Scalable and Cost Efficient Algorithms for Virtual CDN Migration

Virtual Content Delivery Network (vCDN) migration is necessary to optimize the use of resources and improve the performance of the overall SDN/NFV-based CDN function in terms of network operator cost reduction and high streaming quality. It requires intelligent and enticed joint SDN/NFV migration algorithms due to the evident huge amount of traffic to be delivered to end customers of the network. In this paper, two approaches for finding the optimal and near optimal path placement(s) and vCDN migration(s) are proposed (OPAC and HPAC). Moreover, several scenarios are considered to quantify the OPAC and HPAC behaviors and to compare their efficiency in terms of migration cost, migration time, vCDN replication number, and other cost factors. Then, they are implemented and evaluated under different network scales. Finally, the proposed algorithms are integrated in an SDN/NFV framework. Index Terms: vCDN; SDN/NFV Optimization; Migration Algorithms; Scalability Algorithms.Comment: 9 pages, 11 figures, 4 tableaux, conference Local Computer Networks (LCN), class

Des techniques d’optimisation et de virtualisation adaptées aux réseaux

In this thesis, we designed and implemented a tool which performs optimizations that reduce the number of migrations necessary for a delivery task. We present our work on virtualization in the context of replication of video content servers. The work covers the design of a virtualization architecture for which there are also several algorithms that can reduce overall costs and improve system performance. The thesis is divided into several parts: optimal solutions, greedy (heuristic) solutions for reasons of scalability, orchestration of services, multi-objective optimization, service planning in complex active networks, and integration of algorithms in real platform. This thesis is supported by models, implementations and simulations which provide results that showcase our work, quantify the importance of evaluating optimization techniques and analyze the trade-off between reducing operator cost and enhancing end user satisfaction indexDans cette thèse, on présente nos travaux sur la virtualisation dans le contexte de la réplication des serveurs de contenu vidéo. Les travaux couvrent la conception d’une architecture de virtualisation pour laquelle on présente aussi plusieurs algorithmes qui peuvent réduire les couts globaux à long terme et améliorer la performance du système. Le travail est divisé en plusieurs parties : les solutions optimales, les solutions heuristiques pour des raisons de passage à l’échelle, l’orchestration des services, l’optimisation multi-objective, la planification de services dans des réseaux actifs et complexes et l'intégration d'algorithmes dans une plate-forme réell

Dynamic and Scalable Deep Neural Network Verification Algorithm

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Mathematical Programming Approach for Adversarial Attack Modelling

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Dynamic and Scalable Deep Neural Network Verification Algorithm

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Mathematical Programming Approach for Adversarial Attack Modelling

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Constrained Clustering Problems: NewOptimization Algorithms

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Constrained Clustering Problems: NewOptimization Algorithms

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HARQ-aware allocation of computing resources in C-RAN

International audienceThe principal tenet of C-RAN is the softwarization of the base-band signal processing, which enables the sharing of computing resources among ultiple radio heads. When the aggregate demand exceeds the processing capacity, a fraction of the radio packets is lost at PHY layer. Traditional computing resource allocation policies aim to minimize the packet loss rate. Dropping a PHY packet triggers a retransmission, unless the lost packet corresponds to the last available HARQ round, in which case the entirety of the radio resources spent on the multiple transmissions go to waste. This suggests that allocating computing resource accounting also for the HARQ transmission history may make a more efficient use of the bandwidth. We consider a simplified LTE uplink setting, and we measure the performance at the lower MAC layer (accuracy, goodput and average delay). We first compare the PHY-layer loss rate minimization and the cross-layer approaches using an ILP formulation. The cross-layer approach brings a tangible improvement, especially in accuracy. This suggests, for future work, that joint radio and computing resource allocation may further enhancespectral efficiency. We finally propose a probabilistic algorithm amenable to real-time operation which allows to mix strategies via parameter tuning, and we use it to explore the region of achievable goodput/accuracy trade-offs