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A Summary and comparison of RAN slicing Approaches [327]. Table 11

Table 11 A Summary and comparison of RAN slicing Approaches [327]. Table 11

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A Summary of Related Survey Papers on Network Softwarization and 5G Network Slicing. * Proof of Concepts = PoC. v” indicates that the attributes are provided or applicable in the research work. x” indicates that the attributes are unspecified or non applicable in the research work *:
A Summary of Related Survey Papers on Network Softwarization and 5G Network Slicing. * Proof of Concepts = PoC. v” indicates that the attributes are provided or applicable in the research work. x” indicates that the attributes are unspecified or non applicable in the research work *:
Fig. 2. 5G service quality & business requirements [1,3,5].
Fig. 2. 5G service quality & business requirements [1,3,5].
5G Network Slicing using SDN and NFV: A Survey of Taxonomy - Architectures and Future Challenges
5G Network Slicing using SDN and NFV: A Survey of Taxonomy - Architectures and Future Challenges
Table 2 Internet. While today’s mobility management protocols are highly centralized and hierarchical [34], 5G network has to cope signifi- cantly with such extreme situations by providing mobility on de- mand based on each device and service’s requirements. However, for the full mobility support, enhancements to the current mobil- ity management procedures are needed. For example the handover procedures and a topology-aware gateway selection and relocation algorithm [35]. The new introduced distributed mobility manage- ment (DMM) [34,36] proposals for 5G seems to be a solution to overcome the current mobility management limitations. support high-definition streaming from cloud-based technologies and enhanced VR devices such as Google Glass and other wear- able computing devices. It will also provide faster web downloads and enable premium user experience when delivering services, for example, YouTube videos with high-resolution regardless of access method.
Table 2 Internet. While today’s mobility management protocols are highly centralized and hierarchical [34], 5G network has to cope signifi- cantly with such extreme situations by providing mobility on de- mand based on each device and service’s requirements. However, for the full mobility support, enhancements to the current mobil- ity management procedures are needed. For example the handover procedures and a topology-aware gateway selection and relocation algorithm [35]. The new introduced distributed mobility manage- ment (DMM) [34,36] proposals for 5G seems to be a solution to overcome the current mobility management limitations. support high-definition streaming from cloud-based technologies and enhanced VR devices such as Google Glass and other wear- able computing devices. It will also provide faster web downloads and enable premium user experience when delivering services, for example, YouTube videos with high-resolution regardless of access method.
Fig. 3. Summary and tutorial contributions of Section 3.
Fig. 3. Summary and tutorial contributions of Section 3.
A summary of 5G network slicing business roles and emerging markets . Table 3
A summary of 5G network slicing business roles and emerging markets . Table 3
Fig. 4. Software network technologies in 5G architecture. A indicates RAN; B = transport networks; C = core networks and D represents the Internet.
Fig. 4. Software network technologies in 5G architecture. A indicates RAN; B = transport networks; C = core networks and D represents the Internet.
Fig. 5. The NGMN network slicing concept.
Fig. 5. The NGMN network slicing concept.
Fig. 6. Network slicing use case [82].
Fig. 6. Network slicing use case [82].
Fig. 8. A comparison of SDN and network operation today.
Fig. 8. A comparison of SDN and network operation today.
Fig. 7. A summary and a tutorial contribution of Section 4. A summary of 5G Network Slicing Use Cases and Application Scenarios . Table 4
Fig. 7. A summary and a tutorial contribution of Section 4. A summary of 5G Network Slicing Use Cases and Application Scenarios . Table 4
Fig. 9. ONF SDN network slicing architecture [86]. A summary of SDN controllers for network orchestration and dynamic network slicing.
Fig. 9. ONF SDN network slicing architecture [86]. A summary of SDN controllers for network orchestration and dynamic network slicing.
Fig. 11. The role of MEC for 5G network slicing.
Fig. 11. The role of MEC for 5G network slicing.
Fig. 10. An integration of SDN controllers into the ETSI NFV reference architecture at the two levels required to achieve network slicing.
Fig. 10. An integration of SDN controllers into the ETSI NFV reference architecture at the two levels required to achieve network slicing.
Fig. 12. Cloud computing service models and their mapping to part of the NFV reference architecture [84].
Fig. 12. Cloud computing service models and their mapping to part of the NFV reference architecture [84].
The relationship and comparison between SDN and NFV. Table 6
The relationship and comparison between SDN and NFV. Table 6
Fig. 13. Summary of 5G network slicing projects, architectures and implementa- tions in Section 5.
Fig. 13. Summary of 5G network slicing projects, architectures and implementa- tions in Section 5.
Fig. 15. The main innovations of 5G NORMA concept.
Fig. 15. The main innovations of 5G NORMA concept.
Fig. 14. 5GEx network slicing conceptual architecture.
Fig. 14. 5GEx network slicing conceptual architecture.
Fig. 16. 5G NORMA architecture building blocks and their interactions.
Fig. 16. 5G NORMA architecture building blocks and their interactions.
Fig. 17. The life-cycle of a network slice in 5G NORMA architecture.
Fig. 17. The life-cycle of a network slice in 5G NORMA architecture.
A summary of academia/industry 5G projects and implementation based on SDN/NFV.
A summary of academia/industry 5G projects and implementation based on SDN/NFV.
or [197], only a PoC for 5G radio access is given using Non-Orthogonal Multiple Access (NOMA) experiments. Note that, neither SDN nor NFV is considered in thei mplementation. A qualitative comparison of orchestrators and deployment options [201] .
or [197], only a PoC for 5G radio access is given using Non-Orthogonal Multiple Access (NOMA) experiments. Note that, neither SDN nor NFV is considered in thei mplementation. A qualitative comparison of orchestrators and deployment options [201] .
