Abstract:
Network function virtualization paradigm enables us to implement network functions provided in middleboxes as softwares that run on commodity servers. This paper proposes...Show MoreMetadata
Abstract:
Network function virtualization paradigm enables us to implement network functions provided in middleboxes as softwares that run on commodity servers. This paper proposes a backup resource allocation model for middleboxes with considering both failure probabilities of network functions and backup servers. A backup server can protect several functions; a function can have multiple backup servers. We take the importance of functions into account by defining a weighted unavailability for each function. We aim to find an assignment of backup servers to functions, where the worst weighted unavailability is minimized. We formulate the proposed backup resource allocation model as a mixed integer linear programming problem. We prove that the backup resource allocation problem for middlebox with importance is NP-complete. We develop three heuristic algorithms with polynomial time complexity to solve the problem. We analyze the approximation performances of different heuristic algorithms with providing several lower and upper bounds. We present the competitive evaluation in terms of deviation and computation time among the results obtained by running the heuristic algorithms and by solving the mixed integer linear programming problem. The results show the pros and cons of different approaches. With our analyses, a network operator can choose an appropriate approach according to the requirements in specific application scenarios.
Published in: IEEE/ACM Transactions on Networking ( Volume: 27, Issue: 4, August 2019)
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- IEEE Keywords
- Index Terms
- Middlebox ,
- Backup Resources ,
- Important Functions ,
- Computation Time ,
- Upper Bound ,
- Functional Networks ,
- Performance Of Algorithm ,
- Time Complexity ,
- Linear Programming ,
- Linear Problem ,
- Network Operators ,
- Heuristic Algorithm ,
- Probability Of Failure ,
- Mixed Integer Linear Programming ,
- Performance Of Different Algorithms ,
- Virtual Network Functions ,
- Integer Linear Programming Problem ,
- Special Case ,
- Computational Complexity ,
- Set Of Functions ,
- Feasible Solution ,
- Elimination Procedure ,
- Set Of Servers ,
- Problem Size ,
- Greedy Approach ,
- Intrusion Detection System ,
- Even Number ,
- General Case ,
- Heuristic Approach ,
- Breadth-first Search
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Middlebox ,
- Backup Resources ,
- Important Functions ,
- Computation Time ,
- Upper Bound ,
- Functional Networks ,
- Performance Of Algorithm ,
- Time Complexity ,
- Linear Programming ,
- Linear Problem ,
- Network Operators ,
- Heuristic Algorithm ,
- Probability Of Failure ,
- Mixed Integer Linear Programming ,
- Performance Of Different Algorithms ,
- Virtual Network Functions ,
- Integer Linear Programming Problem ,
- Special Case ,
- Computational Complexity ,
- Set Of Functions ,
- Feasible Solution ,
- Elimination Procedure ,
- Set Of Servers ,
- Problem Size ,
- Greedy Approach ,
- Intrusion Detection System ,
- Even Number ,
- General Case ,
- Heuristic Approach ,
- Breadth-first Search
- Author Keywords