数据中心网络中基于可信容错路由的安全路径

IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Concurrency and Computation-Practice & Experience Pub Date : 2024-07-25 DOI:10.1002/cpe.8229
Kaiyun Liu, Weibei Fan, Fu Xiao, Haolin Mao, Huipeng Huang, Yizhou Zhao
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引用次数: 0

摘要

摘要随着数据中心网络(DCN)规模的不断扩大,网络出现故障的概率也越来越高。可信的容错路由对于数据中心的可靠通信意义重大。在本文中,我们针对基于环的 DCN 提出了一种新型容错路由方案,以应对这一挑战。首先,我们提出了一种基于可达路径信任度的多路径信息传输模型,并提出了一种无死锁的新型哈密尔顿奇偶转向模型。其次,我们设计了一种高效的无死锁故障路由算法,在 DCN 中任意两个无故障节点之间构建最长的无故障路径。大量仿真结果表明,所提出的容错路由算法优于之前的算法。与最先进的容错路由算法相比,所提出的算法在吞吐量和数据包到达率方面提高了 21.5% 至 25.3%。此外,它还能将网络中的平均延迟和最大延迟分别降低 18.6% 和 23.7%。
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Secure paths based trustworthy fault-tolerant routing in data center networks

With the continuous expansion scale of data center networks (DCNs), the probability of network failures becomes high. Trustworthy fault-tolerant routing is extremely significant for reliable communication in data centers. In this article, we tackle the challenge by proposing a novel fault-tolerant routing scheme for a torus-based DCN. First, we present a multipath information transmission model based on the trust degree of reachable paths and propose a novel Hamiltonian odd–even turning model without deadlock. Second, we design an efficient deadlock-free fault-routing algorithm by constructing the longest fault-free path between any two fault-free nodes in DCN. Extensive simulation results show that the proposed fault-tolerant routing outperforms the previous algorithms. Compared with the most advanced fault-tolerant routing algorithms, the proposed algorithm has a 21.5% to 25.3% increase in throughput and packet arrival rate. Moreover, it can reduce the average delay of 18.6% and the maximum delay of 23.7% in the network respectively.

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来源期刊
Concurrency and Computation-Practice & Experience
Concurrency and Computation-Practice & Experience 工程技术-计算机:理论方法
CiteScore
5.00
自引率
10.00%
发文量
664
审稿时长
9.6 months
期刊介绍: Concurrency and Computation: Practice and Experience (CCPE) publishes high-quality, original research papers, and authoritative research review papers, in the overlapping fields of: Parallel and distributed computing; High-performance computing; Computational and data science; Artificial intelligence and machine learning; Big data applications, algorithms, and systems; Network science; Ontologies and semantics; Security and privacy; Cloud/edge/fog computing; Green computing; and Quantum computing.
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