By bringing Cloud-like services much closer to endusers and their devices, Fog computing is foreseen to expand the scope of overlay networks, encompassing different heterogeneity dimensions (i.e., size, geographical distribution, devices/virtual objects (VOs) involved, quality of service (QoS) requirements, etc.). Although highly flexible solutions like Software-Defined Networking (SDN) have been conceived to handle such heterogeneity in future networks, scalability is still an open issue, especially with respect to Fog computing requirements. In this paper, we propose an SDN-based network slicing scheme for supporting multi-domain Fog/Cloud services, which offers high scalability, among other aspects, over legacy ones. Results show that the number of unicast forwarding rules needed to be installed in an overlay drops by up to over one order of magnitude and 4 times compared to the "fully-meshed" and OpenStack cases, respectively, at the cost of possible path sub-optimality, albeit knowledge on the datacenter topology can be used for VO placement optimization.

A scalable SDN slicing scheme for multi-domain fog/cloud services

Bruschi, Roberto;Davoli, Franco;Lago, Paolo;Pajo, Jane Frances
2017-01-01

Abstract

By bringing Cloud-like services much closer to endusers and their devices, Fog computing is foreseen to expand the scope of overlay networks, encompassing different heterogeneity dimensions (i.e., size, geographical distribution, devices/virtual objects (VOs) involved, quality of service (QoS) requirements, etc.). Although highly flexible solutions like Software-Defined Networking (SDN) have been conceived to handle such heterogeneity in future networks, scalability is still an open issue, especially with respect to Fog computing requirements. In this paper, we propose an SDN-based network slicing scheme for supporting multi-domain Fog/Cloud services, which offers high scalability, among other aspects, over legacy ones. Results show that the number of unicast forwarding rules needed to be installed in an overlay drops by up to over one order of magnitude and 4 times compared to the "fully-meshed" and OpenStack cases, respectively, at the cost of possible path sub-optimality, albeit knowledge on the datacenter topology can be used for VO placement optimization.
2017
9781509060085
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/881397
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