TL;DR
This paper extends the Kleinberg graph model, by allowing the nodes to choose the distribution of long-range links according to the traffic demand, and shows that demand-aware small-world graphs can significantly outperform their demand-oblivious counterparts.
This work proposes a novel topology named the Balanced Sparse Tree (BST), which is a topology characterized by symmetric design and sparse connections, motivated by hypergraph theory and Steiner Systems, and demonstrates the superiority of BST over the state-of-the-art in network scale, latency, bandwidth, and cost.
This paper presents detailed algorithm for calculating L-LSR coefficient, and shows that L-LSR algorithm not only performs better than OSPF, but also has verySignificant performance improvement over the other LSR family of algorithms.
These topologies are compared to demonstrate the advantage of finding shortest path using Bhandari’s algorithm and Cycle-Based Minimum-Cost Domain-Disjoint Paths (CMCDP) Algorithm.
The results support HON as a simple low-degree construction for structured inter-group communication, whereas higher-radix, adaptive, or more richly connected fabrics remain better suited to less structured traffic and larger bandwidth demand.
The proposed Multi-Path Multi-Level Feedback Queueing (MP-MLFQ) leverages the spatial diversity and regularity of DCNs to realize a scheduler with numerous logical priority levels while occupying as low as 2 physical priority queues within network switches.
These topologies are compared to demonstrate the advantage of finding shortest path using Bhandari’s algorithm and Cycle-Based Minimum-Cost Domain-Disjoint Paths (CMCDP) Algorithm.