Optimization problems in correlated networks

Optimization problems in correlated networks

Yang, S.
Trajanovski, S.
Kuipers, F.A.

Electrical Engineering, Mathematics and Computer Science

Intelligent Systems

2016-01-22

Background Solving the shortest path and min-cut problems are key in achieving high-performance and robust communication networks. Those problems have often been studied in deterministic and uncorrelated networks both in their original formulations as well as in several constrained variants. However, in real-world networks, link weights (e.g., delay, bandwidth, failure probability) are often correlated due to spatial or temporal reasons, and these correlated link weights together behave in a different manner and are not always additive, as commonly assumed. Methods In this paper, we first propose two correlated link weight models, namely (1) the deterministic correlated model and (2) the (log-concave) stochastic correlated model. Subsequently, we study the shortest path problem and the min-cut problem under these two correlated models. Results and Conclusions We prove that these two problems are NP-hard under the deterministic correlated model, and even cannot be approximated to arbitrary degree in polynomial time. However, these two problems are solvable in polynomial time under the (constrained) nodal deterministic correlated model, and can be solved by convex optimization under the (log-concave) stochastic correlated model.

shortest path
min-cut
correlated networks
stochastic link weights
OA-Fund TU Delft

http://resolver.tudelft.nl/uuid:5da08269-1324-4fb6-9b1b-c13d044e362f

SpringerOpen

2197-4314

https://doi.org/10.1186/s40649-016-0026-y

Computational Social Networks, 3 (1), 2016

Institutional Repository

journal article

© 2016 The Author(s)
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/)