Coded caching is a recently proposed technique that achieves significant performance gains for cache networks compared to uncoded caching schemes. However, this substantial coding gain is attained at the cost of large delivery delay, which is not tolerable in delay-sensitive applications such as video streaming. In this paper, we identify and investigate the tradeoff between the performance gain of coded caching and the delivery delay. We propose a computationally efficient caching algorithm that provides the gains of coding and respects delay constraints. The proposed algorithm achieves the optimum performance for large delay, but still offers major gains for small delay. These gains are demonstrated in a practical setting with a video-streaming prototype. I. INTRODUCTION Video on demand drives network traffic growth today, and this trend is expected to continue until the end of the decade [1] . Indeed, some studies predict that video traffic will grow by a factor 12 between 2010 and 2020 [2] . Video traffic is time varying in nature, with a significant peak during the evenings. This characteristic burdens service providers with the cost of having to expand their networks to handle increasing peak traffic even though the network remains underutilized during off-peak times. Caching is a key technique to alleviate this problem by smoothing traffic in time and across the network. Caching uses memories distributed throughout the network to duplicate popular content during off-peak times. During peak traffic times, these memories are then used to deliver requested content with less stress on the network. The core idea behind conventional caching schemes [3]-[10] is to deliver part of the content locally from nearby caches. Recently [11] , [12] proposed instead to use coded caching. Unlike conventional uncoded schemes, coded caching creates linear combinations of chunks of content requested by different users. The combinations are formed such that each user can recover his requested chunk using the content of a nearby cache. Therefore the caches are used not only to deliver parts of the content locally, but also to create coded multicasting opportunities. [11] , [12] shows that, for some basic network structures, coded caching can yield significantly better performance than uncoded caching. This result demonstrates that widely-used caching algorithms such as least-frequently used (LFU) or least-recently used (LRU) can be significantly suboptimal for cache networks [13] , [14] . The substantial gain of coded caching is achieved at the cost of increased delay during content delivery. However, many applications, such as video on demand, are delay sensitive, and consequently this added delay resulting from coding is problematic. This raises the question of how much of the coded caching gain can be obtained within some fixed delay constraint. In this paper, we initiate the investigation of this tradeoff between coded caching gain and delivery delay. We develop a computationally efficient caching scheme that effectively exploits coding opportunities while respecting delivery-delay constraints. The proposed scheme achieves the optimum performance suggested by [11], [12] in the large-delay limit, while still offering a significant gain for delay-sensitive applications. A video-streaming prototype implementing these ideas confirms the practicality and gains of the proposed scheme.
They also extended the coded caching method to consider delay-sensitive content and proposed three algorithms to achieve coding gains for low-delay delivery REF .
Coded Caching for Delay-Sensitive Content
IEEE International Conference on Communications (ICC), pp. 5559 - 5564, June 2015
Computer Science Mathematics