VNE-AC: Virtual Network Embedding Algorithm Based on Ant Colony Metaheuristic

Fajjari, Ilhem; Saadi, Nadjib Ait; Pujolle, Guy; Zimmermann, Hubert

doi:10.1109/icc.2011.5963442

Cited by 123 publications

(67 citation statements)

References 7 publications

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“…Some other techniques have also been applied in this branches, such as subgraph isomorphism algorithm 14 and ant colony metaheuristic algorithm. 15 Our work differs from these existing studies in the following way: we try to address the energy-cost-aware VN embedding problem, which can save energy cost and increase the net profit for the infrastructure provider.…”

Section: Revenue-aware Vn Embeddingmentioning

confidence: 99%

Clustering-based energy-aware virtual network embedding

Zhang

et al. 2017

International Journal of Distributed Sensor Networks

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Virtual network embedding has received a lot of attention from researchers. In this problem, it needs to map a sequence of virtual networks onto the physical network. Generally, the virtual networks have topology, node, and link constraints. Prior studies mainly focus on designing a solution to maximize the revenue by accepting more virtual networks while ignoring the energy cost for the physical network. In this article, to bridge this gap, we design a heuristic energy-aware virtual network embedding algorithm called EA-VNE-C, to coordinate the dynamic electricity price and energy consumption to further optimize the energy cost. Extensive simulations demonstrate that this algorithm significantly reduces the energy cost by up to 14% over the state-of-the-art algorithm while maintaining similar revenue.

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Section: Revenue-aware Vn Embeddingmentioning

confidence: 99%

Clustering-based energy-aware virtual network embedding

Zhang

et al. 2017

International Journal of Distributed Sensor Networks

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“…The heuristic solutions have been investigated abundantly in the literature. These solutions range from metaheuristic approaches like ant-colony optimization [4] over graph isomorphism approaches [5] to Markov-Chain random walks [6]. Many of these algorithms are designed for a certain setting and are only evaluated on specific scenarios.…”

Section: Introductionmentioning

confidence: 99%

Network service chaining with efficient network function mapping based on service decompositions

Sahhaf

Tavernier

Colle

et al. 2015

Proceedings of the 2015 1st IEEE Conference on Network Softwarization (NetSoft)

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Abstract-Network Service Chaining (NSC) is a service concept which promises increased flexibility and cost-efficiency for future carrier networks. The two recent developments, Network Function Virtualization (NFV) and Software-Defined Networking (SDN), are opportunities for service providers to simplify the service chaining and provisioning process and reduce the cost (in CAPEX and OPEX) while introducing new services as well. One of the challenging tasks regarding NFV-based services is to efficiently map them to the components of a physical network based on the services specifications/constraints. In this paper, we propose an efficient cost-effective algorithm to map NSCs composed of Network Functions (NF) to the network infrastructure while taking possible decompositions of NFs into account. NF decomposition refers to converting an abstract NF to more refined NFs interconnected in form of a graph with the same external interfaces as the higher-level NF. The proposed algorithm tries to minimize the cost of the mapping based on the NSCs requirements and infrastructure capabilities by making a reasonable selection of the NFs decompositions. Our experimental evaluations show that the proposed scheme increases the acceptance ratio significantly while decreasing the mapping cost in the long run, compared to schemes in which NF decompositions are selected randomly.

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“…Meta-heuristics such as ant colony optimization, simulated annealing, genetic algorithms or tabu search are used to find a close to optimal solutions. An example is the Max-Min Ant Colony meta-heuristic proposed in [13] to solve the VNEP.…”

Section: Related Workmentioning

confidence: 99%

Network service chaining with optimized network function embedding supporting service decompositions

et al. 2015

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The rise of Software-Defined Networking (SDN) and Network Function Virtualization (NFV) introduces opportunities for service providers to reduce CAPEX/OPEX and to offer and quickly deploy novel network services. In particular, SDN and NFV enable the flexible composition of network functions, a generic service concept known as Network Service Chaining (NSC).However, the control of resources, management and configuration of network service chains is challenging. In particular, there typically exist multiple options on how an abstract network service can be decomposed into more refined, interconnected network functions. Moreover, efficient algorithms have to be devised to allocate the network functions. The underlying algorithmic problem can be seen as a novel generalization of the Virtual Network Embedding Problem (VNEP), where there exist multiple realization options. The joint optimization of decomposition and embedding has not been studied in the literature before. This paper studies the problem of how to optimally decompose and embed network services. In particular, we propose two novel algorithms to map NSCs to the network infrastructure while allowing possible decompositions of network functions. The first algorithm is based on Integer Linear Programming which minimizes the cost of the mapping based on the NSCs requirements and infrastructure capabilities. The second one is a heuristic algorithm to solve the scalability issue of the ILP formulation. It targets to minimize the mapping cost by making a reasonable selection of the network function decompositions. The experimental results indicate that considering network function decompositions at the time of the embedding significantly improves the embedding performance in terms of acceptance ratio while decreasing the mapping cost in the long run in both optimal and heuristic solutions.

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VNE-AC: Virtual Network Embedding Algorithm Based on Ant Colony Metaheuristic

Cited by 123 publications

References 7 publications

Clustering-based energy-aware virtual network embedding

Clustering-based energy-aware virtual network embedding

Network service chaining with efficient network function mapping based on service decompositions

Network service chaining with optimized network function embedding supporting service decompositions

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