# E2E Delay Guarantee for the Tactile Internet via joint NFV and Radio   Resource Allocation

**Authors:** Narges Gholipoor, Hamid Saeedi, Nader Mokari, Eduard Jorswieck

arXiv: 1907.00391 · 2019-11-11

## TL;DR

This paper proposes a joint resource allocation scheme for the Tactile Internet that considers both radio and NFV resources to meet ultra-low end-to-end delay requirements, using advanced optimization techniques.

## Contribution

It introduces the first joint R-RA and NFV-RA framework considering all delay components in a heterogeneous network for TI.

## Key findings

- Significant reduction in network costs with joint optimization.
- Effective delay guarantees for each user in TI.
- Validation of proposed algorithms through simulations.

## Abstract

The Tactile Internet (TI) is one of the next generation wireless network services with end to end (E2E) delay as low as 1~ms. Since this ultra low E2E delay cannot be met in the current 4G network architecture, it is necessary to investigate this service in the next generation wireless network by considering new technologies such as network function virtualization (NFV). On the other hand, given the importance of E2E delay in the TI service, it is crucial to consider the delay of all parts of the network, including the radio access part and the NFV core part. In this paper, for the first time, we investigate the joint radio resource allocation (R-RA) and NFV resource allocation (NFV-RA) in a heterogeneous network where queuing delays, transmission delays, and delays resulting from virtual network function (VNF) execution are jointly considered. For this setup, we formulate a new resource allocation (RA) problem to minimize the total cost function subject to guaranteeing E2E delay of each user. Since the proposed optimization problem is highly non-convex, we exploit alternative search method (ASM), successive convex approximation (SCA), and heuristic algorithms to solve it. Simulation results reveal that in the proposed scheme can significantly reduce the network costs compared to the case where the two problems are optimized separately.

## Full text

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## Figures

23 figures with captions in the complete paper: https://tomesphere.com/paper/1907.00391/full.md

## References

45 references — full list in the complete paper: https://tomesphere.com/paper/1907.00391/full.md

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Source: https://tomesphere.com/paper/1907.00391