Article

# The Network as a Storage Device: Dynamic Routing with Bounded Buffers

Algorithmica (impact factor: 0.6). 04/2012; 55(1):71-94. DOI:10.1007/s00453-007-9143-1 pp.71-94
Source: DBLP

ABSTRACT We study dynamic routing in store-and-forward packet networks where each network link has bounded buffer capacity for receiving
incoming packets and is capable of transmitting a fixed number of packets per unit of time. At any moment in time, packets
are injected at various network nodes with each packet specifying its destination node. The goal is to maximize the throughput, defined as the number of packets delivered to their destinations.

In this paper, we make some progress on throughput maximization in various network topologies. Let n and m denote the number of nodes and links in the network, respectively. For line networks, we show that Nearest-to-Go (NTG), a
natural distributed greedy algorithm, is
[(O)\tilde](Ön)\tilde{O}(\sqrt{n})
-competitive, essentially matching a known
W(Ön)\Omega(\sqrt{n})
lower bound on the performance of any greedy algorithm. We also show that if we allow the online routing algorithm to make centralized decisions, there is a randomized
polylog(n)-competitive algorithm for line networks as well as for rooted tree networks, where each packet is destined for the root
of the tree. For grid graphs, we show that NTG has a competitive ratio of
[(Q)\tilde](n2/3)\tilde{\Theta}(n^{2/3})
while no greedy algorithm can achieve a ratio better than
W(Ön)\Omega(\sqrt{n})
. Finally, for arbitrary network topologies, we show that NTG is
[(Q)\tilde](m)\tilde{\Theta}(m)
-competitive, improving upon an earlier bound of O(mn).

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### Keywords

-competitive

algorithm

arbitrary network topologies

centralized decisions

competitive ratio

destination node

destinations

fixed number

greedy algorithm

grid graphs

incoming packets

line networks

lower

packets

rooted tree networks

store-and-forward packet networks

throughput maximization

various network nodes

various network topologies