![]() To fulfill the required level of demand, some approaches tackled network aspects so to host a huge number of servers while others focused on delivering rapid services to the clients by minimizing the path length between any two servers. In recent years, data centers have witnessed an exponential growth for hosting hundreds of thousands of servers as well as to accommodating a very large demand for resources. Moreover, P-Cube extremely outperforms Fat-tree, and BCube structures in terms of total cost, complexity of cabling and power consumption. Finally, numerical results are provided to show that our proposed topology is a promising structure as it outperforms other topologies and it is superior to Fat-tree, BCube and DCell by approximately 24%, 16% and 8% respectively in terms of network throughput and latency. We design a routing algorithm for P-Cube network that utilizes the P-Cube structure to strike a balance among the numerous links in the network. Additionally, P-Cube is highly scalable to encompass hundreds of thousands of servers with a low stable diameter and high bisection width. P-Cube provides high performance in network latency and throughput and fault tolerance. Our new network topology, named “Parallel Cubes”(PCube), is a duplicate defined structure that utilizes the ports in the servers and mini-switches to form a highly effective, scalable, and efficient network structure. Effective exploitation of the ports of interest for building the topology structure can help in realizing the potentialities of reducing ex- pensive topology. We observe that current DCs use servers that mostly come with dual ports. In this paper, we investigate the server-centric structure. DCN faces a lot of difficulties like the effective exploitation of DC components that, if highlighted, can aid in constructing high performance, scalable, reliable, and cost-effective DCN. Connecting a large number of servers with high bandwidth links is one of the most crucial and challenging tasks that the Data Center Network (DCN) must fulfill. ![]()
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January 2023
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