An efficient virtualized network function deployment scheme for service function chain using deep Q‐network

2022 ◽  
Author(s):  
Wei‐Cheng Wu ◽  
Shang‐Juh Kao ◽  
Fu‐Min Chang
Keyword(s):  
Service Function ◽  
Network Function ◽  
Service Function Chain

scholarly journals Path Load Adaptive Migration for Routing and Bandwidth Allocation in Mobile-Aware Service Function Chain

Electronics ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 57
Author(s):  
Hefei Hu ◽  
Chen Yang ◽  
Lingyi Xu ◽  
Tangyijia Song ◽  
Bonaho Bocochi Dalia
Keyword(s):  
Failure Rate ◽  
Bandwidth Allocation ◽  
Arrival Time ◽  
Network Function Virtualization ◽  
Estimation Model ◽  
Migration Strategy ◽  
Service Function ◽  
Network Function ◽  
Service Function Chain

With network function virtualization (NFV) expanding from network center to edge, the service function chain (SFC) will gradually approach users to provide lower delay and higher-quality services. User mobility seriously affects the quality of service (QoS) provided by the mobile-aware SFC. Therefore, we must migrate the SFC to provide continuous services. In the user estimable movement scenario with a known mobile path and estimable arrival time, we establish the estimation model of user arrival time to obtain the estimated arrival time. Then, to reduce the time that the user is waiting for the migration completion, we propose a softer migration strategy migrating mobile-aware SFC before the user arrives at the corresponding access node. Moreover, for the problem of routing and bandwidth allocation (RBA), to reduce the migration failure rate, the paper proposes a path load adaptive routing and bandwidth allocation (PLARBA) algorithm adjusting the migration bandwidth according to the path load. The experimental results show that the proposed algorithm has significant advantages in reducing the user’s waiting time by more than 90%, decreasing migration failure rate by up to 75%, and improving QoS compared to the soft migration strategy and two RBA algorithms.

scholarly journals An Availability-Enhanced Service Function Chain Placement Scheme in Network Function Virtualization

2019 ◽  
Vol 8 (2) ◽  
pp. 34
Author(s):  
Yansen Xu ◽  
Ved P. Kafle
Keyword(s):  
Single Point ◽  
Computation Time ◽  
Network Services ◽  
Network Function Virtualization ◽  
Placement Problem ◽  
Service Function ◽  
Network Function ◽  
Multiple Substrate ◽  
Service Function Chain ◽  
End To End

A service function chain (SFC) is an ordered virtual network function (VNF) chain for processing traffic flows to deliver end-to-end network services in a virtual networking environment. A challenging problem for an SFC in this context is to determine where to deploy VNFs and how to route traffic between VNFs of an SFC on a substrate network. In this paper, we formulate an SFC placement problem as an integer linear programing (ILP) model, and propose an availability-enhanced VNF placing scheme based on the layered graphs approach. To improve the availability of SFC deployment, our scheme distributes VNFs of an SFC to multiple substrate nodes to avoid a single point of failure. We conduct numerical analysis and computer simulation to validate the feasibility of our SFC scheme. The results show that the proposed scheme outperforms well in different network scenarios in terms of end-to-end delay of the SFC and computation time cost.

scholarly journals Energy Efficient Deployment of a Service Function Chain for Sustainable Cloud Applications

2018 ◽  
Vol 10 (10) ◽  
pp. 3499 ◽  
Author(s):  
Jian Sun ◽  
Yue Chen ◽  
Miao Dai ◽  
Wanting Zhang ◽  
Arun Sangaiah ◽  
...  
Keyword(s):  
Power Consumption ◽  
Greedy Algorithms ◽  
Load Ratio ◽  
Research Problem ◽  
Network Function Virtualization ◽  
Service Function ◽  
Acceptance Ratio ◽  
Network Function ◽  
Service Function Chain ◽  
Cloud Applications

