Dans cette thèse, nous étudions les décompositions arborescentes qui satisfont certaines contraintes supplémentaires et nous proposons des algorithmes pour les calculer dans certaines classes de graphes. Finalement, nous résolvons des problèmes liés au routage en utilisant ces décompositions ainsi que des propriétés structurelles des graphes. Cette thèse est divisée en deux parties. Dans la première partie, nous étudions les décompositions arborescentes satisfaisant des propriétés spécifiques. Dans le Chapitre 2, nous étudions les décompositions de taille minimum, c’est-À-Dire avec un nombre minimum de sacs. Etant donné une entier k 4 fixé, nous prouvons que le problème de calculer une décomposition arborescente de largeur au plus k et de taille minimum est NP-Complet dans les graphes de largeur arborescente au plus 4. Nous décrivons ensuite des algorithmes qui calculent des décompositions de taille minimum dans certaines classes de graphes de largeur arborescente au plus 3. Ces résultats ont été présentés au workshop international ICGT 2014. Dans le Chapitre 3, nous étudions la cordalité des graphes et nous introduisons la notion de k-Good décomposition arborescente. Nous étudions tout d’abord les jeux de Gendarmes et Voleur dans les graphes sans long cycle induit. Notre résultat principal est un algorithme polynomial qui, étant donné un graphe G, soit trouve un cycle induit de longueur au moins k+1, ou calcule une k-Good décomposition de G. Ces résultats ont été publiés à la conférence internationale ICALP’12 et dans la revue internationale Algorithmica. Dans la seconde partie de la thèse, nous nous concentrons sur des problèmes de routage. / A tree decomposition of a graph is a way to represent it as a tree by preserving some connectivity properties of the initial graph. Tree decompositions have been widely studied for their algorithmic applications, in particular using dynamic programming approach. In this thesis, we study tree decompositions satisfying various constraints and design algorithms to compute them in some graph classes. We then use tree decompositions or specific graph properties to solve several problems related to routing. The thesis is divided into two parts. In the first part, we study tree decompositions satisfying some properties. In Chapter 2, we investigate minimum size tree decompositions, i.e., with minimum number of bags. Given a fixed k 4, we prove it is NP-Hard to compute a minimum size decomposition with width at most k in the class of graphs with treewidth at least 4. We design polynomial time algorithms to compute minimum size tree decompositions in some classes of graphs with treewidth at most 3 (including trees). Part of these results will be presented in ICGT 2014. In Chapter 3, we study the chordality (longest induced cycle) of graphs and introduce the notion of good tree decomposition (where each bag must satisfy some particular structure). Precisely, we study the Cops and Robber games in graphs with no long induced cycles. Our main result is the design of a polynomial-Time algorithm that either returns an induced cycle of length at least k+1 of a graph G or compute a k-Good tree decomposition of G. These results have been published in ICALP 2012 and Algorithmica. In the second part of the thesis, we focus on routing problems.

The aim of the thesis was minimize the planned cost of construction of the electricity network in North Africa and the Arabian peninsula between solar power plant in Desertec project. The work is divided into three chapters. The first chapter is devoted Desertec concept, its key technologies, benefits and barriers. Another chapter is devoted to the theory of graphs. It consists of an introduction to graph theory, minimum spanning tree and Steiner tree. The third practical chapter is devoted to reduction of the initial projected cost of constructing Electric Supply network using Steiner tree and its modifications. It also addresses the issue of valuation of edges and nodes to which it is necessary to include a number of factors such as energy capacity to be transmitted, the type of transmission medium, environmental conditions, geomorphological aspects and other safety regulatory requirements.

Neste projeto estudamos algoritmos de aproximação para o problema da árvore de Steiner com coleta de prêmios. Trata-se de uma generalização do problema da árvore de Steiner, onde é dado um grafo com custos positivos nas arestas e penalidades positivas nos vértices. O objetivo é encontrar uma subárvore do grafo que minimize a soma dos custos das arestas mais a soma das penalidades dos vértices que não pertencem à subárvore. Em 2009, os autores Archer, Bateni, Hajiaghayi e Karloff obtiveram pela primeira vez um algoritmo com fator de aproximação estritamente menor do que 2. Além de analisarmos este algoritmo, estudamos também a implementação de algoritmos 2-aproximação para o problema da árvore de Steiner e da árvore de Steiner com coleta de prêmios. / In this project we analyze approximation algorithms for the prize-collecting Steiner tree problem. This is a generalization of the Steiner tree problem, in which it is given a graph with positive costs in edges and positive penalties in vertices. The goal is to find a subtree of the graph that minimizes the sum of costs of edges plus the sum of the penalties of the vertices that don\'t belong to the subtree. In 2009, the authors Archer, Bateni, Hajiaghayi e Karloff described, for the first time an algorithm with approximation factor strictly less than 2. Besides analyzing this algorithm, we also study the implementation of 2-approximation algorithms to the Steiner tree problem and prize-collecting Steiner tree problem.

