We propose a novel caching strategy for the problem of centralized coded caching with non-uniform demands. Our placement strategy can be applied to an arbitrary number of users and files, and can be easily adapted to the scenario where file popularities are user-specific. The distinguishing feature of the proposed placement strategy is that it allows for equal sub-packetization for all files while requiring the users to allocate more cache to the more popular files. This creates natural broadcasting opportunities in the delivery phase which are simultaneously helpful for users who have requested files of different popularities. For the case of two files, we propose a delivery strategy which meets a natural extension of the existing converse bounds under uncoded placement to non-uniform demands, thereby establishing the optimal expected memory-rate trade-off for the case of two files with arbitrary popularities under the restriction of uncoded placement.
For a network with one sender, n receivers (users) and m possible messages (files), caching side information at the users allows to satisfy arbitrary simultaneous demands by sending a common (multicast) coded message. In the worst-case demand setting, explicit deterministic and random caching strategies and explicit linear coding schemes have been shown to be order optimal. In this work, we consider the same scenario where the user demands are random i.i.d., according to a Zipf popularity distribution. In this case, we pose the problem in terms of the minimum average number of equivalent message transmissions. We present a novel decentralized random caching placement and a coded delivery scheme which are shown to achieve order-optimal performance. As a matter of fact, this is the first order-optimal result for the caching and coded multicasting problem in the case of random demands. Despite significant progress in the caching literature concerning the worst case and uniform average case regimes, the algorithms for caching with nonuniform demands are still at a basic stage and mostly rely on simple grouping and memory-sharing techniques. In this work we introduce a novel centralized caching strategy for caching with nonuniform file popularities. Our scheme allows for assigning more cache to the files which are more likely to be requested, while maintaining the same sub-packetization for all the files. As a result, in the delivery phase it is possible to perform linear codes across files with different popularities without resorting to zero-padding or concatenation techniques. We will describe our placement strategy for arbitrary range of parameters. The delivery phase will be outlined for a small example for which we are able to show a noticeable improvement over the state of the art. In content delivery networks, as more contents are being generated and the size of contents is increasing, caching has been identified as a solution to cope with congestion in communication links. The idea is to prepopulate users' cache with parts of files in off-peak time to ease the peak-time delivery traffic. In this paper, we consider nonuniform demands, where different files have different probability of being requested. We consider networks with a server connected to multiple users through a shared link. The goal is to design cache placement schemes that minimize the transmission rate from the server during peak-time content delivery. In this paper, we analytically prove that a caching scheme proposed by , which they showed to achieve within a constant multiplicative and additive gap from the optimal rate, is indeed optimal when there are only two users. Proactive content caching at user devices and coded delivery is studied considering a non-uniform file popularity distribution. A novel centralized uncoded caching and coded delivery scheme, which can be applied to large file libraries, is proposed. The proposed cross-level coded delivery (CLCD) scheme is shown to achieve a lower average delivery rate than the state of art. In the proposed CLCD scheme, the same subpacketization is used for all the files in the library in order to prevent additional zero-padding in the delivery phase, and unlike the existing schemes in the literature, two users requesting files from different popularity groups can be served by the same multicast message in order to reduce the delivery rate. Simulation results indicate significant reduction in the average delivery rate for typical Zipf distribution parameter values.