间歇连接移动网络中的最小延迟数据扩散

M. Sathiamoorthy, Wei Gao, B. Krishnamachari, G. Cao
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引用次数: 1

摘要

我们考虑在间歇性连接的移动网络中扩散缓存内容的问题,从给定的初始配置开始到理想的目标状态,其中所有对特定内容感兴趣的节点都有其所需内容的副本。目标是最小化扩散过程在目标状态终止所花费的时间。由于带宽和存储的限制,每当两个节点相遇时,它们必须决定将哪些内容传输给彼此。虽然关于这个主题的大多数先前的工作都集中在这个问题的实际可实现的启发式上,但我们采取了更正式的方法。我们的主要贡献是表明,假设全局状态信息是可用的,这个问题可以被表述为一个随机最短路径问题,这是一种马尔可夫决策过程(MDP)。利用这一公式,我们对一些能够得到最优解的小尺度例子进行了数值探索。结果表明,最优扩散策略在很大程度上是底层相遇图的函数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Minimum Latency Data Diffusion in Intermittently Connected Mobile Networks
We consider the problem of diffusing cached content in an intermittently connected mobile network, starting from a given initial configuration to a desirable goal state where all nodes interested in particular contents have a copy of their desired contents. The goal is to minimize the time taken for the diffusion process to terminate at a goal state. Due to bandwidth and storage constraints, whenever two nodes encounter each other, they must decide which content if any to transfer to each other. While most prior work on this topic has focused on practically realizable heuristics for this problem, we take a more formal approach. Our main contribution is to show that, assuming global state information is available, this problem can be formulated as a stochastic shortest path problem, which is a kind of Markov decision process (MDP). Using this formulation, we numerically explore some small-scale examples for which we are able to obtain the optimal solution. The results show that the optimal diffusion strategy is very much a function of the underlying encounter graph.
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