Joint Task Offloading and Routing in Wireless Multi-hop Networks Using Biased Backpressure Algorithm

A significant challenge for computation offloading in wireless multi-hop networks is the complex interactions among traffic flows in the presence of interference. Existing approaches often ignore these key effects and/or rely on outdated queueing and channel state information. To fill these gaps, we reformulate joint offloading and routing as a routing problem on an extended graph with physical and virtual links. We adopt the state-of-the-art shortest path-biased Backpressure routing algorithm, which allows the destination and the route of a job to be dynamically adjusted at every time step based on network-wide long-term information and real-time states of local neighborhoods. In large networks, our approach achieves smaller makespan than existing approaches, such as separated Backpressure offloading, and joint offloading and routing based on linear programming.

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Publication Details

Published
2025-03-12
DOI
https://doi.org/10.1109/icassp49660.2025.10888598
Citations
3
Primary Topic
Energy Efficient Wireless Sensor Networks
Type
article
Field-Weighted Citation Impact
4.46

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Joint Task Offloading and Routing in Wireless Multi-hop Networks Using Biased Backpressure Algorithm

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Joint Task Offloading and Routing in Wireless Multi-hop Networks Using Biased Backpressure Algorithm

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article en
3 citations

Abstract

A significant challenge for computation offloading in wireless multi-hop networks is the complex interactions among traffic flows in the presence of interference. Existing approaches often ignore these key effects and/or rely on outdated queueing and channel state information. To fill these gaps, we reformulate joint offloading and routing as a routing problem on an extended graph with physical and virtual links. We adopt the state-of-the-art shortest path-biased Backpressure routing algorithm, which allows the destination and the route of a job to be dynamically adjusted at every time step based on network-wide long-term information and real-time states of local neighborhoods. In large networks, our approach achieves smaller makespan than existing approaches, such as separated Backpressure offloading, and joint offloading and routing based on linear programming.

United States Army Combat Capabilities Development Command (US), Rice University (US)
Arm
Affordable and clean energy
Openalex Percentile: Top 6%
Energy Efficient Wireless Sensor Networks
4.46
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