Service Chain (SC) Mapping with Multiple SC Instances in a Wide Area Network

Network Function Virtualization (NFV) aims to simplify deployment of network services by running Virtual Network Functions (VNFs) on commercial off-the-shelf servers. Service deployment involves placement of VNFs and in-sequence routing of traffic flows through VNFs comprising a Service Chain (SC). The joint VNF placement and traffic routing is usually referred as SC mapping. In a Wide Area Network (WAN), a situation may arise where several traffic flows, generated by many distributed node pairs, require the same SC, one single instance (or occurrence) of that SC might not be enough. SC mapping with multiple SC instances for the same SC turns out to be a very complex problem, since the sequential traversal of VNFs has to be maintained while accounting for traffic flows in various directions. Our study is the first to deal with SC mapping with multiple SC instances to minimize network resource consumption. Exact mathematical modeling of this problem results in a quadratic formulation. We propose a two-phase column-generation-based model and solution in order to get results over large network topologies within reasonable computational times. Using such an approach, we observe that an appropriate choice of only a small set of SC instances can lead to solution very close to the minimum bandwidth consumption

Make-Before-Break Wavelength Defragmentation

International audienceFuture optical networks, in particular Software Defined Optical Networks (SDONs), are expected to provide reconfigurable services while maintaining an efficient usage of wavelength resources. In this paper, we propose a Make-Before-Break (MBB) wavelength defragmentation process which minimizes the bandwidth requirement of the resulting provisioning. We next compare the latter provisioning with a minimum bandwidth provisioning that is not subject to MBB. The resulting solution process is thoroughly tested on various data and network instances. Numerical experiments show that, on average, the best seamless lightpath rerouting is never more than 5% away (less than 1% on average) from an optimal lightpath provisioning

Exhaustive Search for Optimal Offline Spectrum Assignment in Elastic Optical Networks

Heuristic-based approaches are widely deployed in solving Spectrum Assignment problem. This causes the results to be unreliable in some test cases when the results are very far from the lowerbound. This paper presents an exhaustive search approach that starts with an initial seed of a solution achieved by a heuristic-based algorithm called “Longest First Fit” (LFF) and tries all possible permutations starting from this initial seed. The algorithm skips some branches and all its descendant permutations if it meets certain criteria that guarantees that those permutations will not lead to a better result. The experimental results show that the new algorithm has succeeded in achieving the lower-bound in 93% of the randomly generated test cases while the heuristic solver LFF can achieve 65%. The algorithm achieves these results in a reasonable running time of less than 10 seconds

A Scalable Approach for Service Chain (SC) Mapping with Multiple SC Instances in a Wide-Area Network

Network Function Virtualization (NFV) aims to simplify deployment of network services by running Virtual Network Functions (VNFs) on commercial off-the-shelf servers. Service deployment involves placement of VNFs and in-sequence routing of traffic flows through VNFs comprising a Service Chain (SC). The joint VNF placement and traffic routing is called SC mapping. In a Wide-Area Network (WAN), a situation may arise where several traffic flows, generated by many distributed node pairs, require the same SC; then, a single instance (or occurrence) of that SC might not be enough. SC mapping with multiple SC instances for the same SC turns out to be a very complex problem, since the sequential traversal of VNFs has to be maintained while accounting for traffic flows in various directions. Our study is the first to deal with the problem of SC mapping with multiple SC instances to minimize network resource consumption. We first propose an Integer Linear Program (ILP) to solve this problem. Since ILP does not scale to large networks, we develop a column-generation-based ILP (CG-ILP) model. However, we find that exact mathematical modeling of the problem results in quadratic constraints in our CG-ILP. The quadratic constraints are made linear but even the scalability of CG-ILP is limited. Hence, we also propose a two-phase column-generation-based approach to get results over large network topologies within reasonable computational times. Using such an approach, we observe that an appropriate choice of only a small set of SC instances can lead to a solution very close to the minimum bandwidth consumption. Further, this approach also helps us to analyze the effects of number of VNF replicas and number of NFV nodes on bandwidth consumption when deploying these minimum number of SC instances.Comment: arXiv admin note: substantial text overlap with arXiv:1704.0671

Advanced Column Generation Decompositions for Optimizing Provisioning Problems in Optical Networks

With the continued growth of Internet traffic, and the scarcity of the optical spectrum, there is a continuous need to optimize the usage of this resource. In the process of provisioning optical networks, telecommunication operators must deal with combinatorial optimization problems that are NP-complete. One of these problems is the Routing and Wavelength Allocation (RWA) which considers the fixed frequency grid, and the Routing and Spectrum Allocation (RSA) which is defined for the flexible frequency grid. While the flexible frequency grid paradigm attempted to improve the spectrum usage, the RSA problem has an additional spectrum dimension that makes it harder than the RWA problem. In this thesis, in continuation of the previous studies, and using the advanced techniques of Integer Linear Programing, we propose a Column Generation algorithm based on a Lightpath decomposition which we implement for both the RWA and the RSA problems. This algorithm proved to be the most efficient so far producing optimal or near optimal solutions, and improving the computation times by two orders of magnitude on average. This algorithm is based on the approach of finding the right decomposition scheme as to be able to solve the Pricing Problem in a polynomial time. This approach can be used in other optimization problems. In addition, we consider the same Configuration decomposition as the previous studies, and we propose an algorithm based on Nested Column Generation. We implemented this algorithm for both the RSA and the RWA problems, which led to a considerable improvement on the previous algorithms that use the same Configuration decomposition. This Nested Column Generation approach can be adopted in other optimization problems