Yuan, G., Xu, Z., Yang, B., Liang, W., Chai, W. K., Tuncer, D., Galis, A., Pavlou, G. and Wu, G., 2020. Fault Tolerant Placement of Stateful VNFs and Dynamic Fault Recovery in Cloud Networks. Computer Networks: The International Journal of Computer and Telecommunications Networking, 166, 106953.
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DOI: 10.1016/j.comnet.2019.106953
Abstract
Traditional network functions such as firewalls are implemented in costly dedicated hardware. By decoupling network functions from physical devices, network function virtualization enables virtual network functions (VNF) to run in virtual machines (VMs). However, VNFs are vulnerable to various faults such as software and hardware failures. To enhance VNF fault tolerance, the deployment of backup VNFs in stand-by VM instances is necessary. In case of stateful VNFs, stand-by instances require constant state updates from active instances during its operation. This will guarantee a correct and seamless handover from failed instances to stand-by instances after failures. Nevertheless, such state updates to stand-by instances could consume significant network bandwidth resources and lead to potential admission failures for VNF requests. In this paper, we study the fault-tolerant VNF placement problem with the optimization objective of admitting as many requests as possible. In particular, the VNF placement of active/stand-by instances, the request routing paths to active instances, and state transfer paths to stand-by instances are jointly considered. We devise an efficient heuristic algorithm to solve this problem. For the fault tolerance problem without computing or bandwidth constraints, we also propose two bicriteria approximation algorithms with performance guarantees for a special case of the problem. Given the placement locations of VNFs, some of them may go faulty. We thus consider the dynamic fault recovery problem, for which we propose an approximation algorithm that dynamically switches traffic processing from faulty VNFs to normal ones. Simulations with realistic settings show that our algorithms can significantly improve the request admission rate compared to conventional approaches.
Item Type: | Article |
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ISSN: | 0376-5075 |
Uncontrolled Keywords: | Fault-tolerance; network function virtualization; cost minimization; bicriteria approximation algorithms; algorithm analysis. |
Group: | Faculty of Science & Technology |
ID Code: | 32997 |
Deposited By: | Symplectic RT2 |
Deposited On: | 04 Nov 2019 11:26 |
Last Modified: | 14 Mar 2022 14:18 |
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