Distributed workload control for federated service discovery

The diffusion of the internet paradigm in each aspect of human life continuously fosters the widespread of new technologies and related services. In the Future Internet scenario, where 5G telecommunication facilities will interact with the internet of things world, analyzing in real time big amounts of data to feed a potential infinite set of services belonging to different administrative domains, the role of a federated service discovery will become crucial. In this paper the authors propose a distributed workload control algorithm to handle efficiently the service discovery requests, with the aim of minimizing the overall latencies experienced by the requesting user agents. The authors propose an algorithm based on the Wardrop equilibrium, which is a gametheoretical concept, applied to the federated service discovery domain. The proposed solution has been implemented and its performance has been assessed adopting different network topologies and metrics. An open source simulation environment has been created allowing other researchers to test the proposed solution

Enabling Multipath and Multicast Data Transmission in Legacy and Future Internet

The quickly growing community of Internet users is requesting multiple applications and services. At the same time the structure of the network is changing. From the performance point of view, there is a tight interplay between the application and the network design. The network must be constructed to provide an adequate performance of the target application. In this thesis we consider how to improve the quality of users' experience concentrating on two popular and resource-consuming applications: bulk data transfer and real-time video streaming. We share our view on the techniques which enable feasibility and deployability of the network functionality leading to unquestionable performance improvement for the corresponding applications. Modern mobile devices, equipped with several network interfaces, as well as multihomed residential Internet hosts are capable of maintaining multiple simultaneous attachments to the network. We propose to enable simultaneous multipath data transmission in order to increase throughput and speed up such bandwidth-demanding applications as, for example, file download. We design an extension for Host Identity Protocol (mHIP), and propose a multipath data scheduling solution on a wedge layer between IP and transport, which effectively distributes packets from a TCP connection over available paths. We support our protocol with a congestion control scheme and prove its ability to compete in a friendly manner against the legacy network protocols. Moreover, applying game-theoretic analytical modelling we investigate how the multihomed HIP multipath-enabled hosts coexist in the shared network. The number of real-time applications grows quickly. Efficient and reliable transport of multimedia content is a critical issue of today's IP network design. In this thesis we solve scalability issues of the multicast dissemination trees controlled by the hybrid error correction. We propose a scalable multicast architecture for potentially large overlay networks. Our techniques address suboptimality of the adaptive hybrid error correction (AHEC) scheme in the multicast scenarios. A hierarchical multi-stage multicast tree topology is constructed in order to improve the performance of AHEC and guarantee QoS for the multicast clients. We choose an evolutionary networking approach that has the potential to lower the required resources for multimedia applications by utilizing the error-correction domain separation paradigm in combination with selective insertion of the supplementary data from parallel networks, when the corresponding content is available. Clearly both multipath data transmission and multicast content dissemination are the future Internet trends. We study multiple problems related to the deployment of these methods.Internetin nopeasti kasvava käyttäjäkunta vaatii verkolta yhä enemmän sovelluksia ja palveluita. Samaan aikaan verkon rakenne muuttuu. Suorituskyvyn näkökulmasta on olemassa selvä vuorovaikutussovellusten ja verkon suunnittelun välillä. Verkko on rakennettava siten, että se pystyy takaamaan riittävän suorituskyvyn halutuille palveluille. Tässä väitöskirjassa pohditaan, miten verkon käyttökokemusta voidaan parantaa keskittyen kahteen suosittuun ja resursseja vaativaan sovellukseen: tiedonsiirtoon ja reaaliaikaiseen videon suoratoistoon. Esitämme näkemyksemme tekniikoista, jotka mahdollistavat tarvittavien verkkotoiminnallisuuksien helpon toteuttavuuden sekä kiistatta parantavat sovelluksien suorityskykyä. Nykyaikaiset mobiililaitteet monine verkkoyhteyksineen, kuten myös kotitietokoneet, pystyvät ylläpitämään monta internet-yhteyttä samanaikaisesti. Siksi ehdotamme monikanavaisen tiedonsiirron käyttöä suorituskyvyn parantamiseksi ja etenkin vaativien verkkosovelluksien, kuten tiedostonsiirron, nopeuttamiseksi. Tässä väitöskirjassa suunnitellaan Host Identity Protocol (mHIP) -laajennus, sekä esitetään tiedonsiirron vuorotteluratkaisu, joka hajauttaa TCP-yhteyden tiedonsiirtopaketit käytettävissä oleville kanaville. Protokollamme tueksi luomme myös ruuhkautumishallinta-algoritmin ja näytämme sen pystyvän toimimaan yhteen nykyisien verkkoprotokollien kanssa. Tämän lisäksi tutkimme peliteoreettista mallinnusta käyttäen, miten monikanavaiset HIP-verkkopäätteet toimivat muiden kanssa jaetuissa verkoissa. Reaaliaikaisten sovellusten määrä kasvaa nopeasti. Tehokas ja luotettava multimediasisällön siirto on olennainen vaatimus nykypäivän IP-verkoissa. Tässä työssä ratkaistaan monilähetyksen (multicast) jakelustruktuurin skaalautuvuuteen liittyviä ongelmia. Ehdotamme skaalautuvaa monilähetysarkkitehtuuria suurille peiteverkoille. Ratkaisumme puuttuu adaptiivisen virhekorjauksen (Adaptive Hybrid Error Correction, AHEC) alioptimaalisuuteen monilähetystilanteissa. Luomme hierarkisen monivaiheisen monilähetyspuutopologian parantaaksemme AHECin suorituskykyä, sekä taataksemme monilähetysasiakkaiden palvelun laadun. Valitsimme evoluutiomaisen lähestymistavan, jolla on potentiaalia keventää multimediasovelluksien verkkoresurssivaatimuksia erottamalla virhekorjauksen omaksi verkkotunnuksekseen, sekä käyttämällä valikoivaa täydentävää tiedonlisäystä rinnakkaisverkoista vastaavan sisällön ollessa saatavilla. Sekä monikanava- että monilähetystiedonsiirto ovat selvästi osa internetin kehityssuuntaa. Tässä väitöskirjassa tutkimme monia ongelmia näiden tekniikoiden käyttöönottoon liittyen

