Energy-Delay Tradeoff for Virtual Machine Placement in Virtualized Multi-Access Edge Computing: A Two-Sided Matching Approach
2021
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
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 the 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 complex to solve with lower complexity. Based on the one-to-one mapping relation constraint, the VM placement
problem is 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 many-to-many matching problem. Simulation results are presented to demonstrate the effectiveness of our
proposed matching algorithm, and the normalization factor is of great
significance to obtain lower total cost.
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