Die vorliegende Arbeit besteht aus zwei Teilen. Der erste Teil der Arbeit befasst sich mit unteren Schranken für approximative Steinerbaumalgorithmen. Ein Steinerbaum ist ein kürzester Teilgraph, der eine gegebene Teilmenge der Knoten eines Graphen spannt. Das Berechnen eines Steinerbaumes ist ein klassisches NP-schweres Problem, und es existieren mehrere Approximationsalgorithmen, wobei bei den meisten Algorithmen die Approximationsgüte nur durch untere und obere Schranken eingegrenzt werden kann. Für einige dieser Algorithmen werden in dieser Arbeit Instanzen vorgestellt, welche die unteren Schranken verbessern. Für den Relativen Greedy Algorithmus wird außerdem ein Verfahren vorgestellt, mit dem die Güte des Algorithmus eingeschränkt auf die Graphenklasse mit k Terminalen auf einen beliebigen Faktor genau bestimmt werden kann. Der zweite Teil der Arbeit widmet sich vollständig bipartiten Subgraphen mit gleicher Partitionsgrößse, sogenannten balancierten Bicliquen. Seit langem ist bekannt, dass in dichten bipartiten Graphen balancierte Bicliquen mit Omega(log(n)) Knoten existieren, aber es ist unbekannt, ob und wie diese in polynomieller Zeit konstruiert werden können. Der zweite Teil liefert dazu einen Beitrag, indem ein polynomieller Algorithmus vorgestellt wird, der in hinreichend großen dichten bipartiten Graphen eine balancierte Biclique mit Omega(sqrt(log(n))) Knoten konstruiert. / This thesis consists of two parts. The first part is concerned with lower bounds for approximating Steiner trees. The Steiner tree problem is to find a shortest subgraph that spans a given set of vertices in a graph and is a classical NP-hard problem. Several approximation algorithms exist, but for most algorithms only lower and upper bounds for the approximation ratio are known. For some of these algorithms we present instances which improve the lower bounds. When the problem is restricted to the class of graphs with k terminals, we also present a method which can be used to determine the approximation ratio of the Relative Greedy Algorithm with arbitrary precision. The second part is about balanced bicliques, i.e. complete bipartite subgraphs with equal partition sizes. It has been known for a long time that every dense bipartite graph contains a balanced biclique of size Omega(log(n)), but whether and how such a biclique can be constructed in polynomial time is still unknown. Our contribution to this problem is a polynomial time algorithm which constructs a balanced biclique of size Omega(sqrt(log(n))) in sufficiently large and dense bipartite graphs.

