E2E QoS Guarantee for the Tactile Internet via Joint NFV and Radio Resource Allocation

• Published in: IEEE eTransactions on network and service management Vol. 17; no. 3; pp. 1788 - 1804
• Main Authors: Gholipoor, Narges, Saeedi, Hamid, Mokari, Nader, Jorswieck, Eduard A.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Approximation; Computer architecture; Computer simulation; Cost function; Delay; Delays; end-to-end (E2E) delay; Heuristic methods; network function virtualization (NFV); network service (NS); New technology; Next generation networking; Optimization; Quality of service; Queues; queuing delay; Radio; Resource allocation; Resource management; Servers; Tactile Internet (TI); transmission delay; Ultra reliable low latency communication; Virtual networks; virtualized network function (VNF); Wireless networks
• ISSN: 1932-4537; 1932-4537
• DOI: 10.1109/TNSM.2020.3001359

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 networks 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 connection. 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. Besides, for the NFV-RA, we propose an online heuristic algorithm, and analyze its performance for the TI service. Simulation results reveal that the proposed scheme can significantly reduce the network costs compared to the case where the two problems are optimized separately. Moreover, we compare the online algorithm with its offline counterpart as well as a baseline approach and it is shown that the online algorithm outperforms both of them.