A bio-inspired optimal network division method
Hanchao Yang,
Yujia Liu,
Qian Wan and
Yong Deng
Physica A: Statistical Mechanics and its Applications, 2019, vol. 527, issue C
Abstract:
Network models are ubiquitous in engineering like communication, transportation and society. For many algorithms, the processing time grows exponentially as the number of nodes grows. In applications like allocating storage center in a transportation network and organizing cluster architectures in an Iot network, dividing a massive network into small no-overlap subnetworks is necessary. In this paper, a network dividing method is presented inspired by the natural phenomena of bacterial growth, division and competition. This method aims to use the bionic metrics to divided a big network evenly, because in transmission and communication areas, balancing of workload is important. Two examples utilized to illustrate the efficiency of the proposed method. A small network with 31 nodes serves to present the division result visually and a server network with 1200 nodes was used to prove the efficiency and evenness of result.
Keywords: Network division; Bio-inspired model; Physarum algorithm; Shortest path (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437119307253
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:527:y:2019:i:c:s0378437119307253
DOI: 10.1016/j.physa.2019.121259
Access Statistics for this article
Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis
More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().