Fault Tolerance of Optical Hypercube Interconnection Networks with r -Communication Pattern

Author:

Li Xianyong1ORCID,Du Yajun1,Fan Yongquan1

Affiliation:

1. School of Computer and Software Engineering, Xihua University, Chengdu 610039, China

Abstract

As power grids and optical interconnection networks are interdependent, the reliabilities of the optical networks are critical issues in power systems. The optical networks hold prominent performance including wide bandwidth, low loss, strong anti-interference capability, high fidelity, and reliable performance. They are regarded as promising alternatives to electrical networks for parallel processing. This paper is aimed at taking the first step in understanding the communication efficiencies of optical networks. For that purpose, on optical networks, we propose a series of novel notions including communication pattern, r -communication graph, reduced diameter, enhanced connectivity, r -diameter, and r -connectivity. Using these notions, we determine that the r -diameter and r -connectivity of the optical n -dimensional hypercube network are n / r and n 1 + n 2 + + n r , respectively. Since the parameter r is variable, we can adjust different values of r on the basis of the wavelength resources and load of the optical networks, achieving enhanced communication efficiencies of these networks. Compared with the electric n -dimensional hypercube network, the proposed communication pattern on the optical hypercube network not only reduces the maximum communication delay of the conventional electrical hypercube significantly but also improves its fault tolerance remarkably.

Funder

Guangdong Medical University

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Super Structure Fault-Tolerance Assessment of the Generalized Hypercube;The Computer Journal;2023-07-29

2. Evaluating BERT on cloud-edge time series forecasting and sentiment analysis via prompt learning;2022 IEEE 24th Int Conf on High Performance Computing & Communications; 8th Int Conf on Data Science & Systems; 20th Int Conf on Smart City; 8th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys);2022-12

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