Dynamic 5G RAN slice adjustment and migration based on traffic prediction in WDM metro-aggregation networks

Hao Yu; Francesco Musumeci; Jiawei Zhang; Massimo Tornatore; Lin Bai; Yuefeng Ji

doi:10.1364/JOCN.403829

Dynamic 5G RAN slice adjustment and migration based on traffic prediction in WDM metro-aggregation networks

Hao Yu, Francesco Musumeci, Jiawei Zhang, Massimo Tornatore, Lin Bai, and Yuefeng Ji

Journal of Optical Communications and Networking
Vol. 12,
Issue 12,
pp. 403-413
(2020)
•https://doi.org/10.1364/JOCN.403829

Get Citation
Copy Citation Text
Hao Yu, Francesco Musumeci, Jiawei Zhang, Massimo Tornatore, Lin Bai, and Yuefeng Ji, "Dynamic 5G RAN slice adjustment and migration based on traffic prediction in WDM metro-aggregation networks," J. Opt. Commun. Netw. 12, 403-413 (2020)

Export Citation
- BibTex
- Endnote (RIS)
- HTML
- Plain Text
Get PDF (1960 KB)
Set citation alerts
Save article

Related Topics
Optics & Photonics Topics
?

The topics in this list come from the OSA Optics and Photonics Topics applied to this article.

About this Article
History
- Original Manuscript: August 5, 2020
- Revised Manuscript: September 24, 2020
- Manuscript Accepted: October 7, 2020
- Published: October 28, 2020

Not Accessible

Your account may give you access

Abstract

5G radio access network (RAN) slicing has recently been proposed to adapt service provision over substrate network resources to the diversified requirements of 5G services in terms of bandwidth, computation, latency, and reliability. 5G RAN slicing allows baseband processing functions, including centralized units and distributed units, to be deployed in the substrate network according to the different service requirements. Even though existing studies have shown how to perform 5G RAN slicing to flexibly provision service according to their initial requirements, a proper dynamic RAN slice adjustment and migration strategy is also required to accommodate the highly dynamic nature of mobile traffic while maintaining lower service blocking. In this paper, we provide a traffic-prediction-based strategy for dynamic 5G RAN slice adjustment and migration in wavelength division multiplexing (WDM) metro-aggregation networks, which targets the minimization of (1) the slice degradation penalty, which accounts for both the degradation degree and slice priority, and (2) the migrated traffic during slice migration. Our numerical results show that the proposed strategy can effectively reduce the penalty and slice migration.

Full Article | PDF Article

More Like This

Enabling technologies for low-latency service migration in 5G transport networks [Invited]

Jun Li, Lei Chen, and Jiajia Chen
J. Opt. Commun. Netw. 13(2) A200-A210 (2021)

Latency-Aware CU Placement/Handover in Dynamic WDM Access-Aggregation Networks

Francesco Musumeci, Omran Ayoub, Monica Magoni, and Massimo Tornatore
J. Opt. Commun. Netw. 11(4) B71-B82 (2019)

End-to-end URLLC slicing based on packet duplication in 5G optical transport networks

Yajie Li, Jun Li, Yongli Zhao, and Jie Zhang
J. Opt. Commun. Netw. 12(7) 192-199 (2020)

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Figures (8)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Tables (3)

You do not have subscription access to this journal. Article tables are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Equations (6)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Parameters	Description
$\bar{G}$	Substrate network graph
$\bar{V}$	Set of substrate nodes (metro node)
$\bar{E}$	Set of substrate links (bidirectional optical fiber)
$\bar{C}$	Available capacity of substrate nodes $\bar{V}$
$\bar{B}$	Available bandwidth of substrate links $\bar{E}$
$N$	Number of substrate nodes in $\bar{V}$
$F$	Number of substrate links in $\bar{E}$
$W$	Number of wavelengths in fiber link
$\bar{v_{n}}$	$n$ th substrate node in $\bar{V}$
$\bar{e_{f}}$	$f$ th substrate link in $\bar{E}$
$\bar{l_{w, f}}$	$w$ th wavelengths in $\bar{e_{f}}$
$\bar{c_{n}}$	Available capacity of $\bar{v_{n}}$
$\bar{b_{w, f}}$	Available bandwidth of $\bar{l_{w}}$ in link $\bar{e_{f}}$
$R$	Set of slice requests
$K$	Total number of slice requests
$R_{k}$	$k$ th slice request in $R$
$V^{k}$	Set of virtual nodes of slice requests $k$
$E^{k}$	Set of virtual links of slice requests $k$
$C_{t}^{k}$	Computation resource requirement of virtual nodes in $V^{k}$ at time $t$
$B_{t}^{k}$	Bandwidth resource requirement of virtual links in $E^{k}$ at time $t$
$v_{k}^{m}$	$m$ th virtual nodes of slice request $k$
$e_{k}^{m}$	$i$ th virtual links of slice request $k$
$c_{k, t}^{m}$	Computational resource requirement of the $m$ th virtual nodes of slice request $k$ at time $t$
$b_{k, t}^{i}$	Bandwidth requirement of the $i$ th virtual link of slice request $k$ at time $t$
$x_{k}^{t}$	Traffic load of slice request $k$ at time $t$
$X (t, n)$	Traffic prediction of all slices with prediction steps $n$
$X_{k} (t, n)$	Traffic prediction of slice $k$ with prediction steps $n$
$\bar{x_{k}^{t}}$	Predicted traffic load of slice request $k$ at time $t$
$α_{k}^{v}$	Node penalty factor for slice request $k$
$α_{k}^{e}$	Link penalty factor for slice request $k$
$p_{k, t}^{m}$	Requested resources for the $m$ th virtual node of slice request $k$ at time $t$
$q_{k, t}^{i}$	Requested resources for the $i$ th virtual link of slice request $k$ at time $t$
$γ_{k}$	Discount factor for slice request $k$
Variables	Description
$δ_{k, t}^{n, m}$	$m$ th virtual node of slice request $k$ is mapped into $\bar{v_{n}}$ at time $t$
$η_{k, t}^{f, w, i}$	$i$ th virtual link of slice request $k$ is mapped into wavelength $\bar{l_{w, f}}$ of link $\bar{e_{f}}$ at time $t$
${\hat{p}}_{k, t}^{m}$	Actual allocated resources for the $m$ th virtual node of slice request $k$ at time $t$
${\hat{q}}_{k, t}^{i}$	Actual allocated resources for the $i$ th virtual link of slice request $k$ at time $t$

