TY - JOUR
T1 - Dimensioning network slices for power minimization under reliability constraints
AU - Huang, Wei
AU - Araldo, Andrea
AU - Castel-Taleb, Hind
AU - Jouaber, Badii
N1 - Publisher Copyright:
© 2025 Elsevier B.V.
PY - 2025/9/1
Y1 - 2025/9/1
N2 - Network slicing allows multiplexing virtualized networks, called slices, over a single physical network infrastructure. Research has extensively focused on the placement of virtual functions and the links that compose each network slice. On the other hand, performance greatly depends on how many resources are allocated to virtual nodes and links, after they are placed. This aspect has been mostly neglected. In this paper, we propose a method to dimension computation and network resources to slices, with the aim to minimize dynamic power consumption. Latency and power are the result of non-trivial couplings between different components of each slice. Therefore, minimizing power while satisfying the reliability constraints of all slices is challenging. To capture these couplings, we model slices as multiple Jackson networks (one per slice) co-existing in the same resource-constrained physical network. To the best of our knowledge, we are the first to employ Jackson Networks in such a setting. Dynamic power savings are in large part obtained by finely deciding CPU clock frequency, exploiting Dynamic Voltage Frequency Scaling (DVFS). Via numerical evaluation, we show that our method finds per each slice just the right amount of resources to satisfy latency constraints (expressed in probabilistic terms, as chance-constraints). This brings relevant dynamic power reduction with respect to baselines representing the state of the art in network slicing, which focuses on placement without specific strategies for resources dimensioning.
AB - Network slicing allows multiplexing virtualized networks, called slices, over a single physical network infrastructure. Research has extensively focused on the placement of virtual functions and the links that compose each network slice. On the other hand, performance greatly depends on how many resources are allocated to virtual nodes and links, after they are placed. This aspect has been mostly neglected. In this paper, we propose a method to dimension computation and network resources to slices, with the aim to minimize dynamic power consumption. Latency and power are the result of non-trivial couplings between different components of each slice. Therefore, minimizing power while satisfying the reliability constraints of all slices is challenging. To capture these couplings, we model slices as multiple Jackson networks (one per slice) co-existing in the same resource-constrained physical network. To the best of our knowledge, we are the first to employ Jackson Networks in such a setting. Dynamic power savings are in large part obtained by finely deciding CPU clock frequency, exploiting Dynamic Voltage Frequency Scaling (DVFS). Via numerical evaluation, we show that our method finds per each slice just the right amount of resources to satisfy latency constraints (expressed in probabilistic terms, as chance-constraints). This brings relevant dynamic power reduction with respect to baselines representing the state of the art in network slicing, which focuses on placement without specific strategies for resources dimensioning.
KW - Hypo-exponential distribution
KW - Jackson networks
KW - Network slicing
KW - Optimization
KW - Resource allocation
UR - https://www.scopus.com/pages/publications/105001130501
U2 - 10.1016/j.future.2025.107824
DO - 10.1016/j.future.2025.107824
M3 - Article
AN - SCOPUS:105001130501
SN - 0167-739X
VL - 170
JO - Future Generation Computer Systems
JF - Future Generation Computer Systems
M1 - 107824
ER -