Provably efficient algorithms for joint placement and allocation of virtual network functions

Sang, Yu; Ji, Bo; Gupta, Gagan; Du, Xiaojiang; Lin, Yuping

doi:10.1109/infocom.2017.8057036

Cited by 122 publications

(54 citation statements)

References 17 publications

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“…Deploying Virtual Network Functions (VNF) in a specific order is called Service Function Chaining (SFC). Network bandwidth is fixed during the searching of SFC path, and flow routes are also fixed . Further, research is required on it to maintain the QoS.…”

Section: Discussionmentioning

confidence: 99%

A survey and classification of controller placement problem in SDN

Singh

Srivastava

2018

Int J Network Mgmt

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Summary Software defined networking emerges as a promising paradigm shift that decouples the control plane from the data plane. It has the ability to centrally monitor and control the network through softwarization, ie, controller. Deploying a single controller is inefficient to handle large network traffic; thereby, making multiple controllers are a necessity of current software defined networking in wide area networks. Placing multiple controllers in an optimum way, ie, controller placement is a vibrant research problem. Controller placement problem (CPP) is of twofold: the minimum number of controllers to be placed in a network and locations of these controllers. Numerous researchers in the last 5 years (2012 to November 2017) have proposed solutions for the CPP, which is an NP‐hard problem. In general, solutions are based on objective functions and their optimum solutions considering various factors (such as propagation latency between switches and controllers, and intercontrollers) and constraints (such as the capacity of controllers and switches). To the best of our knowledge, this is the first attempt of state‐of‐the‐art review on CPP. This paper classifies the CPP, critically analyzes the existing solutions, and finds limitations and future scope existing, which will help potential researchers in this area to innovate new solutions for CPP lying on this information.

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Section: Discussionmentioning

confidence: 99%

A survey and classification of controller placement problem in SDN

Singh

Srivastava

2018

Int J Network Mgmt

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“…In fact, our model of JPA-HS can also handle the capacity constraints in (2). Based on the NP-hardness of program (1) proved in Sang et al [14], we are able to state the following.…”

Section: Our Models and Definitionsmentioning

confidence: 98%

“…Many scenarios are proposed and considered for real-world requirements in JPA-VNF literature. For example in the work of Sang et al [14], they formulate a scenario of JPA-VNF as the following MILP problem:…”

Section: Related Workmentioning

confidence: 99%

Online Joint Placement and Allocation of Virtual Network Functions With Heterogeneous Servers

Chau

et al. 2020

IEEE Internet Things J.

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Network Function Virtualization (NFV) is a promising virtualization technology that has the potential to significantly reduce the expenses and improve the service agility. NFV makes it possible for Internet Service Providers (ISPs) to employ various Virtual Network Functions (VNFs) without installing new equipments. One of the most attractive approaches in NFV technology is a so-called Joint Placement and Allocation of Virtual Network Functions (JPA-VNF) which considers the balance between VNF investment with Quality of Services (QoS). We introduce a novel capability function to measure the potential of locating VNF instances for each server in the proposed OJPA-HS model. This model allows the servers in the network to be heterogeneous, at the same time combines and generalizes many classical JPA-VNF models. Despite its NP-hardness, we present a provable best-possible deterministic online algorithm based on dynamic programming (DP). To conquer the high complexity of DP, we propose two additional randomized heuristics, the Las Vegas (LV) and Monte Carlo (MC) randomized algorithms, which performs even as good as DP with much smaller complexity. Besides, MC is a promising heuristic in practice as it has the advantage to deal with big data environment. Extensive numerical experiments are constructed for the proposed algorithms in the paper.

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“…The placement problem has been considered in different domains such as NFV (e.g., [5]), SDN (e.g., [3]), and edge cloud computing (e.g., [12]). In NFV, several studies (e.g., [4], [13], [14]) consider the placement of a minimum number of VNF instances to cover all flows. A single type of network functions is considered in [4], [13], [15], [16], and the case of multiple network functions is considered in [14], [17], [18], [19], [20].…”

Section: Related Workmentioning

confidence: 99%

“…Most of the previous work either does not have a limited budget (e.g., [4]) or relaxes the resources constraint (e.g., [3]). In [5], both the budget and resources constraints are considered, along with fully processed flows requirement.…”

Section: Introductionmentioning

confidence: 99%

Placement and Allocation of Virtual Network Functions: Multi-dimensional Case

Sallam

Zheng

2019

2019 IEEE 27th International Conference on Network Protocols (ICNP)

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Network function virtualization (NFV) is an emerging design paradigm that replaces physical middlebox devices with software modules running on general purpose commodity servers. While gradually transitioning to NFV, Internet service providers face the problem of where to introduce NFV in order to make the most benefit of that; here, we measure the benefit by the amount of traffic that can be serviced through the NFV. This problem is non-trivial as it is composed of two challenging subproblems: 1) placement of nodes to support virtual network functions (referred to as VNF-nodes); and 2) allocation of the VNF-nodes resources to network flows; the two subproblems need to be considered jointly to satisfy the objective of serving the maximum amount of traffic. This problem has been studied recently but for the one-dimensional setting, where all network flows require one network function, which requires a unit of resource to process a unit of flow. In this work, we extend to the multi-dimensional setting, where flows can require multiple network functions, which can also require a different amount of each resource to process a unit of flow. The multi-dimensional setting introduces new challenges in addition to those of the onedimensional setting (e.g., NP-hardness and non-submodularity) and also makes the resource allocation a multi-dimensional generalization of the generalized assignment problem with assignment restrictions. To address these difficulties, we propose a novel two-level relaxation method and utilize the primal-dual technique to design two approximation algorithms that achieve an approximation ratio of (e−1)(Z−1) 2e 2 Z(kR) 1/(Z−1) and (e−1)(Z−1) 2e(Z−1+eZR 1/(Z−1) ) , where k (resp. R) is the number of VNF-nodes (resp. resources), and Z is a measure of the available resource compared to flow demand. Finally, we perform extensive trace-driven simulations to show the effectiveness of the proposed algorithms.

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Provably efficient algorithms for joint placement and allocation of virtual network functions

Cited by 122 publications

References 17 publications

A survey and classification of controller placement problem in SDN

A survey and classification of controller placement problem in SDN

Online Joint Placement and Allocation of Virtual Network Functions With Heterogeneous Servers

Placement and Allocation of Virtual Network Functions: Multi-dimensional Case

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