Name
Abstract | ||
|---|---|---|
Two classic categories of models exist for computer networks: network information flow and network of queues. The network information flow model appropriately captures the multi-hop flow routing nature in general network topologies, as well as encodable and replicable properties of information flows. However it assumes nodes in the network to be infinitely powerful and therefore does not accurately model queueing delay and loss at nodes. The network of queues model instead focuses on finite capacitied nodes and studies buffering and loss behaviors from a stochastic perspective. However existing models on network of queues are mostly based on unrealistically simple topologies, and lacks the multi-hop flow routing dimension. In this work, we seek to combine advantages from both models. We start with the network information flow model and replace each infinitely powerful node with a finitely capacitied queue system instead. We show that the optimal routing problems for unicast, multiple unicasts and multicast can all be formulated as convex optimization problems. As a necessary step in validating the model for multicast routing, we show that network coding does not change the memoryless nature of traffic. We examine the correctness of the models through simulations and show that they behave differently than traditional link-cost based network flow models. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/MASCOT.2008.4770562 | 2008 IEEE INTERNATIONAL SYMPOSIUM ON MODELING, ANALYSIS & SIMULATION OF COMPUTER AND TELECOMMUNICATION SYSTEMS (MASCOTS) |
Keywords | Field | DocType |
computational modeling,mathematical model,network flow,encoding,network coding,convex optimization,information flow,network topology,convex programming,queueing theory,routing,computer network,unicast,computer networks | Linear network coding,Flow network,Network formation,Network delay,Computer science,Computer network,Network simulation,Real-time computing,Multi-commodity flow problem,Loss network,Network traffic control,Distributed computing | Conference |
ISSN | Citations | PageRank |
1526-7539 | 2 | 0.41 |
References | Authors | |
11 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Phillipa Gill | 1 | 1504 | 114.56 |
| Zongpeng Li | 2 | 2054 | 153.21 |
| Anirban Mahanti | 3 | 1875 | 113.51 |
| Jingxiang Luo | 4 | 19 | 2.83 |
| C. Williamson | 5 | 2998 | 417.38 |