Track: Tracerouting in SDN networks with arbitrary network functions

The widespread adoption of network function virtualization (NFV) leads to providing network services through a chain of virtual network functions (VNFs). This architecture is called service function chain (SFC), which can be hosted on top of commodity servers and switches located at the cloud. Meanwhile, software-defined networking (SDN) can be utilized to manage VNFs to handle traffic flows through SFC. One of the most critical issues that needs to be addressed in NFV is VNF placement that optimizes physical link bandwidth consumption. Moreover, deploying SFCs enables service providers to consider different goals, such as minimizing the overall cost and service response time. In this paper, a novel approach for the VNF placement problem for SFCs, called virtual network functions and their replica placement (VNFRP), is introduced. It tries to achieve load balancing over the core links while considering multiple resource constraints. Hence, the VNF placement problem is first formulated as an integer linear programming (ILP) optimization problem, aiming to minimize link bandwidth consumption, energy consumption, and SFC placement cost. Then, a heuristic algorithm is proposed to find a near-optimal solution for this optimization problem. Simulation studies are conducted to evaluate the performance of the proposed approach. The simulation results show that VNFRP can significantly improve load balancing by 80% when the number of replicas is increased. Additionally, VNFRP provides more than a 54% reduction in network energy consumption. Furthermore, it can efficiently reduce the SFC placement cost by more than 67%. Moreover, with the advantages of a fast response time and rapid convergence, VNFRP can be considered as a scalable solution for large networking environments.

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Demonstrating the optimal placement of virtualized cellular network functions in case of large crowd events

ACM SIGCOMM Computer Communication Review ◽

10.1145/2740070.2631428 ◽

2015 ◽

Vol 44 (4) ◽

pp. 359-360 ◽

Cited By ~ 10

Author(s):

Steffen Gebert ◽

David Hock ◽

Thomas Zinner ◽

Phuoc Tran-Gia ◽

Marco Hoffmann ◽

...

Keyword(s):

Cellular Network ◽

Optimal Placement ◽

Network Functions

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Performance-aware placement and chaining scheme for virtualized network functions: a particle swarm optimization approach

The Journal of Supercomputing ◽

10.1007/s11227-021-03758-9 ◽

2021 ◽

Author(s):

Samane Asgari ◽

Shahram Jamali ◽

Reza Fotohi ◽

Mahdi Nooshyar

Keyword(s):

Particle Swarm Optimization ◽

Particle Swarm ◽

Optimization Approach ◽

Swarm Optimization ◽

Network Functions

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Dynamic Repair and Robust Optimization of Complex Networks

Mathematical Problems in Engineering ◽

10.1155/2020/4131502 ◽

2020 ◽

Vol 2020 ◽

pp. 1-7

Author(s):

Pengtao Zhang ◽

Peng Bai ◽

Chaoqi Fu ◽

Shanshan Li

Keyword(s):

Energy Transfer ◽

Repair Process ◽

Recovery Efficiency ◽

Repair Strategy ◽

Coupling Structure ◽

Secondary Failure ◽

Fundamental Reason ◽

Network Functions ◽

The Impact ◽

Failure Node

Network repair is indispensable for maintaining network security. Conventional static repair is relatively inefficient. In this study, by considering the energy transfer between nodes, a dynamic repair model was established. The fundamental reason for the secondary failure of repaired nodes during the dynamic repair process is the coupling structure of failure networks. A dynamic repair strategy was proposed that can effectively prevent the secondary failure of repair nodes influenced by energy during repair and can cause the redundant capacity of repair nodes to be used reasonably. By turning off the energy transfer function of the link to control the excessive flow of energy into the repair node to avoid the occurrence of secondary failure; on the other hand, by sharing part of the load of the failure node, realize the rational use of the redundant capacity of the repair node to reduce the impact of the failure node on the overall function of the network. The proposed strategy mitigated the effect of failure nodes on network functions and substantially improved the recovery efficiency of network functions. Furthermore, redundant edges, behaving as energy redundant links in a network structure, can considerably improve the robustness of the network by optimizing the removal of redundant edges. Dynamic repair is not only an efficient repair method but also a highly flexible choice for network repair.

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