Zhaohong Lu | Searcharxiv

arXiv2026

Message-Level Scheduling for RLNC-Coded Multi-Source Traffic

This paper studies weighted decoding-delay minimization for multiple RLNC-coded message streams that compete for finite processing capacity at a destination. Packet arrivals are exogenous, while the scheduler only determines the processing order of packets already available at the destination. A trace-conditioned offline scheduling formulation shows that a batch-release subclass is strongly NP-hard even with a single processing unit. Message-Aware Innovation-Deficit Scheduling (MAIDS) is then developed to prioritize each serviceable message according to its weight and remaining decoding deficit. For a single processing unit, MAIDS is shown to be exactly optimal under nonblocking progressive arrivals with equal weights and under common activation with arbitrary positive weights, while the unrestricted weighted online problem admits no universal deterministic $O(1)$ competitive ratio. Simulation results on streaming and batch benchmarks show that MAIDS consistently reduces weighted decoding delay relative to the tested baselines, remains close to the offline optimum on average, and recovers the predicted exact performance boundaries.

cs.NI↗

arXiv2026

Theoretical Delay Analysis of Network Coding Enabled M-to-N Broadcasting in Ad-Hoc Networks

In this paper, we investigate the delay performance of ad hoc broadcast networks in which random linear network coding is used to support M-to-N information dissemination. Multiple source nodes may inject coded packets for the same message, while multiple destination nodes decode the message after collecting a sufficient number of innovative degrees of freedom. Because broadcast forwarding does not rely on predetermined end-to-end routes, the packet-level relay sequence is generally random and depends on propagation delay, queueing delay, and prior reception history. We first prove that, when queueing, contention, processing, and retransmission delays are ignored, the first-reception time under fastest-only broadcast is exactly equal to the multi-source shortest-path distance, which provides a lower bound on propagation delay. We then develop an equivalent fixed-route queueing approximation to estimate relay-node load, stability, and end-to-end delay under M/D/1 and G/D/1 models. To account for route diversity under congestion, we further introduce a congestion-cost path approximation that penalizes heavily loaded relays. Simulation results on random and structured topologies show that the proposed framework captures the main delay trends under different traffic intensities and network densities while remaining simple for tractable analytical evaluation.

cs.NI↗