Energy-delay tradeoff for virtual machine placement in virtualized multi-access edge computing: a two-sided matching approach

Abstract

By decoupling network functions from the underlying physical machines (PMs) at the edge of the networks, the virtualized multi-access edge computing (MEC) enables deployment of new network services and elastic network scaling to reduce the maintenance costs in a more flexible, scalable and cost-effective manner. Although there are appealing performance gains to be achieved, the placement of virtual machines (VMs) on top of the sharing PMs to support computation-intensive applications for smart mobile devices becomes a major challenge, especially for an increasing network scale. In this paper, we attempt to deal with the VM placement problem in virtualized MEC system, which is targeted for finding a performance balance between energy consumption and computing/offloading delay. To capture such a tradeoff for VM placement, we formulate a weighted sum based cost minimization problem as a pure 0–1 integer linear programming problem, which is NP-complete and very difficult to solve with lower complexity. Based on the one-to-one mapping relation constraint, the VM placement problem is then converted into a many-to-many two-sided matching problem between the VM instances and the PMs. Motivated by the student project allocation problem, we develop an extended two-sided matching algorithm with lower computational complexity for solving the matching problem. Simulation results are presented to show the effectiveness of our proposed algorithm, and the normalization factor is of great significance to obtain the lower total cost.