An Innovative Topologies Based on Hypercube Network Interconnection
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A parallel processing system's most crucial part is a network interconnection that links its processors. The hypercube topology has interesting features that make it a great option for parallel processing applications. This paper presents two innovative configurations of interconnection networks based on fractal Sierpinski and a hypercube. These are called the Sierpinski Triangle Topology (STT) and Sierpinski Carpet Topology (SCT). Compared to a hypercube, the Sierpinski Triangle topology (STT) noticed a significant decrease in the number of nodes and links as large networks grew. Hence, it is considered a great way to reduce costs because it uses fewer nodes and links. The average distance is also shorter, which is better. Despite it having a smaller bisection width and a higher degree than a hypercube by one. The Sierpinski Carpet Topology (SCT) has the advantage of having a high bisection width compared to a hypercube. That is preferable because it places a lower restriction on the difficulty of parallel algorithms. While the drawback of this topology is that it has a diameter and average distance more than a hypercube.
References
-
Mostafa AB, Fayez G. Reliability analysis and fault tolerance for hypercube multi-computer networks. Inf. Sci. (Ny). 2014 Aug 20; 276: 295–318. doi: 10.1016/j.ins.2013.10.031.
Google Scholar
1
-
Nuntipat P, Jeeraporn W. Shortest-path routing for optimal all-to-all personalized-exchange embedding on hierarchical hypercube networks. J. Parallel Distrib. Comput. 2021 Apr; 150: 139–154. doi: 10.1016/j.jpdc.2021.01.004.
Google Scholar
2
-
Hesham ER, Mostafa AB. Advanced Computer Architecture and Parallel Processing. 1st ed. New Jersey: John Wiley & Sons, Inc.;2005.
Google Scholar
3
-
Basel AM, Mohammed A, Luay T, Nada A. Topological Properties Assessment for Hyper Hexa-Cell Interconnection Network. International Journal of Computers. 2019; 13: 115–121.
Google Scholar
4
-
Fathollah B, Mohsen J. Impact of Raising Switching Stages on the Reliability of Interconnection Networks. J. Inst. Electron. Comput. 2020; 2(1): 93–120. doi: 10.33969/jiec.2020.21007.
Google Scholar
5
-
Fei Z, Yiyu F, Wei F. Three-dimensional interconnected networks for thermally conductive polymer composites: Design, preparation, properties, and mechanisms. Mater. Sci. Eng. R Reports. 2020 Oct; 142: 100580. doi: 10.1016/j.mser.2020.100580.
Google Scholar
6
-
Namit G, Kunwar SV, Rajeev K. Design of a Structured Hypercube Network Chip Topology Model for Energy Efficiency in Wireless Sensor Network Using Machine Learning. SN Comput. Sci. 2021 Dec 16; 2(5): 375-388. doi: 10.1007/s42979-021-00766-7.
Google Scholar
7
-
Dan CM. Cloud computing: theory and practice. 3rd ed. United States: Morgan Kaufmann; 2022.
Google Scholar
8
-
Huynh TTB, Pham DT, Ta BT. New approach to solving the clustered shortest-path tree problem based on reducing the search space of evolutionary algorithm. Knowledge-Based Syst. 2019 Sep 15; 180: 12–25. doi: 10.1016/j.knosys.2019.05.015.
Google Scholar
9
-
Shou YC, Jen HC. Varietal hypercube-a new interconnection network topology for large scale multicomputer. Proc. Internatoinal Conf. Parallel Distrib. Syst. 1994 Dec 19-21; Hsinchu, Taiwan: IEEE; 2002.
Google Scholar
10
-
Mohammad Q. Multilayer Hex-Cells: A New Class of Hex-Cell Interconnection Networks for Massively Parallel Systems. Int. J. Communications, Network and System Sciences. 2011 Nov; 4:704–708. doi: 10.4236/ijcns.2011.411086.
