest that there is a high potential of reducing load on the mobile networks by offloading data to WiFi networks, thereby improving mobile users' quality of experience (QoE) with Internet services. Additionally, the storage of the router could be used for content caching and delivery close to the end user, which is more energy efficient compared to classical content servers, and saves costs for network operators by reducing traffic between autonomous systems. Going one step beyond, we foresee that merging these approaches and augmenting them with social information from online social networks (OSNs) will result both in even less costs for network operators and increased QoE of end users. Therefore, we propose home router sharing based on trust (HORST) -a socially-aware traffic management solution which targets three popular use cases: data offloading to WiFi, content caching/prefetching, and content delivery.
The large share of traffic in the Internet generated by video streaming services puts high loads on access and aggregation networks, resulting in high costs for the content delivery infrastructure. To reduce the bandwidth consumed while maintaining a high playback quality, video players use policies that control and limit the buffer level by using thresholds for pausing and continuing the video download. This allows shaping the bandwidth consumed by video streams and limiting the traffic wasted in case of playback abortion. Especially in mobile scenarios, where the throughput can be highly variant, the buffer policy can have a high impact on the probability of interruptions during video playback. To find the optimal setting for the buffer policy in each network condition, the relationship between the parameters of the buffer policy, the network throughput dynamics, and the corresponding video playback behavior needs to be understood. To this end, we model the video buffer as GI/GI/1 queue with
pq
-policy using discrete-time analysis. By studying the stochastic properties of the buffer-level distribution, we are able to accurately evaluate the impact of network and video bitrate dynamics on the video playback quality based on the buffer policy. We find a fundamental relationship between the bandwidth variation and the expected interarrival time of segments, meaning that overproportionately more bandwidth is necessary to prevent stalling events for high bandwidth variation. The proposed model further allows to optimize the trade-off between the traffic wasted in case of video abortion and video streaming quality experienced by the user.
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