scholarly journals Multi-Source Reliable Multicast Routing with QoS Constraints of NFV in Edge Computing

Electronics ◽  
2019 ◽  
Vol 8 (10) ◽  
pp. 1106 ◽  
Author(s):  
Shiming He He ◽  
Kun Xie ◽  
Xuhui Zhou ◽  
Thabo Semong ◽  
Jin Wang
Keyword(s):  
Heuristic Algorithms ◽  
Multicast Routing ◽  
Multicast Tree ◽  
Edge Computing ◽  
Network Function Virtualization ◽  
Reliable Multicast ◽  
Network Function ◽  
Tree Construction ◽  
Service Function Chain ◽  
The Cost

Edge Computing (EC) allows processing to take place near the user, hence ensuring scalability and low latency. Network Function Virtualization (NFV) provides the significant convenience of network layout and reduces the service operation cost in EC and data center. Nowadays, the interests of the NFV layout focus on one-to-one communication, which is costly when applied to multicast or group services directly. Furthermore, many artificial intelligence applications and services of cloud and EC are generally communicated through groups and have special Quality of Service (QoS) and reliable requirements. Therefore, we are devoted to the problem of reliable Virtual Network Function (VNF) layout with various deployment costs in multi-source multicast. To guarantee QoS, we take into account the bandwidth, latency, and reliability constraints. Additionally, a heuristic algorithm, named Multi-Source Reliable Multicast Tree Construction (RMTC), is proposed. The algorithm aims to find a common link to place the Service Function Chain (SFC) in the multilevel overlay directed (MOD) network of the original network, so that the deployed SFC can be shared by all users, thereby improving the resource utilization. We then constructed a Steiner tree to find the reliable multicast tree. Two real topologies are used to evaluate the performance of the proposed algorithm. Simulation results indicate that, compared to other heuristic algorithms, our scheme effectively reduces the cost of reliable services and satisfies the QoS requirements.

scholarly journals QoS-Based Multicast Routing in Network Function Virtualization-Enabled Software-Defined Mobile Edge Computing Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Shimin Sun ◽  
Xinchao Zhang ◽  
Wentian Huang ◽  
Aixin Xu ◽  
Xiaofan Wang ◽  
...  
Keyword(s):  
Multicast Routing ◽  
Computational Cost ◽  
Mobile Network ◽  
Multicast Tree ◽  
Edge Computing ◽  
Network Function Virtualization ◽  
Mobile Edge Computing ◽  
Seamless Integration ◽  
Network Function ◽  
Pass Through

Mobile Edge Computing (MEC) technology brings the unprecedented computing capacity to the edge of mobile network. It provides the cloud and end user swift high-quality services with seamless integration of mobile network and Internet. With powerful capability, virtualized network functions can be allocated to MEC. In this paper, we study QoS guaranteed multicasting routing with Network Function Virtualization (NFV) in MEC. Specifically, data should pass through a service function chain before reaching destinations along a multicast tree with minimal computational cost and meeting QoS requirements. Furthermore, to overcome the problems of traditional IP multicast and software-defined multicasting approaches, we propose an implementable multicast mechanism that delivers data along multicast tree but uses unicast sessions. We finally evaluate the performance of the proposed mechanism based on experimental simulations. The results show that our mechanism outperforms others reported in the literature.

A FAST HYBRID ALGORITHM FOR MULTICAST ROUTING IN WIRELESS NETWORKS

2007 ◽  
Vol 16 (01) ◽  
pp. 45-68 ◽  
Author(s):  
S. AL-SHARHAN ◽  
W. GUEAIEB
Keyword(s):  
Wireless Networks ◽  
Hybrid Algorithm ◽  
Heuristic Algorithms ◽  
Multicast Routing ◽  
Learning Algorithm ◽  
Population Based ◽  
Multicast Tree ◽  
Recent Developments ◽  
Real Challenge

This paper tackles the issue of constrained multicast routing in wireless networks using a hybrid soft computing-based algorithm. Recent developments in multimedia applications and the dynamic and rapidly changed environment of the wireless networks make the constrained multicast routing a real challenge. The problem can be formulated as minimizing a multicast tree cost under several constraints or Quality of Service (QoS) metrics. This problem has been proven to be NP-complete. The proposed hybrid algorithm is based on a population based incremental learning algorithm that combines in an efficient way the features of genetic algorithms and competitive learning. Experimental results show that, in most cases, the proposed algorithm yields better solutions than other heuristic algorithms proposed in the literature.