Google Scholar
11
-
Basel AM, Mohammad A, Tasneem MA, Elham FA, Nesreen AH. The optical chained-cubic tree interconnection network: topological structure and properties. Comput. & Electr. Eng. 2012 Mar; 38(2): 330–345.
Google Scholar
12
-
Youcef S, Martin S. Topological properties of hypercubes. IEEE Trans. Comput. 1988 July; 37(7): 867–872. doi: 10.1109/12.2234.
Google Scholar
13
-
Nibedita A, Singh A, Nirmal K. Reliable, Effective and Fault-Tolerant design of Leafy cube interconnection network topology. Int. J. Innov. Technol. Explor. Eng. 2019; 8(12): 3163–3170.
Google Scholar
14
-
Nuntipat P, Jeeraporn W. Shortest-path routing for optimal all-to-all personalized-exchange embedding on hierarchical hypercube networks. J. Parallel Distrib. Comput. 2021 Apr; 150: 139–154. doi: 10.1016/j.jpdc.2021.01.004.
Google Scholar
15
-
Orieb A, Mohammad Q, Wesam A, Maha S. A new hierarchical architecture and protocol for key distribution in the context of IoT-based smart cities. J. Inf. Secur. Appl. 2022 June; 67: 103173. doi: 10.1016/j.jisa.2022.103173.
Google Scholar
16
-
Awad IQ. Embedding Hex-Cells into Tree-Hypercube Networks. IJCSI International Journal of Computer Science Issues. 2013 May; 10(3): 136–143.
Google Scholar
17
-
Wei MC, Gen HC, Frank DH. Generalized diameters of the mesh of trees. Theory Comput. Syst. 2004 May 14; 37(4): 547–556. doi: 10.1007/s00224-004-1115-0.
Google Scholar
18
-
Loucif S, Ould MK, Al-Ayyoub A. Hypermeshes: Implementation and performance. J. Syst. Archit. 2002 Sep; 48(1–3): 37–47. doi: 10.1016/S1383-7621(02)00063-2.
Google Scholar
19
-
Narcisa RM, Alassio F. Fintech frontiers in quantum computing, fractals, and blockchain distributed ledger: Paradigm shifts and open innovation. J. Open Innov. Technol. Mark. Complex. 2021 Jan 07; 7(1): 1–19. doi: 10.3390/joitmc7010019.
Google Scholar
20
-
Akhlaq H, Manykyala NN, Movva SC, Mohammad S. Fractals: An Eclectic Survey, Part-I. Fractal Fract. 2022 Feb 06; 6(2): 1-35, doi: 10.3390/fractalfract6020089.
Google Scholar
21
-
Yuanyuan L, Jiaqi F, Lifeng X. Average geodesic distance on stretched Sierpiński gasket. Chaos, Solitons & Fractals. 2021 Sep; 150: 111120. doi: 10.1016/j.chaos.2021.111120.
Google Scholar
22
-
Fatemeh J, Dawn CP. An Overview of Fractal Geometry Applied to Urban Planning. Land. 2022 Mar 25; 11(4): 1-23. doi: 10.3390/land11040475.
Google Scholar
23
-
Kavitha K. Design of a Sierpinski Gasket Fractal Bowtie Antenna for Multiband Applications. Int. J. Appl. Eng. Res. 2018; 13(9): 6865–6869. Available from: http://www.ripublication.com.
Google Scholar
24
-
Xiaotian Y, Weiqing Z, Peiliang Z, Shengjun Y. Confined electrons in effective plane fractals. 2020 Dec 28; 102(24):1-10. doi: 10.1103/PhysRevB.102.245425.
Google Scholar
25
-
Elham S, Mohammad AA, Tirdad SA. Higuchi fractal dimension: An efficient approach to detection of brain entrainment to theta binaural beats. Biomedical Signal Processing and Control. 2021 July; 68: 102580. doi: 10.1016/j.bspc.2021.102580.
Google Scholar
26