5G Cross Aspect Functions

Acronyms

The following acronyms are used throughout these pages:

DC                   Data Center
IA                     Infrastructure Adaptor
NFVI                Network Function Virtualization Instantiator
MCE                Management and Control Entity
NIM                 Network Infrastructure Manager
PoP                 Point of Presence
REST              Representational State Transfer
SDN                Software Defined Networking
SFC                 Service Function Chaining
VIM                  Virtual Infrastructure Manager
VNF                 Virtual Network Function
WIM                 Wide Area Network Infrastructure Manager
VM                   Virtual Machine

 9. Optimization systems

This section describes optimization aspects that can be found in many parts of a 5G environment. The optimization subsystems of a 5G environment will be responsible for the performance and the optimization of it. Optimization is not embedded in a single place, but it cuts across multiple concerns. Such optimization can be seen for scaling and placement, for resource usage optimization, or within the energy consumption dimension of a system.

With the introduction of slicing in 5G, we can consider the optimization of slice creation and of slice scaling. We can also consider what is the best size of a service and the best place of individual slices to support that service.

The optimization subsystem of this 5G test-bed will be responsible for the performance optimization of it, such as energy consumption management for network slices, scaling and placement of network slices, resource usage optimization, and service assignment in network slices.

Consider in more detail the following:

• Energy management for network slices: DOLFIN project aims to significantly contribute towards improving the energy efficiency of data centers and stabilizing of smart grids. DOLFIN will model, monitor, and measure energy consumption and enable seamless, autonomic migration of VMs between servers of the same DC or across a group of Energy-conscious, Synergetic DCs. In this 5G-test bed, the energy models, energy monitoring methods form the basic models for monitoring the energy consumptions of network slices that across resources distributed in multiple data centers.
• The placement and scaling for network slices: The placement and scaling from SONATA can be leveraged to enable the scaling and placement of network slices in the 5G test-bed. To flexibly adapt to changing demands of the services within each network slice, the automatic mechanisms proposed in SONATA project will be adapted to scale slices by adding or removing logical/physical resources into the network slice. In particular, the resource allocation of network slices will be reallocated and the service assignment to slices will be adjusted.
• Resource usage optimization and service assignment in network slices: The orchestrator kernel and plugins of SONATA project provide a framework to support the placement and scaling optimization, conflict resolution, life-cycle management, etc. of services. It can be extended into a framework that optimizes service provisioning in network slices, and conflict resolution, life-cycle management of network slices.

References

27.  G. Clegg, R., Clayman, S., Pavlou, G., Mamatas, L., Galis, A.- "On the Selection of management and monitoring nodes in dynamic networks"— IEEE Transactions on Computers, Volume 62, Issue 6, June 2013, Digital Object Identifier no. 10.1109/TC.2012.67; IEEE computer Society Digital Library. IEEE Computer Society, http://doi.ieeecomputersociety.org/10.1109/TC.2012.67

28.  Z. Xu, W. Liang, A. Galis, and Y. Ma — "Throughput Maximization and Resource Optimization in NFV-Enabled Networks"- IEEE International Conference on Communications, 21-25 May 2017, Paris, France; http://icc2017.ieee-icc.org

29.  Zichuan Xu, Weifa Liang, Alex Galis, and Yu Ma. Throughput maximization and resource optimization in NFV-enabled networks. Proc of IEEE ICC’17, May, 2017.

30.  Zichuan Xu, Weifa Liang, Meitian Huang, Mike Jia, Song Guo, and Alex Galis. Approximation and online algorithms for NFV-enabled multicasting in SDNs. Proc of IEEE ICDCS’17, June 2017.

31.  D. Valocchi, D. Tuncer, M. Charalambides, M. Femminella, G. Reali and G. Pavlou, "Extensible signaling framework for decentralized network management applications," NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium, Istanbul, 2016, pp. 153-161.
doi: 10.1109/NOMS.2016.7502808

10. Programmability of systems

This section describes the programmability aspects that need to be added to various sub-systems. In order to make the 5G environments as flexible as possible, we need the sub-systems to be adaptable at run-time. To achieve this there needs to be a level of programmability built into the 5G environments. The programmability means that sub-systems are not pre-configured using static files, using pre-known data, rather it allows the data to be collected at run-time and the configuration to occur on-the-fly.  Consider at the infrastructure level how network end-points often have their addresses fixed before use, or at the service level database address configurations are in a file, and require a full restart if a new database node is added.  Programmability overcomes this static approach, ensuring these factors are all addressed at run-time.

Programmability has the following features:

• Dynamic configuration — whereby the configuration of sub-systems is not data from a fixed file but can happen at run-time and changes to the configuration can come under software control. The sub-system will adapt to the injected change.
• Run-time introspection — whereby a program can interact with a sub-system to find out its current state. Further options include finding out values for configuration variables, what functions it can support, and what API operations it supports.
• Naming and discovery — for programmability to work over the full 5G environment individual systems will need a unique name so that they can be addressed accurately. As there may be many instances of the same system deployed (in the order of 100s or even 1000s) unique naming ensures each one can be identified. Discovery is the mechanism by which a program can search and retrieve names for the relevant elements.
• APIs — it is the API in each sub-system that needs to be adapted and suitable for the programmability aspect of 5G.  Some sub-systems may use REST interfaces, while others may use a well-specified protocol.  Either of these are suitable, as long as they support enough functionality. However, without these APIs, overall programmability cannot be achieved.

References

32.  L. Mamatas, S. Clayman and A. Galis "Software-Defined Infrastructure" - IEEE Communications Magazine in April 2015 (Volume 53, Issue 4), pp 166-174, ISSN 0163-6804; DOI: 10.1109/MCOM.2015.7081091

33.  Clayman, S., Maini, E., Galis, A., Manzalini, A., Mazzocca, N. -"The Dynamic Placement of Virtual Network Functions" — IEEE/IFIP NOMS 2014 / SDNMO 2014 — 9th May 2014 Krakow; http://noms2014.ieee-noms.org; http://clayfour.ee.ucl.ac.uk/sdnmo2014/

34.  Galis, A., Rubio-Loyola, J., Clayman, S., Mamatas, L., Manzalini, A., Kukli_ski, S., Serrat, J., Zahariadis, T.  - "Softwarization of Future Networks and Services - Programmable Enabled Networks as Next Generation Software Defined Networks" - IEEE SDN4FNS (Software Defined Networks for Future Networks and Services), Trento, Italy 11-13 November 2013; http://sites.ieee.org/sdn4fns/

Authors 

Institute of Communications and Connected Systems
Roberts Building
University College London
WC1E 7JE

Institute of Communications and Connected Systems
Roberts Building
University College London
WC1E 7JE

Institute of Communications and Connected Systems
Roberts Building
University College London
WC1E 7JE