In the first part of the thesis, we address the optimization of multimedia applications such as videoconferences or multi-player games in which user-dependent information has to be sent from the users to a core node to be chosen, and then global information has to be multicast back from the core node to all users. For a given communication network, this optimization seeks a core node under two potentially competing criteria, one being the sum of the distances to a set of user terminals, the other being the cost of connecting this core node and the terminals with a multicast (or Steiner) tree. We first consider the problem of minimizing a weighted sum of the two criteria and propose a heuristic which rapidly computes a solution guaranteed to be within a few percent of the optimum. Then we characterize the worst-case trade-offs between approximation ratios for the two criteria. To state our result informally, we show that there always exists a core location for which each criterion is close to its minimum value (if we were to disregard the other criterion). In the second part, we focus on the protection of multimedia streaming applications against packet losses. Because of real-time constraints, error recovery is often achieved by Forward Error Correction (FEC) techniques which consist of partitioning the packet stream into blocks of consecutive packets and adding redundant data packets to each block. If the number of packets lost within a block is at most the number of redundant packets added, the receiver is able to recover the original data packets. Otherwise some data is irrecoverably lost. In communication networks, FEC techniques are typically impaired by the fact that packet losses are not evenly distributed among blocks but rather occur in long bursts of consecutive losses. However it has been observed that splitting the transmission of a FEC block onto several paths typically decreases the probability of an irrecoverable loss. Whereas current approaches rely on an exact computation of the probability and are consequently restricted to very small network instances, we propose to approximate this probability by measuring the impact of the chosen routing on the peakedness of the received packet stream. The peakedness of a stream may be seen as a measure of how packets are spread over time within the stream. Numerical experiments are presented and show that our method yields good approximations of the probability of irrecoverable loss./La première partie de cette thèse concerne l'optimisation d'applications multimédias, telles que des vidéoconférences ou des jeux en groupes, pour lesquels l'information propre à chaque utilisateur doit être envoyée vers un noeud central à sélectionner. L'information globale est ensuite diffusée en retour de ce noeud central vers chacun des utilisateurs. Pour un réseau de communication donné, cette optimisation consiste à choisir le noeud central selon deux critères potentiellement concurrents, le premier étant la somme des distances vers les utilisateurs, le second étant le coût de connecter ce noeud central et les utilisateurs avec un arbre multicast (ou arbre de Steiner). Nous considérons tout d'abord le problème de la minimisation d'une somme pondérée des deux critères et proposons une heuristique qui calcule rapidement une solution garantie d'être éloignée de l'optimum d'au plus quelques pour cent. Ensuite nous caractérisons les pires cas du compromis existant entre les rapports d'approximation pour les deux critères. De façon informelle, notre résultat peut se formuler comme suit : nous montrons qu'il est toujours possible de sélectionner le noeud central de telle sorte que chaque critère soit proche de sa valeur minimum (obtenue sans considérer l'autre critère). Dans la seconde partie, nous nous concentrons sur la protection des applications de diffusion multimédia (streaming) contre les pertes de paquets. A cause de contraintes temps réel, la récupération des erreurs pour ces applications est typiquement réalisée par des techniques de corrections d'erreurs dites "en avant" (Forward Error Correction ou FEC) qui consistent à partitionner le flux de paquets en blocs de paquets consécutifs et à ajouter des paquets de données redondantes à chacun de ces blocs. Si le nombre de paquets perdus au sein d'un bloc est inférieur ou égal au nombre de paquets ajoutés, le récepteur est capable de récupérer les paquets de données originaux. Dans le cas contraire, des données sont perdues de façon irrécupérable. Dans les réseaux de communication, l'efficacité des techniques FEC est typiquement dégradée par le fait que les pertes de paquets ne sont pas distribuées uniformément parmi les blocs de paquets mais apparaissent plutôt groupées par en rafales de pertes consécutives. Cependant il a été récemment observé que répartir la transmission d'un bloc FEC sur plusieurs chemins permet généralement de diminuer la probabilité de perte irrécupérable. Alors que les approches existantes se basent sur un calcul exact de cette probabilité et se limitent donc à des réseaux de très petite taille, nous proposons d'en calculer une approximation en mesurant l'impact du routage choisi sur la "peakedness" du flux de paquets. La peakedness d'un flux peut être vue comme un mesure de la répartition temporelle des paquets au sein de ce flux. Des résultats numériques sont présentés et montrent que notre méthode permet de calculer une bonne approximation de la probabilité de perte irrécupérable..

