Survivable Task Allocation in Cloud Radio Access Networks with Mobile-Edge Computing

Song Yang*, Nan He, Fan Li, Stojan Trajanovski, Xu Chen, Yu Wang, Xiaoming Fu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)

Abstract

Cloud radio access network (C-RAN) is a promising 5G network architecture by establishing baseband units (BBU) pools to perform baseband processing functionalities and deploying remote radio heads (RRHs) for wireless signal transmission and reception. Mobile-edge computing (MEC) offers a way to shorten the service delay by building small-scale cloud infrastructures at the network edge. By co-locating the BBU pool with edge cloud at the so-called BBU node, we can take full advantages of C-RAN and MEC for better spectrum utilization and delay-guaranteed services. In this article, we first study how to allocate each user's task to the BBU node and find the path from his/her accessing RRH node to the BBU node such that the maximum service delay among all the requests is minimized. We then consider this problem with survivability concerns, which is to use both primary and backup BBU nodes to issue the request such that the primary path and backup path are link disjoint. We analyze the complexities of these two problems and prove they are NP-hard in general. Subsequently, we devise a randomized approximation algorithm and an efficient heuristic to solve the considered problems, respectively. The simulation results show that the proposed algorithms outperform two benchmark heuristics in terms of acceptance ratio and maximum service delay.

Original languageEnglish
Article number9144505
Pages (from-to)1095-1108
Number of pages14
JournalIEEE Internet of Things Journal
Volume8
Issue number2
DOIs
Publication statusPublished - 15 Jan 2021

Keywords

  • Cloud radio access network (C-RAN)
  • delay
  • mobile-edge computing (MEC)
  • survivability
  • task allocation

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