With the increasing popularity of the Internet, user requests for cloud applications have dramatically increased. The traditional model of relying on dedicated hardware to implement cloud applications has not kept pace with the rapid growth in demand. Network function virtualization (NFV) architecture emerged at a historic moment. By moving the implementation of functions to software, a separation of functions and hardware was achieved. Therefore, when user demand increases, cloud application providers only need to update the software; the underlying hardware does not change, which can improve network scalability. Although NFV solves the problem of network expansion, deploying service function chains into the underlying network to optimize indicators remains an important research problem that requires consideration of delay, reliability, and power consumption. In this paper, we consider the optimization of power consumption with the premise of guaranteeing a certain virtual function link yield. We propose an efficient algorithm that is based on first-fit and greedy algorithms to solve the problem. The simulation results show that the proposed algorithm substantially improves the path-finding efficiency, achieves a higher request acceptance ratio and reduces power consumption while provisioning the cloud applications. Compared with the baseline algorithm, the service function chain (SFC) acceptance ratio of our proposed algorithms improves by a maximum of approximately 15%, our proposed algorithm reduces the power consumption by a maximum of approximately 15%, the average link load ratio of our proposed algorithm reduces by a maximum of approximately 20%, and the average mapped path length of our proposed algorithm reduces by a maximum of approximately 1.5 hops.

scholarly journals Server Resource Dimensioning and Routing of Service Function Chain in NFV Network Architectures

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
V. Eramo ◽  
A. Tosti ◽  
E. Miucci
Keyword(s):  
Power Consumption ◽  
Virtual Machines ◽  
Blocking Probability ◽  
Network Function Virtualization ◽  
Traffic Demand ◽  
Service Function ◽  
Network Function ◽  
Service Function Chain ◽  
Commercial Off The Shelf ◽  
Resource Dimensioning

The Network Function Virtualization (NFV) technology aims at virtualizing the network service with the execution of the single service components in Virtual Machines activated on Commercial-off-the-shelf (COTS) servers. Any service is represented by the Service Function Chain (SFC) that is a set of VNFs to be executed according to a given order. The running of VNFs needs the instantiation of VNF instances (VNFI) that in general are software components executed on Virtual Machines. In this paper we cope with the routing and resource dimensioning problem in NFV architectures. We formulate the optimization problem and due to its NP-hard complexity, heuristics are proposed for both cases of offline and online traffic demand. We show how the heuristics works correctly by guaranteeing a uniform occupancy of the server processing capacity and the network link bandwidth. A consolidation algorithm for the power consumption minimization is also proposed. The application of the consolidation algorithm allows for a high power consumption saving that however is to be paid with an increase in SFC blocking probability.

scholarly journals Multiple instances mapping of Service Function Chain with parallel Virtual Network Functions

2019 ◽  
Vol 13 ◽  
pp. 174830261986853 ◽  
Author(s):  
Dong Zhang ◽  
Xiang Lin ◽  
Xiang Chen
Keyword(s):  
Queuing Theory ◽  
Virtual Network ◽  
Network Function Virtualization ◽  
Service Function ◽  
Network Function ◽  
Integer Programing ◽  
Service Function Chain ◽  
Network Functions ◽  
Simulation Results ◽  
Mapping Scheme

Network Function Virtualization addresses the defect of traditional middleboxes and enables operators to implement new services through a process named Service Function Chain mapping. Service Function Chain is composed by a sequence of Virtual Network Functions (VNFs) which is deployed in shared platforms. Service Function Chain with parallel VNFs is proposed to reduce the delivery latency. In this paper, a multiple instances mapping scheme named MIM is proposed to resolve the performance bottleneck introduced by the imbalance of parallel VNFs. A integer programing model is established to describe the multiple instances mapping problem based on queuing theory, and a double layer Genetic Algorithm is used to allocate parallel VNFs with multiple instances. Simulation results show that the multiple instances mapping scheme can improve the performance of Service Function Chain with parallel VNFs effectively.

scholarly journals A Cross-Domain Service Function Chain Deployment Scheme Based on Bargaining Game

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Guoyan Li ◽  
Yajuan Ren ◽  
Yi Liu
Keyword(s):  
Bargaining Game ◽  
Network Function Virtualization ◽  
Service Chain ◽  
Service Function ◽  
Network Function ◽  
Cross Domain ◽  
Optimal Node ◽  
Consumption Cost ◽  
Service Function Chain ◽  
Multiple Domains

