A bio-inspired optimal network division method

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.