End-to-end resource management for federated delivery of multimedia services

Recently, the Internet has become a popular platform for the delivery of multimedia content. Currently, multimedia services are either offered by Over-the-top (OTT) providers or by access ISPs over a managed IP network. As OTT providers offer their content across the best-effort Internet, they cannot offer any Quality of Service (QoS) guarantees to their users. On the other hand, users of managed multimedia services are limited to the relatively small selection of content offered by their own ISP. This article presents a framework that combines the advantages of both existing approaches, by dynamically setting up federations between the stakeholders involved in the content delivery process. Specifically, the framework provides an automated mechanism to set up end-to-end federations for QoS-aware delivery of multimedia content across the Internet. QoS contracts are automatically negotiated between the content provider, its customers, and the intermediary network domains. Additionally, a federated resource reservation algorithm is presented, which allows the framework to identify the optimal set of stakeholders and resources to include within a federation. Its goal is to minimize delivery costs for the content provider, while satisfying customer QoS requirements. Moreover, the presented framework allows intermediary storage sites to be included in these federations, supporting on-the-fly deployment of content caches along the delivery paths. The algorithm was thoroughly evaluated in order to validate our approach and assess the merits of including intermediary storage sites. The results clearly show the benefits of our method, with delivery cost reductions of up to 80 % in the evaluated scenario

Path computation in multi-layer networks: Complexity and algorithms

Carrier-grade networks comprise several layers where different protocols coexist. Nowadays, most of these networks have different control planes to manage routing on different layers, leading to a suboptimal use of the network resources and additional operational costs. However, some routers are able to encapsulate, decapsulate and convert protocols and act as a liaison between these layers. A unified control plane would be useful to optimize the use of the network resources and automate the routing configurations. Software-Defined Networking (SDN) based architectures, such as OpenFlow, offer a chance to design such a control plane. One of the most important problems to deal with in this design is the path computation process. Classical path computation algorithms cannot resolve the problem as they do not take into account encapsulations and conversions of protocols. In this paper, we propose algorithms to solve this problem and study several cases: Path computation without bandwidth constraint, under bandwidth constraint and under other Quality of Service constraints. We study the complexity and the scalability of our algorithms and evaluate their performances on real topologies. The results show that they outperform the previous ones proposed in the literature.Comment: IEEE INFOCOM 2016, Apr 2016, San Francisco, United States. To be published in IEEE INFOCOM 2016, \<http://infocom2016.ieee-infocom.org/\&g

Optimal Worst-Case QoS Routing in Constrained AWGN Channel Network

In this paper, we extend the optimal worst-case QoS routing algorithm and metric definition given in [1]. We prove that in addition to the q-ary symmetric and q-ary erasure channel model, the necessary and sufficient conditions defined in [2] for the Generalized Dijkstra's Algorithm (GDA) can be used with a constrained non-negative-mean AWGN channel. The generalization allowed the computation of the worst-case QoS metric value for a given edge weight density. The worst-case value can then be used as the routing metric in networks where some nodes have error correcting capabilities. The result is an optimal worst-case QoS routing algorithm that uses the Generalized Dijkstra's Algorithm as a subroutine with a polynomial time complexity of O(V^3)

The edge-disjoint path problem on random graphs by message-passing

We present a message-passing algorithm to solve the edge disjoint path problem (EDP) on graphs incorporating under a unique framework both traffic optimization and path length minimization. The min-sum equations for this problem present an exponential computational cost in the number of paths. To overcome this obstacle we propose an efficient implementation by mapping the equations onto a weighted combinatorial matching problem over an auxiliary graph. We perform extensive numerical simulations on random graphs of various types to test the performance both in terms of path length minimization and maximization of the number of accommodated paths. In addition, we test the performance on benchmark instances on various graphs by comparison with state-of-the-art algorithms and results found in the literature. Our message-passing algorithm always outperforms the others in terms of the number of accommodated paths when considering non trivial instances (otherwise it gives the same trivial results). Remarkably, the largest improvement in performance with respect to the other methods employed is found in the case of benchmarks with meshes, where the validity hypothesis behind message-passing is expected to worsen. In these cases, even though the exact message-passing equations do not converge, by introducing a reinforcement parameter to force convergence towards a sub optimal solution, we were able to always outperform the other algorithms with a peak of 27% performance improvement in terms of accommodated paths. On random graphs, we numerically observe two separated regimes: one in which all paths can be accommodated and one in which this is not possible. We also investigate the behaviour of both the number of paths to be accommodated and their minimum total length.Comment: 14 pages, 8 figure

Operator Calculus Algorithms for Multi-Constrained Paths

Classical approaches to multi-constrained routing problems generally require construction of trees and the use of heuristics to prevent combinatorial explosion. Introduced here is the notion of constrained path algebras and their application to multi-constrained path problems. The inherent combinatorial properties of these algebras make them useful for routing problems by implicitly pruning the underlying tree structures. Operator calculus (OC) methods are generalized to multiple non-additive constraints in order to develop algorithms for the multi constrained path problem and multi constrained optimization problem. Theoretical underpinnings are developed first, then algorithms are presented. These algorithms demonstrate the tremendous simplicity, flexibility and speed of the OC approach. Algorithms are implemented in Mathematica and Java and applied to a problem first proposed by Ben Slimane et al. as an example