Summary of Orchestration Enabling technologies in 5G Networks [201] . NETCONF is the Network Configuration Protocol [216] that provides mechanisms to install, manage, and delete the configurations of network devices. YANG [217,218] is a data modeling language for configuration data, state data, emote procedure calls, and notifications for network management protocols, e.g., NETCONF and RESTCONF [219]. TOSCA [220] is a language that describes the relationships and dependencies between services and applications hat reside on a cloud computing platform.
Summary of Orchestration Enabling technologies in 5G Networks [201] . NETCONF is the Network Configuration Protocol [216] that provides mechanisms to install, manage, and delete the configurations of network devices. YANG [217,218] is a data modeling language for configuration data, state data, emote procedure calls, and notifications for network management protocols, e.g., NETCONF and RESTCONF [219]. TOSCA [220] is a language that describes the relationships and dependencies between services and applications hat reside on a cloud computing platform.
Fig. 18. Illustration of 5G!Pagoda network slice orchestration and management ar- chitecture.
Fig. 18. Illustration of 5G!Pagoda network slice orchestration and management ar- chitecture.
Fig. 19. The NECOS slice provider and data center / network provider role.
Fig. 19. The NECOS slice provider and data center / network provider role.
Fig. 20. Three network slices with different critical key performance indicators. The Massive IoT slice may include VNFs like vEPC, vFW, and vGW. Packet loss is the KPI to meet SLA requirements for this slice. The industry slice may include VNFs such as vRouter and vVPN. Latency is the KPI for this slice to meet SLA requirements [210].
Fig. 20. Three network slices with different critical key performance indicators. The Massive IoT slice may include VNFs like vEPC, vFW, and vGW. Packet loss is the KPI to meet SLA requirements for this slice. The industry slice may include VNFs such as vRouter and vVPN. Latency is the KPI for this slice to meet SLA requirements [210].
Fig. 22. High level overview of an architecture of Slicing Packet Network (SPN) fot 5G transport. Fig. 21. Network slicing relevant industry groups and SDOs landscape.
Fig. 22. High level overview of an architecture of Slicing Packet Network (SPN) fot 5G transport. Fig. 21. Network slicing relevant industry groups and SDOs landscape.
Fig. 25. 5G!Pagoda slice template and instantiated slices. Fig. 24. High-level overview of management and orchestration in a single domain. The “Enhanced Telecom Operations Map (eTOM) is a reference framework that cat- egorizes the business processes that a service provider will use.
Fig. 25. 5G!Pagoda slice template and instantiated slices. Fig. 24. High-level overview of management and orchestration in a single domain. The “Enhanced Telecom Operations Map (eTOM) is a reference framework that cat- egorizes the business processes that a service provider will use.
Fig. 23. A summary of Section 6.
Fig. 23. A summary of Section 6.
Fig. 26. A multi-domain slicing architecture in 5G networks (adapted from [253]) Taleb et al. [253] also provide a discussion on multi-domain network slice orchestration and management procedures for multi- domain network slice configuration and multi-domain network slice modification. Three fundamental design challenges rele- vant to the realization of service management in 5G network slicing include: resource isolation and sharing, service manage- ment interfaces & service profiling and service-based manage- ment plane. For service management interface, the RESTfull mod- els like L3SM/L2SM [283,284] and NFVIFA Os-Ma-Nfvo’° are cur- rently being considered for facilitating the information exchange. These models are used for programmability purposes to provide control capabilities among different administrative and technol- ogy domains and third parties such as verticals. However, the problem with these models is the lack of resiliency and perfor- mance measurement capabilities, multi-domain connectivity and control considerations on federated resources. It is therefore ar- gued that new data models have to be developed that can ana- lyze and map service requirements of the corresponding slice into the relevant cloud and networking resources. Besides that, service profiling algorithms for optimizing the mapping of allocated re- sources are highly needed in future 5G network slicing environ- ments [253]. Authors in [285] propose an E2E slices architecture platform that exploits feedback information from mobile network slices to make orchestration decisions via a hierarchical control plane. Efficient management mechanisms are proposed that per-
Fig. 26. A multi-domain slicing architecture in 5G networks (adapted from [253]) Taleb et al. [253] also provide a discussion on multi-domain network slice orchestration and management procedures for multi- domain network slice configuration and multi-domain network slice modification. Three fundamental design challenges rele- vant to the realization of service management in 5G network slicing include: resource isolation and sharing, service manage- ment interfaces & service profiling and service-based manage- ment plane. For service management interface, the RESTfull mod- els like L3SM/L2SM [283,284] and NFVIFA Os-Ma-Nfvo’° are cur- rently being considered for facilitating the information exchange. These models are used for programmability purposes to provide control capabilities among different administrative and technol- ogy domains and third parties such as verticals. However, the problem with these models is the lack of resiliency and perfor- mance measurement capabilities, multi-domain connectivity and control considerations on federated resources. It is therefore ar- gued that new data models have to be developed that can ana- lyze and map service requirements of the corresponding slice into the relevant cloud and networking resources. Besides that, service profiling algorithms for optimizing the mapping of allocated re- sources are highly needed in future 5G network slicing environ- ments [253]. Authors in [285] propose an E2E slices architecture platform that exploits feedback information from mobile network slices to make orchestration decisions via a hierarchical control plane. Efficient management mechanisms are proposed that per-
Related topics:
Computer NetworksMultimedia CommunicationsQuality of Experience (QoE)QoE ManagementSoftware Defined Networks (SDN)Mobile Edge ComputingNFV Orchestration
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