5G networks are characterized by massive device connectivity, supporting a wide range of novel applications with their diverse Quality of Service (QoS) requirements. This poses a challenge since 5G as one-fits-all technology has to simultaneously address all these requirements. Network slicing has been proposed to cope with this challenge, calling for efficient slicing and slice placement strategies in order to ensure that the slice requirements (e.g., latency, data rate) are met, while the network resources are utilized in the most optimal manner. In this paper, we compare different end-to-end (E2E) slice placement strategies by formulating and solving a Mixed Integer Linear Programming (MILP) slice placement problem and study their trade-offs. E2E slice requests are modelled as Service Functions Chains (SFC), in which each core network and radio access network component is represented as a Virtual Network Function (VNF). Based on the analysis of the results, we then propose a slice placement heuristic algorithm whose objective is to minimize the number of VNF migrations in the network and their impact onto the slices while, at the same time, optimizing the network utilization and making sure that the QoS requirements of the considered slice requests are satisfied. The results of the simulations demonstrate the efficiency of the proposed algorithm.

Orchestrating End-to-end Slices in 5G Networks

Roberto Riggio
2019

Abstract

5G networks are characterized by massive device connectivity, supporting a wide range of novel applications with their diverse Quality of Service (QoS) requirements. This poses a challenge since 5G as one-fits-all technology has to simultaneously address all these requirements. Network slicing has been proposed to cope with this challenge, calling for efficient slicing and slice placement strategies in order to ensure that the slice requirements (e.g., latency, data rate) are met, while the network resources are utilized in the most optimal manner. In this paper, we compare different end-to-end (E2E) slice placement strategies by formulating and solving a Mixed Integer Linear Programming (MILP) slice placement problem and study their trade-offs. E2E slice requests are modelled as Service Functions Chains (SFC), in which each core network and radio access network component is represented as a Virtual Network Function (VNF). Based on the analysis of the results, we then propose a slice placement heuristic algorithm whose objective is to minimize the number of VNF migrations in the network and their impact onto the slices while, at the same time, optimizing the network utilization and making sure that the QoS requirements of the considered slice requests are satisfied. The results of the simulations demonstrate the efficiency of the proposed algorithm.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11566/291245
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