This thesis has two parts. In the first part, we study some graph covering problems with a non-local covering rule that allows a "remote" node to be covered by repeatedly applying the covering rule. In the second part, we provide some results on the packing of Steiner trees. In the Propagation problem we are given a graph $G$ and the goal is to find a minimum-sized set of nodes $S$ that covers all of the nodes, where a node $v$ is covered if (1) $v$ is in $S$, or (2) $v$ has a neighbor $u$ such that $u$ and all of its neighbors except $v$ are covered. Rule (2) is called the propagation rule, and it is applied iteratively. Throughout, we use $n$ to denote the number of nodes in the input graph. We prove that the path-width parameter is a lower bound for the optimal value. We show that the Propagation problem is NP-hard in planar weighted graphs. We prove that it is NP-hard to approximate the optimal value to within a factor of $2^{\log^{1-\epsilon}{n}}$ in weighted (general) graphs. The second problem that we study is the Power Dominating Set problem. This problem has two covering rules. The first rule is the same as the domination rule as in the Dominating Set problem, and the second rule is the same propagation rule as in the Propagation problem. We show that it is hard to approximate the optimal value to within a factor of $2^{\log^{1-\epsilon}{n}}$ in general graphs. We design and analyze an approximation algorithm with a performance guarantee of $O(\sqrt{n})$ on planar graphs. We formulate a common generalization of the above two problems called the General Propagation problem. We reformulate this general problem as an orientation problem, and based on this reformulation we design a dynamic programming algorithm. The algorithm runs in linear time when the graph has tree-width $O(1)$. Motivated by applications, we introduce a restricted version of the problem that we call the $\ell$-round General Propagation problem. We give a PTAS for the $\ell$-round General Propagation problem on planar graphs, for small values of $\ell$. Our dynamic programming algorithms and the PTAS can be extended to other problems in networks with similar propagation rules. As an example we discuss the extension of our results to the Target Set Selection problem in the threshold model of the diffusion processes. In the second part of the thesis, we focus on the Steiner Tree Packing problem. In this problem, we are given a graph $G$ and a subset of terminal nodes $R\subseteq V(G)$. The goal in this problem is to find a maximum cardinality set of disjoint trees that each spans $R$, that is, each of the trees should contain all terminal nodes. In the edge-disjoint version of this problem, the trees have to be edge disjoint. In the element-disjoint version, the trees have to be node disjoint on non-terminal nodes and edge-disjoint on edges adjacent to terminals. We show that both problems are NP-hard when there are only $3$ terminals. Our main focus is on planar instances of these problems. We show that the edge-disjoint version of the problem is NP-hard even in planar graphs with $3$ terminals on the same face of the embedding. Next, we design an algorithm that achieves an approximation guarantee of $\frac{1}{2}-\frac{1}{k}$, given a planar graph that is $k$ element-connected on the terminals; in fact, given such a graph the algorithm returns $k/2-1$ element-disjoint Steiner trees. Using this algorithm we get an approximation algorithm with guarantee of (almost) $4$ for the edge-disjoint version of the problem in planar graphs. We also show that the natural LP relaxation of the edge-disjoint Steiner Tree Packing problem has an integrality ratio of $2-\epsilon$ in planar graphs.

This thesis has two parts. In the first part, we study some graph covering problems with a non-local covering rule that allows a "remote" node to be covered by repeatedly applying the covering rule. In the second part, we provide some results on the packing of Steiner trees. In the Propagation problem we are given a graph $G$ and the goal is to find a minimum-sized set of nodes $S$ that covers all of the nodes, where a node $v$ is covered if (1) $v$ is in $S$, or (2) $v$ has a neighbor $u$ such that $u$ and all of its neighbors except $v$ are covered. Rule (2) is called the propagation rule, and it is applied iteratively. Throughout, we use $n$ to denote the number of nodes in the input graph. We prove that the path-width parameter is a lower bound for the optimal value. We show that the Propagation problem is NP-hard in planar weighted graphs. We prove that it is NP-hard to approximate the optimal value to within a factor of $2^{\log^{1-\epsilon}{n}}$ in weighted (general) graphs. The second problem that we study is the Power Dominating Set problem. This problem has two covering rules. The first rule is the same as the domination rule as in the Dominating Set problem, and the second rule is the same propagation rule as in the Propagation problem. We show that it is hard to approximate the optimal value to within a factor of $2^{\log^{1-\epsilon}{n}}$ in general graphs. We design and analyze an approximation algorithm with a performance guarantee of $O(\sqrt{n})$ on planar graphs. We formulate a common generalization of the above two problems called the General Propagation problem. We reformulate this general problem as an orientation problem, and based on this reformulation we design a dynamic programming algorithm. The algorithm runs in linear time when the graph has tree-width $O(1)$. Motivated by applications, we introduce a restricted version of the problem that we call the $\ell$-round General Propagation problem. We give a PTAS for the $\ell$-round General Propagation problem on planar graphs, for small values of $\ell$. Our dynamic programming algorithms and the PTAS can be extended to other problems in networks with similar propagation rules. As an example we discuss the extension of our results to the Target Set Selection problem in the threshold model of the diffusion processes. In the second part of the thesis, we focus on the Steiner Tree Packing problem. In this problem, we are given a graph $G$ and a subset of terminal nodes $R\subseteq V(G)$. The goal in this problem is to find a maximum cardinality set of disjoint trees that each spans $R$, that is, each of the trees should contain all terminal nodes. In the edge-disjoint version of this problem, the trees have to be edge disjoint. In the element-disjoint version, the trees have to be node disjoint on non-terminal nodes and edge-disjoint on edges adjacent to terminals. We show that both problems are NP-hard when there are only $3$ terminals. Our main focus is on planar instances of these problems. We show that the edge-disjoint version of the problem is NP-hard even in planar graphs with $3$ terminals on the same face of the embedding. Next, we design an algorithm that achieves an approximation guarantee of $\frac{1}{2}-\frac{1}{k}$, given a planar graph that is $k$ element-connected on the terminals; in fact, given such a graph the algorithm returns $k/2-1$ element-disjoint Steiner trees. Using this algorithm we get an approximation algorithm with guarantee of (almost) $4$ for the edge-disjoint version of the problem in planar graphs. We also show that the natural LP relaxation of the edge-disjoint Steiner Tree Packing problem has an integrality ratio of $2-\epsilon$ in planar graphs.