A Multicast Routing Algorithm with Cost, Delay and Bandwidth Constraints

2013 ◽  
Vol 756-759 ◽  
pp. 1850-1854
Author(s):  
Yuan Chen Li ◽  
Guo Fang Kuang
Keyword(s):  
Communication Networks ◽  
Multicast Routing ◽  
Routing Algorithm ◽  
Multicast Tree ◽  
Routing Problem ◽  
Qos Parameters ◽  
The Cost ◽  
Multicast Routing Algorithm ◽  
Multiple Qos

Quality of service (QoS) generally assumes more than one QoS measure which implies that routing can be categorized as an instance of routing subject to multiple constraints: such as cost, delay, bandwidth, etc. The problem of constructing multicast trees is studied to meet the QoS requirements where it is necessary to provide bounded constraints among the source and all destinations while keeping the cost of the multicast tree low. So, a kind of source-destination QoS multicast routing problem is addressed about communication networks. The algorithm we presented takes bandwidth, delay and loss rate as premise, constructs routing selected function based on shortest path, modifies selected path according to the function above so as to fit multi-QoS parameters. Simulation results show that the algorithm has both lower delay and better performance and can be extended to cases of multiple QoS parameters conveniently.

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 An Efficient Availability Guaranteed Deployment Scheme for IoT Service Chains over Fog-Core Cloud Networks

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3970 ◽  
Author(s):  
Ngoc-Thanh Dinh ◽  
Younghan Kim
Keyword(s):  
Critical Issue ◽  
High Availability ◽  
Network Function Virtualization ◽  
Cloud Networks ◽  
Protection Scheme ◽  
Network Function ◽  
Resource Limitations ◽  
Additional Protection ◽  
Cost Efficient ◽  
The Cost

High availability is one of the important requirements of many end-to-end services in the Internet of Things (IoT). This is a critical issue in network function virtualization (NFV) and NFV-enabled service function chaining (SFC) due to hard- and soft-ware failures. Thus, merely mapping primary VNFs is not enough to ensure high availability, especially for SFCs deployed over fog - core cloud networks due to resource limitations of fogs. As a result, additional protection schemes, like VNF redundancy deployments, are required to improve the availability of SFCs to meet predefined requirements. With limited resources of fog instances, a cost-efficient protection scheme is required. This paper proposes a cost-efficient availability guaranteed deployment scheme for IoT services over fog-core cloud networks based on measuring the improvement potential of VNFs for improving the availability of SFCs. In addition, various techniques for redundancy placement for VNFs at the fog layer are also presented. Obtained analysis and simulation results show that the proposed scheme achieves a significant improvement in terms of the cost efficiency and scalability compared to the state-of-the-art approaches.

scholarly journals Impact of the Maximum Number of Switching Reconfigurations on the Cost Saving in Network Function Virtualization Environments with Elastic Optical Interconnection

2019 ◽  
Vol 9 (23) ◽  
pp. 5167
Author(s):  
Vincenzo Eramo ◽  
Francesco G. Lavacca ◽  
Tiziana Catena
Keyword(s):  
Computational Complexity ◽  
Cost Saving ◽  
Virtual Machines ◽  
New Technology ◽  
Network Function Virtualization ◽  
Optical Interconnection ◽  
Network Function ◽  
Network Functions ◽  
The Cost ◽  
The Impact

Network Function Virtualization is based on the virtualization of the network functions and it is a new technology allowing for a more flexible allocation of cloud and bandwidth resources. In order to employ the flexibility of the technology and to adapt its use according to the traffic variation, reconfigurations of the cloud and bandwidth resources are needed by means of both migration of the Virtual Machines executing the network functions and reconfiguration of circuits interconnecting the Virtual Machines. The objective of the paper is to study the impact of the maximum number of switch reconfigurations on the cost saving that the Networking Function Virtualization technology allows us to achieve. The problem is studied in the case of a scenario with an elastic optical network interconnecting datacenters in which the Virtual Machines are executed. The problem can be formulated as an Integer Linear Programming one introducing a constraint on the maximum number of switch reconfigurations but due to its computational complexity we propose a low computational complexity heuristic allowing for results close to the optimization ones. The results show how the limitation on the number of possible reconfigurations has to be taken into account to evaluate the effectiveness in terms of cost saving that the Virtual Machine migrations in Network Function Virtualization environment allows us to achieve.

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.

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