Software-defined networking (SDN) and network function virtualization (NFV) technologies provide support for service function chain (SFC) deployment. As the scale of a network expands, SDN domains are maintained and managed by their respective network operators. When deploying an SFC in multiple domains, to protect the privacy of each domain is challenging. We propose a cross-domain SFC deployment scheme based on a bargaining game. We establish an effective cross-domain service chain system model and combine resource consumption cost and load balance to translate SFC deployment to an optimization problem. A bargaining game model is established so as to reasonably optimize these contradictory parameters. We solve the model by an improved imperialist competition algorithm and obtain the optimal node mapping relationship. Experimental results show that our method performs better than the current one in terms of network load balancing and mapping overhead and has better scalability.

scholarly journals Reliable Service Function Chain Deployment Method Based on Deep Reinforcement Learning

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2733
Author(s):  
Hua Qu ◽  
Ke Wang ◽  
Jihong Zhao
Keyword(s):  
Reinforcement Learning ◽  
Load Balancing ◽  
Network Function Virtualization ◽  
Node Degree ◽  
Average Delay ◽  
Service Function ◽  
Network Function ◽  
Resource Requirements ◽  
Current Resource ◽  
Service Function Chain

Network function virtualization (NFV) is a key technology to decouple hardware device and software function. Several virtual network functions (VNFs) combine into a function sequence in a certain order, that is defined as service function chain (SFC). A significant challenge is guaranteeing reliability. First, deployment server is selected to place VNF, then, backup server is determined to place the VNF as a backup which is running when deployment server is failed. Moreover, how to determine the accurate locations dynamically with machine learning is challenging. This paper focuses on resource requirements of SFC to measure its priority meanwhile calculates node priority by current resource capacity and node degree, then, a novel priority-awareness deep reinforcement learning (PA-DRL) algorithm is proposed to implement reliable SFC dynamically. PA-DRL determines the backup scheme of each VNF, then, the model jointly utilizes delay, load balancing of network as feedback factors to optimize the quality of service. In the experimental results, resource efficient utilization, survival rate, and load balancing of PA-DRL were improved by 36.7%, 35.1%, and 78.9% on average compared with benchmark algorithm respectively, average delay was reduced by 14.9%. Therefore, PA-DRL can effectively improve reliability and optimization targets compared with other benchmark methods.

scholarly journals Service Function Chain Placement in Distributed Scenarios: a Systematic Review

2021 ◽  
Author(s):  
Guto Leoni Santos ◽  
Diego de Freitas Bezerra ◽  
Élisson da Silva Rocha ◽  
Leylane Ferreira ◽  
André Moreira ◽  
...  
Keyword(s):  
Systematic Review ◽  
Network Performance ◽  
Network Function Virtualization ◽  
Service Function ◽  
Network Function ◽  
Network Flexibility ◽  
Specific Order ◽  
Service Function Chain ◽  
Network Functions ◽  
Traffic Oscillations

Abstract The network function virtualization (NFV) paradigm is an emerging technology that provides network flexibility by allowing the allocation of network functions over commodity hardware, like legacy servers in an IT infrastructure. In comparison with traditional network functions, implemented by dedicated hardware, the use of NFV reduces the operating and capital expenses and improves service deployment. In some scenarios, a complete network service can be composed of several functions, following a specific order, known as a service function chain (SFC). SFC placement is a complex task, already proved to be NP-hard. Moreover, in highly distributed scenarios, the network performance can also be impacted by other factors, such as traffic oscillations and high delays. Therefore, a given SFC placement strategy must be carefully developed to meet the network operator service constraints. In this paper, we present a systematic review of SFC placement advances in distributed scenarios. Differently from the current literature, we examine works over the last 10 years which addressed this problem while focusing on distributed scenarios. We then discuss the main scenarios where SFC placement has been deployed, as well as the several techniques used to create the placement strategies. We also present the main goals considered to create SFC placement strategies and highlight the metrics used to evaluate them.

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