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Network slicing of multi-access edge computing (MEC) resources is expected tobe a pivotal technology to the success of 5G networks and beyond. The keychallenge that sets MEC slicing apart from traditional resource allocationproblems is that edge nodes depend on tightly-intertwined andstrictly-constrained networking, computation and storage resources. Therefore,instantiating MEC slices without incurring in resource over-provisioning ishardly addressable with existing slicing algorithms. The main innovation ofthis paper is Sl-EDGE, a unified MEC slicing framework that allows networkoperators to instantiate heterogeneous slice services (e.g., video streaming,caching, 5G network access) on edge devices. We first describe the architectureand operations of Sl-EDGE, and then show that the problem of optimallyinstantiating joint network-MEC slices is NP-hard. Thus, we proposenear-optimal algorithms that leverage key similarities among edge nodes andresource virtualization to instantiate heterogeneous slices 7.5x faster andwithin 0.25 of the optimum. We first assess the performance of our algorithmsthrough extensive numerical analysis, and show that Sl-EDGE instantiates slices6x more efficiently then state-of-the-art MEC slicing algorithms. Furthermore,experimental results on a 24-radio testbed with 9 smartphones demonstrate thatSl-EDGE provides at once highly-efficient slicing of joint LTE connectivity,video streaming over WiFi, and ffmpeg video transcoding.

Sl-EDGE: Network Slicing at the Edge