A Note to Non-adaptive Broadcasting
Broadcasting is a fundamental problem in the information dissemination area. In classical broadcasting, a message must be sent from one network member to all other members as rapidly as feasible. Although it has been demonstrated that this problem is NP-Hard for arbitrary graphs, it has several appl...
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| Published in | Parallel processing letters Vol. 34; no. 1 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Singapore
World Scientific Publishing Company
01.03.2024
World Scientific Publishing Co. Pte., Ltd |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0129-6264 1793-642X |
| DOI | 10.1142/S0129626423400170 |
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| Summary: | Broadcasting is a fundamental problem in the information dissemination area. In classical broadcasting, a message must be sent from one network member to all other members as rapidly as feasible. Although it has been demonstrated that this problem is NP-Hard for arbitrary graphs, it has several applications in various fields. As a result, the universal lists model, replicating real-world restrictions like the memory limits of nodes in large networks, is introduced as a branch of this problem in the literature. In the universal lists model, each node is equipped with a fixed list and has to follow the list regardless of the originator.
In this study, we focus on the non-adaptive branch of universal lists broadcasting. In this regard, we establish the optimal broadcast time of
k
-ary trees and binomial trees under the non-adaptive model and provide an upper bound for complete bipartite graphs. We also improved a general upper bound for trees under the same model and showed that our upper bound cannot be improved in general. |
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| Bibliography: | This article is in the “Special issue on Graph and Combinatorial Optimization for Big Data Intelligence with Parallel Processing”, edited by Xiaoyan Zhang (Nanjing Normal University, China), Eddie Cheng (Oakland University, USA), Longkun Guo (Fuzhou University, China) & Yaping Mao (Qinghai Normal University, China). ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 0129-6264 1793-642X |
| DOI: | 10.1142/S0129626423400170 |