An announcement-based caching approach for video-on-demand streaming

The growing popularity of over the top ( OTT) video streaming services has led to a strong increase in bandwidth capacity requirements in the network. By deploying intermediary caches, closer to the end-users, popular content can be served faster and without increasing backbone traffic. Designing an appropriate replacement strategy for such caching networks is of utmost importance to achieve high caching efficiency and reduce the network load. Typically, a video stream is temporally segmented into smaller chunks that can be accessed and decoded independently. This temporal segmentation leads to a strong relationship between consecutive segments of the same video. Therefore, caching strategies have been developed, taking into account the temporal structure of the video. In this paper, we propose a novel caching strategy that takes advantage of clients announcing which videos will be watched in the near future, e.g., based on predicted requests for subsequent episodes of the same TV show. Based on a Video-on-Demand (VoD) production request trace, the presented algorithm is evaluated for a wide range of user behavior and request announcement models. In a realistic scenario, a performance increase of 11% can be achieved in terms of hit ratio, compared to the state-of-the-art

Cooperative announcement-based caching for video-on-demand streaming

Recently, video-on-demand (VoD) streaming services like Netflix and Hulu have gained a lot of popularity. This has led to a strong increase in bandwidth capacity requirements in the network. To reduce this network load, the design of appropriate caching strategies is of utmost importance. Based on the fact that, typically, a video stream is temporally segmented into smaller chunks that can be accessed and decoded independently, cache replacement strategies have been developed that take advantage of this temporal structure in the video. In this paper, two caching strategies are proposed that additionally take advantage of the phenomenon of binge watching, where users stream multiple consecutive episodes of the same series, reported by recent user behavior studies to become the everyday behavior. Taking into account this information allows us to predict future segment requests, even before the video playout has started. Two strategies are proposed, both with a different level of coordination between the caches in the network. Using a VoD request trace based on binge watching user characteristics, the presented algorithms have been thoroughly evaluated in multiple network topologies with different characteristics, showing their general applicability. It was shown that in a realistic scenario, the proposed election-based caching strategy can outperform the state-of-the-art by 20% in terms of cache hit ratio while using 4% less network bandwidth

Adjustable Two-Tier Cache for IPTV Based on Segmented Streaming

Internet protocol TV (IPTV) is a promising Internet killer application, which integrates video, voice, and data onto a single IP network, and offers viewers an innovative set of choices and control over their TV content. To provide high-quality IPTV services, an effective strategy is based on caching. This work proposes a segment-based two-tier caching approach, which divides each video into multiple segments to be cached. This approach also partitions the cache space into two layers, where the first layer mainly caches to-be-played segments and the second layer saves possibly played segments. As the segment access becomes frequent, the proposed approach enlarges the first layer and reduces the second layer, and vice versa. Because requested segments may not be accessed frequently, this work further designs an admission control mechanism to determine whether an incoming segment should be cached or not. The cache architecture takes forward/stop playback into account and may replace the unused segments under the interrupted playback. Finally, we conduct comprehensive simulation experiments to evaluate the performance of the proposed approach. The results show that our approach can yield higher hit ratio than previous work under various environmental parameters