Fair Resource Allocation in Macroscopic Evacuation Planning Using Mathematical Programming: Modeling and Optimization

Evacuation is essential in the case of natural and manmade disasters such as hurricanes, nuclear disasters, fire accidents, and terrorism epidemics. Random evacuation plans can increase risks and incur more losses. Hence, numerous simulation and mathematical programming models have been developed over the past few decades to help transportation planners make decisions to reduce costs and protect lives. However, the dynamic transportation process is inherently complex. Thus, modeling this process can be challenging and computationally demanding. The objective of this dissertation is to build a balanced model that reflects the realism of the dynamic transportation process and still be computationally tractable to be implemented in reality by the decision-makers. On the other hand, the users of the transportation network require reasonable travel time within the network to reach their destinations. This dissertation introduces a novel framework in the fields of fairness in network optimization and evacuation to provide better insight into the evacuation process and assist with decision making. The user of the transportation network is a critical element in this research. Thus, fairness and efficiency are the two primary objectives addressed in the work by considering the limited capacity of roads of the transportation network. Specifically, an approximation approach to the max-min fairness (MMF) problem is presented that provides lower computational time and high-quality output compared to the original algorithm. In addition, a new algorithm is developed to find the MMF resource allocation output in nonconvex structure problems. MMF is the fairness policy used in this research since it considers fairness and efficiency and gives priority to fairness. In addition, a new dynamic evacuation modeling approach is introduced that is capable of reporting more information about the evacuees compared to the conventional evacuation models such as their travel time, evacuation time, and departure time. Thus, the contribution of this dissertation is in the two areas of fairness and evacuation. The first part of the contribution of this dissertation is in the field of fairness. The objective in MMF is to allocate resources fairly among multiple demands given limited resources while utilizing the resources for higher efficiency. Fairness and efficiency are contradicting objectives, so they are translated into a bi-objective mathematical programming model and solved using the ϵ-constraint method, introduced by Vira and Haimes (1983). Although the solution is an approximation to the MMF, the model produces quality solutions, when ϵ is properly selected, in less computational time compared to the progressive-filling algorithm (PFA). In addition, a new algorithm is developed in this research called the θ progressive-filling algorithm that finds the MMF in resource allocation for general problems and works on problems with the nonconvex structure problems. The second part of the contribution is in evacuation modeling. The common dynamic evacuation models lack a piece of essential information for achieving fairness, which is the time each evacuee or group of evacuees spend in the network. Most evacuation models compute the total time for all evacuees to move from the endangered zone to the safe destination. Lack of information about the users of the transportation network is the motivation to develop a new optimization model that reports more information about the users of the network. The model finds the travel time, evacuation time, departure time, and the route selected for each group of evacuees. Given that the travel time function is a non-linear convex function of the traffic volume, the function is linearized through a piecewise linear approximation. The developed model is a mixed-integer linear programming (MILP) model with high complexity. Hence, the model is not capable of solving large scale problems. The complexity of the model was reduced by introducing a linear programming (LP) version of the full model. The complexity is significantly reduced while maintaining the exact output. In addition, the new θ-progressive-filling algorithm was implemented on the evacuation model to find a fair and efficient evacuation plan. The algorithm is also used to identify the optimal routes in the transportation network. Moreover, the robustness of the evacuation model was tested against demand uncertainty to observe the model behavior when the demand is uncertain. Finally, the robustness of the model is tested when the traffic flow is uncontrolled. In this case, the model's only decision is to distribute the evacuees on routes and has no control over the departure time

