Computing Sharp Bounds of Metric Based Fractional Dimensions for the Sierpinski Networks
Abstract
:1. Introduction
2. Preliminaries
3. LRNs of -Based Sierpinski Networks
- 1.
- ∀,
- 2.
- , where , and .
LRNs | Cardinalities |
---|---|
, | |
, | |
, , , |
- 1.
- ∀ ,
- 2.
- , where , and .
LRNs | Cardinalities |
---|---|
, | 14 |
, | 22 |
, , , | 16 |
, | 18 |
, , | 26 |
- 1.
- ∀,
- 2.
- , where , and .
- For , we have 31 types of edges in a network . Eleven types of LRNs of these edges are as follows:= ,= = ,= = ,= = ,= = ,= = ,= = ,= = ,= = ,= = ,.Similarly, we obtained = , = , = , = , = , = , = , = , = , = , = , = , = , = , = , = , = , = , = and = and the cardinalities of the sets of all LRNs are in Table 3.
- Table 3 shows that and > .
LRNs | Cardinalities |
---|---|
, | 63 |
; | 121 |
, | 122 |
, | 123 |
, | 115 |
, | 66 |
, | 67 |
, | 75 |
, | 73 |
, | 84 |
, , | 124 |
- 1.
- ∀ ,
- 2.
- , where , and .
- For and , the LRNs of 57 types of edges in a network . Thirteen types of LRNs of these edges are as follows:= = , where ,= = ,= = ,,= = ,= = ,= = ,= = ,= ,= ,= = ,= = ,= = , where .Similarly, we obtained , , , , , , , , , , , ,, , , , , , , , , , , , , , , , , where , , , where , ,, , , , where , , , where , , , , , , and the cardinalities of the sets of all LRNs are in Table 4.
- Table 4 shows that and > .
LRNs | Cardinalities |
---|---|
, | |
, | |
, | |
, | |
, | |
, | |
, , , , , | |
, | |
, , , | |
, , , | |
, | |
, , , , , | |
; |
4. LFMD of -Based Sierpinski Networks
- 1.
- , if .
- 2.
- , if .
- 3.
- , if
- From Lemma 3, we have , where and ∀ . In addition, = 1. Define a local resolving function asSince for each , = = =We note that and the pairwise intersection of ’s is non-empty. Therefore ∃ a LRF, such that then , where . Therefore, .The cardinalities of , and are greater than other remaining LRNs. Using Lemma 1, . Hence,
- From Lemma 4, we have , where and ∀. In addition, = 63. Define a local resolving function asSince for each , = = =We note that and the pairwise intersection of ’s is non-empty. Therefore ∃ a LRF, such that then , where . Therefore, .The cardinalities of , and are greater than other remaining LRNs. Using Lemma 1, . Hence,
- From Lemma 5, we have , where and ∀. In addition, = . Define a local resolving function asSince for each , = = = .We note that and the pairwise intersection of ’s is non-empty. Therefore ∃ a LRF, such that then , where . Therefore, .The cardinality of , where is greater than other remaining LRNs. Using Lemma 1, . Hence,
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Networks | Bounds of LFMD | Limiting Values of LFMD as | Remarks |
---|---|---|---|
bounded | |||
- | bounded | ||
- | bounded | ||
unbounded |
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Fatima, A.; Alamer, A.; Javaid, M. Computing Sharp Bounds of Metric Based Fractional Dimensions for the Sierpinski Networks. Mathematics 2022, 10, 4332. https://doi.org/10.3390/math10224332
Fatima A, Alamer A, Javaid M. Computing Sharp Bounds of Metric Based Fractional Dimensions for the Sierpinski Networks. Mathematics. 2022; 10(22):4332. https://doi.org/10.3390/math10224332
Chicago/Turabian StyleFatima, Arooba, Ahmed Alamer, and Muhammad Javaid. 2022. "Computing Sharp Bounds of Metric Based Fractional Dimensions for the Sierpinski Networks" Mathematics 10, no. 22: 4332. https://doi.org/10.3390/math10224332
APA StyleFatima, A., Alamer, A., & Javaid, M. (2022). Computing Sharp Bounds of Metric Based Fractional Dimensions for the Sierpinski Networks. Mathematics, 10(22), 4332. https://doi.org/10.3390/math10224332