  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.
