Scaling of average receiving time and average shortest path on claw network

Yang, Huixian; Sun, Yu; Hao, Yong-Xia

doi:10.1088/1402-4896/aba3ad

Cited by 2 publications

(1 citation statement)

References 30 publications

(37 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…But in reality, taking road traffic as an example, each path is chosen with a different probability. With the gradual development and improvement, unbiased random walk [22][23][24] is converted into biased random walk [25]. Therefore, the network we constructed is a class of weighted-crystal networks by adding the weight factor r (0 < r 1) in which the dynamic is a biased random walks, which has more practical application significance.…”

Section: Introductionmentioning

confidence: 99%

Scaling of average receiving time and average weighted shortest path on weighted-crystal network

Li¹,

Li²,

Sun³

2021

J. Stat. Mech.

Self Cite

View full text Add to dashboard Cite

In this paper, we focus on a network with even nodes named the weighted-crystal network, which is different from the regular iterative rules. By employing the self-similarity of the crystal network, we study and calculate the average receiving time (ART) and average weighted shortest path (AWSP) after dividing the network into n + 1 blocks. In particular, we pay attention to the hexagon crystal network in order to obtain exact results. The obtained scaled results show that ART grows linearly or sublinearly with the iterative and increases with the weight factor r. Meanwhile, the results of AWSP indicate that AWSP exhibits a sublinear dependence on the network order when r = 1. Otherwise, AWSP tends towards constants when 0 < r < 1.

show abstract

Section: Introductionmentioning

confidence: 99%

Scaling of average receiving time and average weighted shortest path on weighted-crystal network

Li¹,

Li²,

Sun³

2021

J. Stat. Mech.

Self Cite

View full text Add to dashboard Cite

show abstract

Scaling of average receiving time on double-weighted polygon networks

Sun

2021

Int. J. Mod. Phys. B

View full text Add to dashboard Cite

In this paper, we introduce a class of double-weighted polygon networks with two different meanings of weighted factors [Formula: see text] and [Formula: see text], which represent path-difficulty and path-length, respectively, based on actual traffic networks. Picking an arbitrary node from the hub nodes set as the trap node, and the double-weighted polygon networks are divided into [Formula: see text] blocks by combining with the iterative method. According to biased random walks, the calculation expression of average receiving time (ART) of any polygon networks is given by using the intermediate quantity the mean first-passage time (MFPT), which is applicable to any [Formula: see text] ([Formula: see text]) polygon networks. What is more, we display the specific calculation process and results of ART of the double-weighted quadrilateral networks, indicating that ART grows exponentially with respect to the networks order and the exponent is [Formula: see text] which grows with the product of [Formula: see text]. When [Formula: see text] increases, ART increases linearly ([Formula: see text]) or sublinearly ([Formula: see text]) with the size of networks, and the smaller value of [Formula: see text], the higher transportation efficiency.

show abstract

Scaling of average receiving time and average shortest path on claw network

Cited by 2 publications

References 30 publications

Scaling of average receiving time and average weighted shortest path on weighted-crystal network

Scaling of average receiving time and average weighted shortest path on weighted-crystal network

Scaling of average receiving time on double-weighted polygon networks

Contact Info

Product

Resources

About