DMCA
Multi-dimensional conflict graph based computing for optimal capacity (2010)
| Venue: | in MR-MC wireless networks”, in Proc. IEEE ICDCS |
| Citations: | 18 - 6 self |
BibTeX
@INPROCEEDINGS{Li10multi-dimensionalconflict,
author = {Hongkun Li and Yu Cheng and Chi Zhou and Pengjun Wan},
title = {Multi-dimensional conflict graph based computing for optimal capacity},
booktitle = {in MR-MC wireless networks”, in Proc. IEEE ICDCS},
year = {2010}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
Abstract—Optimal capacity analysis in multi-radio multichannel wireless networks by nature incurs the formulation of a mixed integer programming, which is NP-hard in general. The current state of the art mainly resorts to heuristic algorithms to obtain an approximate solution. In this paper, we propose a novel concept of multi-dimensional conflict graph (MDCG). Based on MDCG, the capacity optimization issue can be accurately modeled as a linear programming (LP) multi-commodity flow (MCF) problem, augmented with maximal independent set (MIS) constraints. The MDCG-based solution will provide not only the maximum throughput or utility, but also the optimal configurations on routing, channel assignment, and scheduling. Moreover, the MDCG-based optimal capacity planning can exploit dynamic channel swapping, which is difficult to achieve for those existing heuristic algorithms. A particular challenge associated with the MDCG-based capacity analysis is to search exponentially many possible MISs. We theoretically show that in fact only a small set of critical MISs, termed as critical MIS set, will be scheduled in the optimal resource allocation. We then develop a polynomial computing method, based on a novel scheduling index ordering (SIO) concept, to search the critical MIS set. Extensive numerical results are presented to demonstrate the efficiency of the MDCGbased resource allocation compared to well-known heuristic algorithm presented in [1], and the efficiency of SIO-based MIS computing compared to the widely adopted random algorithm for searching MISs. I.
Keyphrases
multi-dimensional conflict graph optimal capacity critical mi set well-known heuristic algorithm current state random algorithm heuristic algorithm novel concept multi-commodity flow maximal independent set approximate solution linear programming mdcgbased resource allocation dynamic channel swapping capacity optimization issue particular challenge sio-based mi computing abstract optimal capacity analysis channel assignment small set mdcg-based optimal capacity planning extensive numerical result critical miss maximum throughput novel scheduling index ordering many possible miss polynomial computing method multi-radio multichannel wireless network mdcg-based capacity analysis optimal resource allocation mixed integer programming mdcg-based solution optimal configuration
