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arXiv 1102.1782cs.ITmath.IT
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非循环时滞网络的网络编码

On network coding for acyclic networks with delays

K. Prasad, B. Sundar Rajan

摘要:

与非循环瞬时网络的网络编码相关的问题(其中,假设表示网络的非循环图的边具有零延迟)在最近的过去已经被广泛地处理。这些问题中最突出的包括(a)实现最大传输速率的网络码的存在,(b)有效的网络码构造,以及(c)字段大小问题。然而,实际上,网络具有传输延迟。在网络编码理论中,这种具有传输延迟的网络通常通过假设其边缘具有整数延迟来抽象。请注意,在具有整数延迟的非循环网络的节点处使用足够的内存可以有效地模拟瞬时行为,这可能就是为什么到目前为止只关注非循环瞬时网络的原因。在这项工作中,我们详细阐述了与整数延迟无环网络的网络编码相关的问题((a),(b)和(c)),这些问题到目前为止大多被忽视了。我们表明,与网络的边缘相关联的延迟不能被忽略,实际上是有利的,不利的或不重要的,这取决于网络的拓扑结构和考虑的问题,即,(a)、(b)或(c)。在这个过程中,我们还表明,在非循环网络(瞬时和延迟)的单源组播问题,在每个节点的网络编码操作可以简单地限于存储旧的符号和编码他们在一个二进制字段。因此,在网络中,对较大字段的元素的操作是不必要的,折衷是在节点和接收器处存在足够的存储器,并且接收器具有更多的处理能力。

英文摘要:

Problems related to network coding for acyclic, instantaneous networks (where the edges of the acyclic graph representing the network are assumed to have zero-delay) have been extensively dealt with in the recent past. The most prominent of these problems include (a) the existence of network codes that achieve maximum rate of transmission, (b) efficient network code constructions, and (c) field size issues. In practice, however, networks have transmission delays. In network coding theory, such networks with transmission delays are generally abstracted by assuming that their edges have integer delays. Note that using enough memory at the nodes of an acyclic network with integer delays can effectively simulate instantaneous behavior, which is probably why only acyclic instantaneous networks have been primarily focused on thus far. In this work, we elaborate on issues ((a), (b) and (c) above) related to network coding for acyclic networks with integer delays, which have till now mostly been overlooked. We show that the delays associated with the edges of the network cannot be ignored, and in fact turn out to be advantageous, disadvantageous or immaterial, depending on the topology of the network and the problem considered i.e., (a), (b) or (c). In the process, we also show that for a single source multicast problem in acyclic networks (instantaneous and with delays), the network coding operations at each node can simply be limited to storing old symbols and coding them over a binary field. Therefore, operations over elements of larger fields are unnecessary in the network, the trade-off being that enough memory exists at the nodes and at the sinks, and that the sinks have more processing power.

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