Payment Channel Network-Enabled Multi-Hop Task Offloading for UAV-Relayed MEC

Abstract

Multi-Access Edge Computing is in great demand for improved computation access and low-latency services. In remote regions or infrastructure-hit areas, Unmanned Aerial Vehicles (UAVs) are envisioned to relay tasks from User Equipments (UEs) and provide connectivity to MEC servers (MECS) in single or multiple hops. However, due to the decentralised and multi-stakeholder nature of UEs, UAVs and MECS, establishing trust and guaranteeing service fulfilment remains a significant challenge. To address these issues, we incorporate Layer-2 of Blockchain, i.e. Payment Channel Network (PCN), into a multihop task offloading scenario. A Joint Task Offloading integrated PCN Routing problem is formulated, with the goal of minimising system strain, i.e., the total latency and the cost of task computation. We propose an HTLC-based data routing mechanism that uses Lyapunov Optimisation, assigning weights to each possible edge along the routing path. The simulation performed under various task arrival rates shows that the proposed method improves the success ratio by at least $1.5 \times$, decreases the latency by at least 5% and decreases the cost by at least 3.5% when compared with multi-hop task offloading works like DQN and CLP, and PCN routing works like Flare and Speedymurmurs.