Task Offloading Optimization in NOMA-Enabled Multi-hop Mobile Edge Computing System Using Conflict Graph

TL;DR

This paper proposes a conflict graph-based optimization framework for task offloading in NOMA-enabled multi-hop MEC systems, jointly minimizing latency and energy consumption through efficient resource scheduling and power control.

Contribution

It introduces a novel conflict graph-based method for joint offloading, scheduling, and power control in multi-hop MEC with NOMA, improving resource utilization.

Findings

Proposed approaches outperform benchmark schemes in simulations.

Joint optimization reduces latency and energy consumption.

Conflict graph method enhances resource scheduling efficiency.

Abstract

Resource allocation is investigated for offloading computational-intensive tasks in multi-hop mobile edge computing (MEC) system. The envisioned system has both the cooperative access points (AP) with the computing capability and the MEC servers. A user-device (UD) therefore first uploads a computing task to the nearest AP, and the AP can either locally process the received task or offload to MEC server. In order to utilize the radio resource blocks (RRBs) in the APs efficiently, we exploit the non-orthogonal multiple access for offloading the tasks from the UDs to the AP(s). For the considered NOMA-enabled multi-hop MEC computing system, our objective is to minimize both the latency and energy consumption of the system jointly. Towards this goal, a joint optimization problem is formulated by taking the offloading decision of the APs, the scheduling among the UDs, RRBs, and APs, and UDs' transmit power allocation into account. To solve this problem efficiently, (i) a conflict graph-based approach is devised that solves the scheduling among the UDs, APs, and RRBs, the transmit power control, and the APs' computation resource allocation jointly, and (ii) a low-complexity pruning graph-based approach is also devised. The efficiency of the proposed graph-based approaches over several benchmark schemes is verified via extensive simulations.