Cost analysis of initial deployment strategies for virtualized mobile core network functions

Yousaf, Faqir Zarrar; Loureiro, Paulo R. A.; Zdarsky, Frank A.; Taleb, Tarik; Liebsch, Marco

doi:10.1109/mcom.2015.7355586

Cited by 47 publications

(34 citation statements)

References 6 publications

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“…The example of such a complex VNF is illustrated in Fig. 1 [2]. The MANO complexity of a CMS further increases when it manages Network Services (NS), i.e., designed chains of relevant VNFs, e.g.…”

Section: A Cms Operational Modementioning

confidence: 99%

“…Each VNF profile group n ∈ N is characterized by a center of gravity c n = {c n, (1) , c n, (2) , · · · , c n,(z) }, where z ∈ Z is the spatial dimension (Z = |Z| = 3 in our example). The center of gravity of group n is obtained as the spatial point with the least Euclidean distance from all other VNF profile values p i associated to that group n. Mathematically, we can formulate the optimization problem as the following Problem VNF-Affinity:…”

Section: A Unsupervised Binding Affinitymentioning

confidence: 99%

See 1 more Smart Citation

z-TORCH: An Automated NFV Orchestration and Monitoring Solution

Sciancalepore¹,

Yousaf²,

Costa‐Pérez³

2018

IEEE Trans. Netw. Serv. Manage.

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Autonomous management and orchestration (MANO) of virtualized resources and services, especially in large-scale Network Function Virtualization (NFV) environments, is a big challenge owing to the stringent delay and performance requirements expected of a variety of network services. The Quality-of-Decisions (QoD) of a Management and Orchestration (MANO) system depends on the quality and timeliness of the information received from the underlying monitoring system. The data generated by monitoring systems is a significant contributor to the network and processing load of MANO systems, impacting thus their performance. This raises a unique challenge: how to jointly optimize the QoD of MANO systems while at the same minimizing their monitoring loads at runtime? This is the main focus of this paper.In this context, we propose a novel automated NFV orchestration solution, namely z-TORCH (zero Touch Orchestration) that jointly optimizes the orchestration and monitoring processes by exploiting machine-learning-based techniques. The objective is to enhance the QoD of MANO systems achieving a near-optimal placement of Virtualized Network Functions (VNFs) at minimum monitoring costs.

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Section: A Cms Operational Modementioning

confidence: 99%

Section: A Unsupervised Binding Affinitymentioning

confidence: 99%

z-TORCH: An Automated NFV Orchestration and Monitoring Solution

Sciancalepore¹,

Yousaf²,

Costa‐Pérez³

2018

IEEE Trans. Netw. Serv. Manage.

Self Cite

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“…This metric was used to dimension the VNF and, therefore, the number of each component type (Base Station, Mobility Management Entity, etc.) belonging to the EPC, by applying the dimensioning rules from 480 [20].…”

Section: Numerical Evaluationmentioning

confidence: 99%

“…CPU and, thus, the possibility of Service Level Agreement (SLA) violations. As VNFs are com- 20 posed of a set of VNF Components (VNFC) that need to exchange data over the network under capacity and latency constraints, the networking plays also an important part. Deploying each VNFC on a different server may result in lower SLA violation due to CPU contention but will increase the energy cost due to more active resources and additional traffic exchanged, 25 leading to higher router and link utilization, network contention and increased energy cost for the network.…”

Section: Introductionmentioning

confidence: 99%

On the energy cost of robustness for green virtual network function placement in 5G virtualized infrastructures

et al. 2017

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Next generation 5G networks will rely on virtualized Data Centers (vDC) to host virtualized network functions on commodity servers. Such Network Function Virtualization (NFV) will lead to significant savings in terms of infrastructure cost and reduced management complexity. However, green strategies for networking and computing inside data centers, such as server consolidation or energy aware routing, should not negatively impact the quality and service level agreements expected from network operators. In this paper, we study how robust strategies that place virtual network functions (VNF) inside vDC impact the energy savings and the protection level against resource demand uncertainty. We propose novel optimization models that allow the minimization of the energy of the computing and network infrastructure which is hosting a set of service chains that implement the VNFs. The model explicitly provides for robustness to unknown or imprecisely formulated resource demand variations, powers down unused routers, switch ports and servers, and calculates the energy optimal VNF placement and network embedding also considering latency constraints on the service chains. We propose both exact and heuristic methods. Our experiments were carried out using the virtualized Evolved Packet Core (vEPC), which * Corresponding author allows us to quantitatively assess the trade-off between energy cost, robustness and the protection level of the solutions against demand uncertainty. Our heuristic is able to converge to a good solution in a very short time, in comparison to the exact solver, which is not able to output better results in a longer run as demonstrated by our numerical evaluation. We also study the degree of robustness of a solution for a given protection level and the cost of additional energy needed because of the usage of more computing and network elements.

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“…Unfortunately, there is not much information available that may analyze the impact of deployment strategy during the initial deployment of VNI in a datacenter and how quickly the VNI converges to a functional operational status. In this regard, the work presented in [16] analyzes the impact on the cost of datacenter resources, such as network and compute, by comparing the impact of two constraint-based and heuristically derived deployment strategies namely Vertical Serial Deployment (VSD) and Horizontal Serial Deployment (HSD) strategies.…”

Section: Related Workmentioning

confidence: 99%

User mobility-aware Virtual Network Function placement for Virtual 5G Network Infrastructure

Taleb

Bagaa

Ksentini

2015

2015 IEEE International Conference on Communications (ICC)

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111

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Cloud offerings represent a promising solution for mobile network operators to cope with the surging mobile traffic. The concept of carrier cloud has therefore emerged as an important topic of inquiry. For a successful carrier cloud, algorithms for optimal placement of Virtual Network Functions (VNFs) on federated cloud are of crucial importance. In this paper, we introduce different VNF placement algorithms for carrier cloud with two main design goals: i) minimizing path between users and their respective data anchor gateways and ii) optimizing their sessions' mobility. The two design goals effectively represent two conflicting objectives, that we deal with considering the mobility features and service usage behavioral patterns of mobile users, in addition to the mobile operators' cost in terms of the total number of instantiated VNFs to build a Virtual Network Infrastructure (VNI). Different solutions are evaluated based on different metrics and encouraging results are obtained.IEEE ICC 2015 -Mobile and Wireless Networking Symposium 978-1-4673-6432-4/15/$31.00 ©2015 IEEE

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Cost analysis of initial deployment strategies for virtualized mobile core network functions

Cited by 47 publications

References 6 publications

z-TORCH: An Automated NFV Orchestration and Monitoring Solution

z-TORCH: An Automated NFV Orchestration and Monitoring Solution

On the energy cost of robustness for green virtual network function placement in 5G virtualized infrastructures

User mobility-aware Virtual Network Function placement for Virtual 5G Network Infrastructure

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