The Steiner Tree problem is one of the most popular graph problems and has many application areas. The rectilinear version of this problem, introduced by Hanan, has taken special attention since it addresses a fundamental matter in &ldquo / Physical Design&rdquo / phase of the Very Large Scale Integrated (VLSI) Computer Aided Design (CAD) process. The Rectilinear Steiner Tree Problem asks for a minimum length tree that interconnects a given set of points by only horizontal and vertical line segments, enabling the use of extra points. There are various exact algorithms. However the problem is NP-complete hence approximation algorithms have to be used especially for large instances. In this thesis work, first a survey on heuristics for the Rectilinear Steiner Tree Problem is conducted and then two recently developed successful algorithms, BGA by Kahng et. al. and RST by Zhou have been studied and investigated deeply. Both algorithms have subproblems, most of which have individual backgrounds in literature. After an analysis of BGA and RST, the thesis proposes a modification on RST, which leads to a faster and non-recursive version. The efficiency of the modified algorithm has been validated by computational tests using both random and VLSI benchmark instances. A partially parallelized version of the modified algorithm is also proposed for distributed computing environments. It is implemented using MPI (message passing interface) middleware and the results of comparative tests conducted on a cluster of workstations are presented. The proposed distributed algorithm has also proved to be promising especially for large problem instances.

Dans un graphe orienté contenant un nœud appelé racine, un sous ensemble de nœuds appelés terminaux et une pondération sur les arcs, le problème de l’arborescence de Steiner (DST) consiste en la recherche d’une arborescence de poids minimum contenant pour chaque terminal un chemin de la racine vers ce terminal. Ce problème est NP-Complet. Cette thèse se penche sur l’étude de l’approximabilité de ce problème. Sauf si P=NP, il n’existe pas pour ce problème d’approximation de rapport constant ou logarithmique en k, oú k est le nombre de terminaux. Le plus petit rapport d’approximation connu est O (k") où " est un réel strictement positif. Dans la première partie, nous donnons trois algorithmes d’approximation : un algorithme glouton efficace qui associe deux techniques d’approximations connues pour DST, un algorithme dans le cas des graphes structurés en paliers qui étudie l’approximabilité du problème quand les terminaux sont éloignés de la racine, et un algorithme exponentiel qui combine un algorithme d’approximation et un algorithme exact, dont le rapport d’approximation et la complexité temporelle sont paramétrés par le nombre de terminaux couverts par l’algorithme exact. Dans la seconde partie, nous étudions deux problèmes issus de DST auquel est ajoutée une contrainte sur les nœuds de branchement. Cette contrainte réduit le nombre de solutions réalisables et peut faciliter la recherche d’une solution optimale parmi ce sous-ensemble de solutions. En fonction de la contrainte, nous étudions la possibilité de la trouver en temps polynomial et quel est le rapport d’approximation entre cette solution et la solution du problème non contraint / The directed Steiner tree problem (DST) asks, considering a directed weighted graph, a node r called root and a set of nodes X called terminals, for a minimum cost directed tree rooted in r spanning X. DST is an NP-complete problem. We are interested in the search for polynomial approximations for DST. Unless P = NP, DST can not be approximated neither within a constant ratio nor a logarithmic ratio with respected to k, where k is the number of terminals. The smallest known approximation ratio is O(kԑ)$ where ԑ is a positive real.In the first part, we provide three new approximation algorithms : a practical greedy algorithm merging two of the main approximation techniques for DST, an algorithm for the case where the graph is layered and where the distance between the terminals and the root is high, and an exponential approximation algorithm combining an approximation algorithm and an exact algorithm, parameterized with the number of terminals the exact algorithm must cover.In the last part we study DST with two branching constraints. With this technique, we are able to reduce the number of feasible solutions, and possibly facilitate the search for an optimal solution of the constraint problem. We study how it is possible to build such a solution in polynomial time and if this solution is a good approximation of an optimal solution of the non-constraint problem