Parameter	Value
Carrier bandwidth	100 MHz
Modulation format	256 QAM
MIMO type	$8 \times 8$
Number of RBs	500
Number of CSs	51
Number of COs	25
Number of DCs	2
Number of wavelengths per core link	40
Number of wavelengths per extension link	10
Wavelength capacity	10 Gbit/s
Computation capacity per core CO	50,000 GOPS
Computation capacity per main CO	20,000 GOPS
Computation capacity per access CO	10,000 GOPS
RAN split option	Options 2 and 7 [22]
Number of candidate shortest paths	3
Area types	Residential/commercial
Priority	High/low

Parameters	Description
$\bar{G}$	Substrate network graph
$\bar{V}$	Set of substrate nodes (metro node)
$\bar{E}$	Set of substrate links (bidirectional optical fiber)
$\bar{C}$	Available capacity of substrate nodes $\bar{V}$
$\bar{B}$	Available bandwidth of substrate links $\bar{E}$
$N$	Number of substrate nodes in $\bar{V}$
$F$	Number of substrate links in $\bar{E}$
$W$	Number of wavelengths in fiber link
$\bar{v_{n}}$	$n$ th substrate node in $\bar{V}$
$\bar{e_{f}}$	$f$ th substrate link in $\bar{E}$
$\bar{l_{w, f}}$	$w$ th wavelengths in $\bar{e_{f}}$
$\bar{c_{n}}$	Available capacity of $\bar{v_{n}}$
$\bar{b_{w, f}}$	Available bandwidth of $\bar{l_{w}}$ in link $\bar{e_{f}}$
$R$	Set of slice requests
$K$	Total number of slice requests
$R_{k}$	$k$ th slice request in $R$
$V^{k}$	Set of virtual nodes of slice requests $k$
$E^{k}$	Set of virtual links of slice requests $k$
$C_{t}^{k}$	Computation resource requirement of virtual nodes in $V^{k}$ at time $t$
$B_{t}^{k}$	Bandwidth resource requirement of virtual links in $E^{k}$ at time $t$
$v_{k}^{m}$	$m$ th virtual nodes of slice request $k$
$e_{k}^{m}$	$i$ th virtual links of slice request $k$
$c_{k, t}^{m}$	Computational resource requirement of the $m$ th virtual nodes of slice request $k$ at time $t$
$b_{k, t}^{i}$	Bandwidth requirement of the $i$ th virtual link of slice request $k$ at time $t$
$x_{k}^{t}$	Traffic load of slice request $k$ at time $t$
$X (t, n)$	Traffic prediction of all slices with prediction steps $n$
$X_{k} (t, n)$	Traffic prediction of slice $k$ with prediction steps $n$
$\bar{x_{k}^{t}}$	Predicted traffic load of slice request $k$ at time $t$
$α_{k}^{v}$	Node penalty factor for slice request $k$
$α_{k}^{e}$	Link penalty factor for slice request $k$
$p_{k, t}^{m}$	Requested resources for the $m$ th virtual node of slice request $k$ at time $t$
$q_{k, t}^{i}$	Requested resources for the $i$ th virtual link of slice request $k$ at time $t$
$γ_{k}$	Discount factor for slice request $k$
Variables	Description
$δ_{k, t}^{n, m}$	$m$ th virtual node of slice request $k$ is mapped into $\bar{v_{n}}$ at time $t$
$η_{k, t}^{f, w, i}$	$i$ th virtual link of slice request $k$ is mapped into wavelength $\bar{l_{w, f}}$ of link $\bar{e_{f}}$ at time $t$
${\hat{p}}_{k, t}^{m}$	Actual allocated resources for the $m$ th virtual node of slice request $k$ at time $t$
${\hat{q}}_{k, t}^{i}$	Actual allocated resources for the $i$ th virtual link of slice request $k$ at time $t$

Parameter	Value
Carrier bandwidth	100 MHz
Modulation format	256 QAM
MIMO type	$8 \times 8$
Number of RBs	500
Number of CSs	51
Number of COs	25
Number of DCs	2
Number of wavelengths per core link	40
Number of wavelengths per extension link	10
Wavelength capacity	10 Gbit/s
Computation capacity per core CO	50,000 GOPS
Computation capacity per main CO	20,000 GOPS
Computation capacity per access CO	10,000 GOPS
RAN split option	Options 2 and 7 [22]
Number of candidate shortest paths	3
Area types	Residential/commercial
Priority	High/low

Abstract

References

Cited By

Figures (8)

Tables (3)

Equations (6)

Login or Create Account