Skip to content
Open access

ILP Formulation and Exact Solution of Multicast Routing with Fairness

Aug 2026 · Mathematics · Vol 14, pp. 2900 · 0 citations · 20 references

TL;DR

This work studies fairness-aware multicast routing under two parameters: the maximum end-to-end delay (Δ) and the inter-destination delay variation (δ) and presents flow-based ILP formulations that treat Δ and δ as either objectives or constraints.

Abstract

Fairness is critical in delay-sensitive group applications—multiplayer online games, live collaborative editing, and distributed interactive simulations—where every participant should receive each message within a bounded delay and with minimal timing differences between recipients. We study fairness-aware multicast routing under two parameters: the maximum end-to-end delay (Δ) and the inter-destination delay variation (δ). Although several heuristics address this NP-hard problem and exact integer linear programs (ILPs) exist for the minimum-cost multi-constrained case, exact methods that directly optimize inter-destination delay variation under bounded delay remain underexplored. We present flow-based ILP formulations that treat Δ and δ as either objectives or constraints. Their feasible solutions are partial spanning hierarchies, a class that contains partial spanning trees as a special case; consequently a hierarchy optimum is, by construction, at least as good as the best tree-constrained solution. On proven-optimal instances, hierarchy optima reduce inter-destination delay variation considerably relative to the best tree-constrained solution. A sensitivity analysis, a real-topology study on the Abilene backbone, and an exact-ILP scalability study quantify and corroborate these gains.

Read PDF

Similar papers

Conference Jul 2026

Optimal vCDN Placement in Fixed Broadband Networks: A Multi-Objective ILP Formulation with Partial Caching

This paper proposes a multi-objective Integer Linear Programming (ILP) formulation for optimal virtual Content Delivery Network (vCDN) placement in fixed broadband networks. The proposed framework jointly minimizes backhaul traffic and end-to-end latency across a six-tier topology spanning OLT, Tier 2/Tier 1 aggregatio...

Yohana Jayanti Aruan, R. Munadi, S. Hertiana et al. · 0 citations
Jul 2026

Online Fair Division with Budget Constraints

We study an online variant of discrete fair division under generalized assignment budget constraints. Goods arrive one at a time and must be assigned irrevocably to a feasible agent or to charity, which holds all unallocated goods, while fairness is evaluated only against budget-feasible subsets of every recipient's bu...

Saar Cohen, Nicholas J. Teh, Paul W. Goldberg et al. · 1 citation
Jul 2026

A Dual-Guided Exact Algorithm for the Two-Constraint Path Problem

A dual-guided exact algorithm that effectively bridges the gap between the computational efficiency of Lagrangian relaxation and the optimality guarantees of combinatorial search and reduces the execution time by orders of magnitude compared to traditional exact methods.

Kaixiang Hu, Xian-Kai Li, Caixia Kou · 0 citations
2026

Delay-Optimal Congestion-Aware Routing and Computation Offloading in Arbitrary Networks

Emerging edge computing paradigms enable heterogeneous devices to collaborate on complex computation applications. However, for arbitrary heterogeneous edge networks, delay-optimal forwarding and computation offloading for long-term average performance remains an open problem. In this paper, we jointly optimize data/re...

Jin-Kun Zhang, Yuezhou Liu, Edmund Yeh · 0 citations
Preprint Aug 2026

Online Multi-Level Aggregation with Per-Batch Maximum Delay

The deterministic guarantee matches the known fixed-node lower bound, and the matching randomized lower bound are proved, ensuring that both guarantees are optimal on every nondegenerate rooted tree.

Tian-Han Lu, Run-Tian Ren, Sheng-Cai Liu et al. · 3 citations
Preprint Sep 2026

On the Delay-Constrained Maximum Concurrent Flow Problem

Real-time services, such as VoIP and large-scale neural network training, require strict transmission delay guarantees. While routing under hop constraints is tractable, real-world delays increase sharply with equipment load, typically modeled using the M/M/1 queuing function where delay is inversely proportional to av...

W. Ben-Ameur, Guillaume Beraud-Sudreau, H. Kerivin et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.