Chaima Ghribi

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This paper presents two exact algorithms for energy efficient scheduling of virtual machines (VMs) in cloud data centers. Modeling of energy aware allocation and consolidation to minimize overall energy consumption leads us to the combination of an optimal allocation algorithm with a consolidation algorithm relying on migration of VMs at service departures.(More)
This paper presents a model for Virtual Network Function (VNF) placement and chaining across Cloud environments. We propose a new analytical approach for joint VNFs placement and traffic steering for complex service chains and different VNF types. A custom greedy algorithm is also proposed to compare with our solution. Performance evaluation results show(More)
Network function virtualization (NFV) decouples software implementations of network functions from their hosts (or hardware). NFV exposes a new set of entities, the virtualized network functions (VNFs). The VNFs can be chained with other VNFs and physical network functions to realize network services. This flexibility introduced by NFV allows service(More)
This paper addresses Virtual Network Functions (VNFs) placement and chaining in the presence of physical link failures. A decision tree approach to the NP-Hard VNF placement and chaining problem is used to minimize the penalties induced by service interruptions due to link outages. Formulating the problem as decision tree reduces the complexity(More)
This paper addresses the problem of Virtualized Network Functions placement and traffic steering in Cloud infrastructures. We design an efficient dynamic programming (DP) algorithm for joint VNF placement and traffic steering that runs in polynomial time. In compliance with dynamic programming approaches, we organize the problem in smaller interdependent(More)
This paper presents a new graph-coloring model for advance resource reservation with minimum energy consumption in heterogeneous IaaS cloud data centers. We start with an exact integer linear programming (ILP) formulation which generalizes the graph coloring problem and follow with a fast Energy Efficient Graph Pre-coloring (EEGP) heuristic to address the(More)
The virtualized network functions placement and chaining problem is formulated as a decision tree to reduce significantly the complexity of service function chaining (SFC) in clouds. Each node in the tree corresponds to a virtual resource embedding and each tree branch to the mapping of a client request in some physical candidate. This transforms the(More)
This paper addresses energy efficient VNF placement and chaining over NFV enabled infrastructures. VNF placement and chaining are formulated as a decision tree search to overcome this NP-Hard problem complexity. The proposed approach is an extension of the Monte Carlo Tree Search(MCTS) method to achieve energy savings using physical resourceconsolidation(More)