Optimisation Models for Robust and Survivable Network Slice Design: A Comparative Analysis

Baumgartner, Andreas; Bauschert, Thomas; Koster, Arie M. C. A.; Reddy, Varun S.

doi:10.1109/glocom.2017.8254073

Cited by 30 publications

(21 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Since NS allows operators to customize networks according to various service demands, both industry and academia introduce many realization models of NS. Baumgartner et al [14] illustrate the slice as an E2E traffic flow set, outline a model for Network Slice Design Problem (NSDP), and present two model extensions for traffic robustness and survivability requirements. However, the problem statement for NS has to encompass the characterization of the NS itself (i.e., including required VNUs and their interconnections).…”

Section: Network Slicing and Resource Allocationmentioning

confidence: 99%

“…For instance, as shown in Figure 1, NSI4 for auto driving consists of three communication service instances and communication service instances consist of different VNUs and virtual links. VNUs can be implemented as a set of VNFs running on general x86 hardware in DCs, while each logical slice corresponds to an abstraction of a subset of physical substrate network resources tailored to meet the specific customer QoS/resilience requirements [14]. The slice controller achieves the resource allocation by mapping NS requests into substrate network resources (e.g., BBUs, GWs, and AMFs) to implement specific network functions.…”

Section: Vnf Resources Allocation Processmentioning

confidence: 99%

“…and formulate the corresponding problem with ignoring the integer constraint (14). That is, the relaxation problem of the original ILP (RILP), as follows:…”

Section: Algorithm Frameworkmentioning

confidence: 99%

“…Numerical results verify that our proposed model can find out the latency-optimal VNUs and virtual links mapping. With comparison to Robust Network Slice Design Problem (NSDP) [14] and Random Fit Placement Algorithm (RFPA) [15], our scheme can optimize the transport network latency and improve load-balance and serviceability. The contributions of this work can be concluded as follows:…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Latency-Optimal Virtual Network Functions Resource Allocation for 5G Backhaul Transport Network Slicing

Feng

et al. 2019

Applied Sciences

View full text Add to dashboard Cite

The concept of network slicing (NS) has been proposed for flexible resource provisioning where a physical resource is partitioned into logically independent networks on demand. The NS resource allocation implies the definition of a feasible path in the infrastructure network with adequate resource availability. However, due to complex structural characteristics of the backhaul transport network, a number of issues arise when fast deploying the end-to-end (E2E) slices onto network infrastructures. In this paper, a pair-decision resource allocation model is firstly formulated to construct the mapping relationship between logical networks and substrate networks in a coordinated way. In order to improve extreme quality of service (QoS) and user experiment, latency-optimal virtual resource allocation problem is defined, subject to the backhaul capacity and bandwidth constraints. The problem is formulated as an integer linear programming (ILP) and solved with the branch-and-bound scheme, whose resolution yields an optimal virtual network function (VNF) placement and traffic routing policy. Numerical results reveal that the proposed scheme can enable the transport network latency optimization with a reduction of up to 30% and 41.6% compared to the Network Slice Design Problem (NSDP) and Random Fit Placement Algorithm (RFPA) schemes respectively. In the meanwhile, the network load balance and serviceability have been improved efficiently with better resource utilization as well.

show abstract

Section: Network Slicing and Resource Allocationmentioning

confidence: 99%

Section: Vnf Resources Allocation Processmentioning

confidence: 99%

“…and formulate the corresponding problem with ignoring the integer constraint (14). That is, the relaxation problem of the original ILP (RILP), as follows:…”

Section: Algorithm Frameworkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Latency-Optimal Virtual Network Functions Resource Allocation for 5G Backhaul Transport Network Slicing

Feng

et al. 2019

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…Other previous work points out the need of schemes dealing with user demand uncertainties. In [10], a network slice allocation problem is solved by robust optimization, distributing resource shares so as to minimize the extra costs due to demand uncertainties. A fair resource allocation is considered in [11], where a distributed algorithm allocates resources to users of each slice, based on traffic demands on different locations.…”

Section: Introductionmentioning

confidence: 99%

Enabling Dynamic Resource Sharing for Slice Customization in 5G Networks

Lieto

Malanchini

Capone

2018

2018 IEEE Global Communications Conference (GLOBECOM)

View full text Add to dashboard Cite

Network slicing is one of the main novelty of 5G systems and it is expected to radically change the approach of network operators to the support of vertical applications with specific and stringent performance requirements that can be managed by tenants. Static allocation of resources to slices is a straightforward approach to meet Service Level Agreements (SLAs), but it may lead to dramatic inefficiencies and high costs. On the other side, dynamic sharing can greatly improve resource utilization, but it requires a strict control of performance parameters so as to guarantee small congestion probability and smoothed degradation when it occurs. In this paper, we propose a utilitybased approach that can properly map the slice customization strategies that tenants can use to address the different traffic requirements and their specific service management policies. We define resource scheduling mechanisms that allow differentiation among slices and service prioritization through slice-specific parameters. We model resource allocation as a mathematical programming problem and present numerical results that show the viability of the proposed approach.

show abstract

Integration of D2D, Network Slicing, and MEC in 5G Cellular Networks: Survey and Challenges

et al. 2021

View full text Add to dashboard Cite

With the tremendous demand for connectivity anywhere and anytime, existing network architectures should be modified. To cope with the challenges that arise due to the increasing flood of devices/users and a diverse range of application requirements, new technologies and concepts must be integrated to enable their benefits. Service providers and business companies are looking for new areas of research to enhance overall system performance. This paper gives a detailed survey about the recent 5G technologies, the solutions they provide, and the effect caused by their addition to current cellular networks. It is based on the three most important 5G concepts: Device to Device (D2D), Network Slicing (NS), and Mobile Edge Computing (MEC). This study proposes to design the future 5G networks by the integration of all three technologies. It is believed that spectrum efficiency, energy efficiency, and overall throughput will be greatly improved by using D2D. The system delay and computational load will be reduced as tasks will be handled by edge routers located at the base stations. Thus offloading the core network and the system capital expenses and operational expenses will be reduced significantly by slicing the network.

show abstract

Optimisation Models for Robust and Survivable Network Slice Design: A Comparative Analysis

Cited by 30 publications

References 16 publications

Latency-Optimal Virtual Network Functions Resource Allocation for 5G Backhaul Transport Network Slicing

Latency-Optimal Virtual Network Functions Resource Allocation for 5G Backhaul Transport Network Slicing

Enabling Dynamic Resource Sharing for Slice Customization in 5G Networks

Integration of D2D, Network Slicing, and MEC in 5G Cellular Networks: Survey and Challenges

Contact Info

Product

Resources

About