Multi-Path and Multi-Hop Task Offloading in Mobile Ad Hoc Networks

Abstract

Edge computing offloading in remote areas is a challenging problem in 5 G and 6 G studies, since edge cloud infrastructures are often unavailable in remote areas. In these areas, using drones instead of infrastructures to provide edge computing services can be an efficient solution. However, the limited coverage of drones makes it challenging to provide effective edge computing services. In this paper, we propose an edge computing architecture based on the cooperation among the drones with and without edge servers to provide edge computing services for the users, where the computing tasks are transmitted in multi-path and multi-hop in a Mobile Ad hoc Network (MANET). To extend the lifetime of a MANET while ensuring service quality, we formulate a joint optimization problem, which assigns a suitable computing drone, a transmission path and a task division scheme for each task. The problem is investigated using a Software Defined Network (SDN) controller, which can get a partial solution of the problem through a greedy algorithm. By adding a task arrival order constraint, we approximate the original problem as a multi-path multi-hop task transmission problem, which can be solved according to the movement state of a MANET. Specifically, when a MANET is stationary, we propose a traversal method to obtain the optimal solution of the approximate problem; when a MANET is dynamic, we propose a heuristic scheme to get a suboptimal solution of the problem based on average rate. Experimental results show that our scheme has a better performance compared to typical existing ones.