arXiv subjects

Negar Erfaniantaghvayi

Publications and source records attributed to Negar Erfaniantaghvayi.

3 recordsLinked to original sources

arXiv2026

Ant Backpressure Routing for Dynamic Wireless Multi-hop Networks with Mixed Traffic Patterns

Backpressure (BP) routing and its shortest-path biased variant (SP-BP) provide powerful congestion-aware multipath resource allocation for wireless multi-hop networks, but they rely on per-commodity queueing and slot-by-slot control that may be difficult to realize under practical or legacy forwarding architectures. Moreover, even state-of-the-art SP-BP still suffers from the last-packet problem when short-lived traffic coexists with streaming flows. To address these limitations, we propose Ant Backpressure (Ant-BP), a periodic and fully distributed routing scheme that decouples route learning from packet forwarding. Ant-BP uses virtual SP-BP to construct pheromone-based forwarding probabilities, while actual packets are forwarded through per-neighbor first-in-first-out (FIFO) queues with probabilistic next-hop selection. This architecture enables link-capacity sharing across commodities, mitigates starvation of short-lived traffic, and extends the benefits of SP-BP to network architectures based on per-neighbor FIFO forwarding. Through periodic virtual updates, Ant-BP also adapts to transient link failures and mobility-induced topology changes. Our theoretical analysis and simulations show that, compared with conventional ant colony optimization (ACO) routing, virtual SP-BP enables Ant-BP to establish higher-quality forwarding policies with lower overhead. As a result, Ant-BP improves latency and delivery ratio over SP-BP and ACO-based baselines under mixed streaming and bursty traffic, achieves throughput comparable to SP-BP at low and medium traffic load, and remains robust to mismatched virtual-traffic assumptions, transient link failures, and node mobility.

cs.NI↗

arXiv2025

SeLR: Sparsity-enhanced Lagrangian Relaxation for Computation Offloading at the Edge

This paper introduces a novel computational approach for offloading sensor data processing tasks to servers in edge networks for better accuracy and makespan. A task is assigned with one of several offloading options, each comprises a server, a route for uploading data to the server, and a service profile that specifies the performance and resource consumption at the server and in the network. This offline offloading and routing problem is formulated as mixed integer programming (MIP), which is non-convex and HP-hard due to the discrete decision variables associated to the offloading options. The novelty of our approach is to transform this non-convex problem into iterative convex optimization by relaxing integer decision variables into continuous space, combining primal-dual optimization for penalizing constraint violations and reweighted $L_1$-minimization for promoting solution sparsity, which achieves better convergence through a smoother path in a continuous search space. Compared to existing greedy heuristics, our approach can achieve a better Pareto frontier in accuracy and latency, scales better to larger problem instances, and can achieve a 7.72--9.17$\times$ reduction in computational overhead of scheduling compared to the optimal solver in hierarchically organized edge networks with 300 nodes and 50--100 tasks.

cs.NI↗

arXiv2024

Ant Backpressure Routing for Wireless Multi-hop Networks with Mixed Traffic Patterns

A mixture of streaming and short-lived traffic presents a common yet challenging scenario for Backpressure routing in wireless multi-hop networks. Although state-of-the-art shortest-path biased backpressure (SP-BP) can significantly improve the latency of backpressure routing while retaining throughput optimality, it still suffers from the last-packet problem due to its inherent per-commodity queue structure and link capacity assignment. To address this challenge, we propose Ant Backpressure (Ant-BP), a fully distributed routing scheme that incorporates the multi-path routing capability of SP-BP into ant colony optimization (ACO) routing, which allows packets of different commodities to share link capacity in a first-in-first-out (FIFO) manner. Numerical evaluations show that Ant-BP can improve the latency and delivery ratio over SP-BP and ACO routing schemes, while achieving the same throughput of SP-BP under low-to-medium traffic loads.

cs.NI↗