The index coding problem has recently attracted a significant attention from the research community. In this problem, a server needs to deliver data to a set of wireless clients over the broadcast channel. Each client...
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ISBN:
(纸本)9781424492688
The index coding problem has recently attracted a significant attention from the research community. In this problem, a server needs to deliver data to a set of wireless clients over the broadcast channel. Each client requires one or more packets, but it might have access to the packets requested by other clients as side information. The goal is to deliver the required data to each client with minimum number of transmissions. In this paper, we focus on finding sparse solutions to the index coding problem. In a sparse solution each transmitted packet is a linear combination of at most two original packets. We focus both on scalar and vector versions of the problem. For the scalar case, we present a polynomial time algorithm that achieves an approximation ratio of 2 - 1/root n. For the vector case, we present a polynomial time algorithm that identifies an optimal solution to the problem. Our simulation studies demonstrate that our algorithms achieve good performance in practical scenarios.
We investigate the problem of data synchronization in which a sender has a set of packets to be distributed to all the receivers via a broadcast channel. Initially, each receiver has some fraction of the packets. At e...
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We investigate the problem of data synchronization in which a sender has a set of packets to be distributed to all the receivers via a broadcast channel. Initially, each receiver has some fraction of the packets. At each time slot, the sender might broadcast a packet to all the receivers. The goal is to find a broadcast scheme that minimizes the number of time slots until all the receivers successfully obtain all the packets. We propose two probabilisticmodels on howthe initial fractions of packets at receivers are distributed. These models arise naturally in many large-scale systems, such as peer-to-peer networks, data centers, and distributed storage systems. Based on these models, we establish probabilistic bounds and asymptotic results on the minimum number of time slots to successfully transmit all the packets to all the receivers. Next, we propose and analyze a number of random network coding algorithms for finding the approximately optimal solution. Theoretical analysis and simulations are provided to verify the probabilistic bounds and the proposed algorithms.
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