50 research outputs found

    Centralized Coded Caching with User Cooperation

    Full text link
    In this paper, we consider the coded-caching broadcast network with user cooperation, where a server connects with multiple users and the users can cooperate with each other through a cooperation network. We propose a centralized coded caching scheme based on a new deterministic placement strategy and a parallel delivery strategy. It is shown that the new scheme optimally allocate the communication loads on the server and users, obtaining cooperation gain and parallel gain that greatly reduces the transmission delay. Furthermore, we show that the number of users who parallelly send information should decrease when the users' caching size increases. In other words, letting more users parallelly send information could be harmful. Finally, we derive a constant multiplicative gap between the lower bound and upper bound on the transmission delay, which proves that our scheme is order optimal.Comment: 9 pages, submitted to ITW201

    Demand-Private Coded Caching and the Exact Trade-off for N=K=2

    Get PDF
    The distributed coded caching problem has been studied extensively in the recent past. While the known coded caching schemes achieve an improved transmission rate, they violate the privacy of the users since in these schemes the demand of one user is revealed to others in the delivery phase. In this paper, we consider the coded caching problem under the constraint that the demands of the other users remain information theoretically secret from each user. We first show that the memory-rate pair (M,min{N,K}(1M/N))(M,\min \{N,K\}(1-M/N)) is achievable under information theoretic demand privacy, while using broadcast transmissions. We then show that a demand-private scheme for NN files and KK users can be obtained from a non-private scheme that satisfies only a restricted subset of demands of NKNK users for NN files. We then focus on the demand-private coded caching problem for K=2K=2 users, N=2N=2 files. We characterize the exact memory-rate trade-off for this case. To show the achievability, we use our first result to construct a demand-private scheme from a non-private scheme satisfying a restricted demand subset that is known from an earlier work by Tian. Further, by giving a converse based on the extra requirement of privacy, we show that the obtained achievable region is the exact memory-rate trade-off.Comment: 8 pages, 2 figure
    corecore