کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5103245 | 1480100 | 2017 | 13 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Average weighted receiving time on the non-homogeneous double-weighted fractal networks
ترجمه فارسی عنوان
میانگین دریافت زمان در شبکه های فراکتال دوگانه غیر همگن
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کلمات کلیدی
شبکه فراکتال، غیر همگن، شبکه دوگانه متوسط زمان دریافت، عامل وزن
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
فیزیک ریاضی
چکیده انگلیسی
In this paper, based on actual road networks, a model of the non-homogeneous double-weighted fractal networks is introduced depending on the number of copies s and two kinds of weight factors wi,ri(i=1,2,â¦,s). The double-weights represent the capacity-flowing weights and the cost-traveling weights, respectively. Denote by wijF the capacity-flowing weight connecting the nodes i and j, and denote by wijC the cost-traveling weight connecting the nodes i and j. Let wijF be related to the weight factors w1,w2,â¦,ws, and let wijC be related to the weight factors r1,r2,â¦,rs. Assuming that the walker, at each step, starting from its current node, moves to any of its neighbors with probability proportional to the capacity-flowing weight of edge linking them. The weighted time for two adjacency nodes is the cost-traveling weight connecting the two nodes. The average weighted receiving time (AWRT) is defined on the non-homogeneous double-weighted fractal networks. AWRT depends on the relationships of the number of copies s and two kinds of weight factors wi,ri(i=1,2,â¦,s). The obtained remarkable results display that in the large network, the AWRT grows as a power-law function of the network size Ng with the exponent, represented by θ=logs(w1r1+w2r2+â¯+wsrs)<1 when w1r1+w2r2+â¯+wsrsâ 1, which means that the smaller the value of w1r1+w2r2+â¯+wsrs is, the more efficient the process of receiving information is. Especially when w1r1+w2r2+â¯+wsrs=1, AWRT grows with increasing order Ng as logNg or (logNg)2 . In the classic fractal networks, the average receiving time (ART) grows with linearly with the network size Ng. Thus, the non-homogeneous double-weighted fractal networks are more efficient than classic fractal networks in term of receiving information.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Physica A: Statistical Mechanics and its Applications - Volume 473, 1 May 2017, Pages 390-402
Journal: Physica A: Statistical Mechanics and its Applications - Volume 473, 1 May 2017, Pages 390-402
نویسندگان
Dandan Ye, Meifeng Dai, Yu Sun, Weiyi Su,