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Irregularity-Based Entropy Inequalities Determining Complete Interconnection Network Complexity | ||
| Communications in Combinatorics and Optimization | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 30 خرداد 1405 اصل مقاله (865.48 K) | ||
| نوع مقاله: Original paper | ||
| شناسه دیجیتال (DOI): 10.22049/cco.2026.31502.2870 | ||
| نویسندگان | ||
| Asfand Fahad1؛ Muhammad Imran Qureshi2؛ Muhammad Anwar Chaudhry3؛ Rida Irfan4؛ Anas Ashraf2؛ Yilun Shang* 5 | ||
| 1Centre for Advanced Studies in Pure and Applied Mathematics, Bahauddin Zakariya University, Multan, 60000, Pakistan | ||
| 2Department of Mathematics, COMSATS University Islamabad, Vehari Campus, Vehari, 61100, Pakistan | ||
| 3Department of Mathematics and Statistics, Institute of Southern Punjab, Multan 60800, Pakistan | ||
| 4Department of Mathematics, COMSATS University Islamabad, Sahiwal Campus, Sahiwal, 57000, Pakistan | ||
| 5University of Northumbria | ||
| چکیده | ||
| In contemporary scientific research, network analysis theory contributes significantly to diverse systems, including forecasting cetane numbers, examining thermal transport phenomena, addressing sustainability in supply chains, monitoring postoperative health, shaping public policy through social networks, and investigating phase transitions in storage tanks. Various Interconnection networks (ICNs) are discriminated based on attributes such as bandwidth, latency, switch radix, and network topology. Entropy is pivotal in extracting meaningful information from these scientific models, thereby enhancing their efficiency. The butterfly and Benes networks and their derived networks are widely utilized in diverse systems, including IBM, NEC Cenju-3, MIT Transit Project, optical coupler internal structures, permutation routing, chip networks, and multiprocessor systems. To extract meaningful information, a few models to discriminate these networks on the basis of their entropy and complexity have been introduced in recent research. In this paper, we propose an entropy-determining model based on the irregularity of these ICNs, which is applied to obtain mathematical formulae for entropy determination, leading to complexity analysis of these ICNs. The analysis shows that we determine explicit inequalities through numeric data produced by these formulae, thus giving a complete characterization of this family of ICNs and answering the recently posed questions. | ||
| کلیدواژهها | ||
| Irregularity-based Entropy؛ Complexity؛ Information functional؛ Network analysis؛ Interconnection networks | ||
| مراجع | ||
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