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arXiv 1108.4152cs.ITmath.IT
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存储器辅助信源编码的全网增益研究

On the Network-Wide Gain of Memory-Assisted Source Coding

Mohsen Sardari, Ahmad Beirami, Faramarz Fekri

摘要:

一些研究已经确定了大量的冗余网络流量。例如,它表明,随着时间的推移,在服务器的内容中存在大量的冗余。通过在网络中部署存储器单元,可以利用这种冗余来减少网络流量。由此产生的问题是,内存的部署是否会导致网络性能的根本改善。在本文中,我们肯定地回答了这个问题,首先建立了内存辅助源压缩的基本收益,然后将该技术应用于网络。具体来说,我们研究了由一个单一的源和几个随机选择的内存单元组成的随机网络图中的内存辅助压缩的增益。我们发现一个阈值的存储器的数量部署在一个随机图,并表明,如果存储器的数量超过阈值,我们观察到网络范围内的流量减少。

英文摘要:

Several studies have identified a significant amount of redundancy in the network traffic. For example, it is demonstrated that there is a great amount of redundancy within the content of a server over time. This redundancy can be leveraged to reduce the network flow by the deployment of memory units in the network. The question that arises is whether or not the deployment of memory can result in a fundamental improvement in the performance of the network. In this paper, we answer this question affirmatively by first establishing the fundamental gains of memory-assisted source compression and then applying the technique to a network. Specifically, we investigate the gain of memory-assisted compression in random network graphs consisted of a single source and several randomly selected memory units. We find a threshold value for the number of memories deployed in a random graph and show that if the number of memories exceeds the threshold we observe network-wide reduction in the traffic.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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