La popularité de la grande variété de l'utilisation d'Internet entraîne une croissance significative du trafic de données dans les réseaux de télécommunications. L'efficacité de la transmission de données sera contestée en vertu du principe de la capacité actuelle du réseau et des mécanismes de contrôle de flux de données. En plus d'augmenter l'investissement financier pour étendre la capacité du réseau, améliorer les techniques existantes est plus rationnel et éconmique.Diverses recherches de pointe pour faire face aux besoins en évolution des réseaux ont vu le jour, et l'une d'elles est appelée codage de réseau. Comme une extension naturelle dans la théorie du codage, il permet le mélange de différents flux réseau sur les noeuds intermédiaires, ce qui modifie la façon d'éviter les collisions de flux de données. Il a été appliqué pour obtenir un meilleur débit, fiabilité, sécurité et robustesse dans différents environnements et applications réseau. Cette thèse porte sur l'utilisation du réseau de codage pour le multicast dans les réseaux maillés fixes et systèmes de stockage distribués. Nous avons d'abord des modèles de différentes stratégies de routage multicast dans un cadre d'optimisation, y compris de multicast à base d'arbres et de codage de réseau; nous résolvons les modèles avec des algorithmes efficaces et comparons l'avantage de codage, en termes de gain de débit de taille moyenne graphique généré aléatoirement. Basé sur l'analyse numérique obtenue à partir des expériences précédentes, nous proposons un cadre révisé de routage multicast, appelé codage de réseau stratégique, qui combine transmission muticast standard et fonctions de codage de réseau afin d'obtenir le maximum de bénéfice de codage réseau au moindre coût lorsque ces coûts dépendent à la fois sur le nombre de noeuds à exécuter un codage et le volume de trafic qui est codé. Enfin, nous étudions le problème révisé de transport qui est capable de calculer un système de routage statique entre les serveurs et les clients dans les systèmes de stockage distribués où nous appliquons le codage pour soutenir le stockage de contenu. Nous étendons l'application à un problème d'optimisation général, nommé problème de transport avec des contraintes de degré, qui peut être largement utilisé dans divers domaines industriels, y compris les télécommunications, mais n'a pas été étudié très souvent. Pour ce problème, nous obtenons quelques résultats théoriques préliminaires et nous proposons une approche de décomposition Lagrange raisonnable / The popularity of the great variety of Internet usage brings about a significant growth of the data traffic in telecommunication network. Data transmission efficiency will be challenged under the premise of current network capacity and data flow control mechanisms. In addition to increasing financial investment to expand the network capacity, improving the existing techniques are more rational and economical. Various cutting-edge researches to cope with future network requirement have emerged, and one of them is called network coding. As a natural extension in coding theory, it allows mixing different network flows on the intermediate nodes, which changes the way of avoiding collisions of data flows. It has been applied to achieve better throughput and reliability, security, and robustness in various network environments and applications. This dissertation focuses on the use of network coding for multicast in fixed mesh networks and distributed storage systems. We first model various multicast routing strategies within an optimization framework, including tree-based multicast and network coding; we solve the models with efficient algorithms, and compare the coding advantage, in terms of throughput gain in medium size randomly generated graphs. Based on the numerical analysis obtained from previous experiments, we propose a revised multicast routing framework, called strategic network coding, which combines standard multicast forwarding and network coding features in order to obtain the most benefit from network coding at lowest cost where such costs depend both on the number of nodes performing coding and the volume of traffic that is coded. Finally, we investigate a revised transportation problem which is capable of calculating a static routing scheme between servers and clients in distributed storage systems where we apply coding to support the storage of contents. We extend the application to a general optimization problem, named transportation problem with degree constraints, which can be widely used in different industrial fields, including telecommunication, but has not been studied very often. For this problem, we derive some preliminary theoretical results and propose a reasonable Lagrangian decomposition approach