# Optimal Resource Allocation with Node and Link Capacity Constraints in Complex Networks

## TL;DR

This paper presents an optimization framework for resource allocation in complex networks, maximizing traffic utility under node and link capacity constraints using a duality-based iterative algorithm, outperforming existing methods.

## Contribution

Introduces a novel duality-based iterative algorithm for joint traffic rate and capacity adjustment considering network topology and constraints.

## Key findings

- Algorithm outperforms NUP on BA and ER networks
- Provides insights into resource allocation in real communication networks
- Achieves higher total utility than previous methods

## Abstract

With the tremendous increase of the Internet traffic, achieving the best performance with limited resources is becoming an extremely urgent problem. In order to address this concern, in this paper, we build an optimization problem which aims to maximize the total utility of traffic flows with the capacity constraint of nodes and links in the network. Based on Duality Theory, we propose an iterative algorithm which adjusts the rates of traffic flows and capacity of nodes and links simultaneously to maximize the total utility. Simulation results show that our algorithm performs better than the NUP algorithm on BA and ER network models, which has shown to get the best performance so far. Since our research combines the topology information with capacity constraint, it may give some insights for resource allocation in real communication networks.