Simple and stable dynamic traffic engineering for provider scale ethernet

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia InformáticaThe high speeds and decreasing costs of Ethernet solutions has motivated providers’ interest in using Ethernet as the link layer technology in their backbone and aggregation networks. Provider scale Ethernet offers further advantages, providing not only an easy to manage solution for multicast traffic, but also transparent interconnection between clients’ LANs. These Ethernet deployments face altogether different design issues, requiring support for a significantly higher number of hosts. This support relies on hierarquization, separating address and virtual network spaces of customers and providers. In addition, large scale Ethernet solutions need to grant forwarding optimality. This can be achieved using traffic engineering approaches. Traffic engineering defines the set of engineering methods and techniques used to optimize the flow of network traffic. Static traffic engineering approaches enjoy widespread use in provider networks, but their performance is greatly penalized by sudden load variations. On the other hand, dynamic traffic engineering is tailored to adapt to load changes. However, providers are skeptical to adopt dynamic approaches as these induce problems such as routing instability, and as a result, network performance decreases. This dissertation presents a Simple and Stable Dynamic Traffic Engineering framework (SSD-TE), which addresses these concerns in a provider scale Ethernet scenario. The validation results show that SSD-TE achieves better or equal performance to static traffic engineering approaches, whilst remaining both stable and responsive to load variations

GAME THEORETIC FLOW AND ROUTING CONTROL FOR COMMUNICATION NETWORKS

As the need to support high speed data exchange in modern communication networks grows rapidly, effective and fair sharing of the network resources becomes very important. Today's communication networks typically involve a large number of users that share the same network resources but may have different, and often competing, objectives. Advanced network protocols that are implemented to optimize the performance of such networks typically assume that the users are passive and are willing to accept compromising their own performance for the sake of optimizing the performance of the overall network. However, considering the trend towards more decentralization in the future, it is natural to assume that the users in a large network may take a more active approach and become more interested in optimizing their own individual performances without giving much consideration to the overall performance of the network. A similar situation occurs when the users are members of teams that are sharing the network resources. A user may find itself cooperating with other members of its team which itself is competing with the other teams in the network. Game theory appears to provide the necessary framework and mathematical tools for formulating and analyzing the strategic interactions among users, or teams of users, of such networks. In this thesis, we investigate networks in which users, or teams of users, either compete or cooperate for the same network resources. We considered two important network topologies and used many examples to illustrate the various solution concepts that we have investigated.. First we consider two-nodeiiiparallel link networks with non-cooperative users trying to optimally distribute their flows among the links. For these networks, we established a condition which guarantees the existence and uniqueness of a Nash equilibrium for the link flows. We derived an analytical expression for the Nash equilibrium and investigated its properties in terms of the network parameters and the users preferences. We showed that in a competitive environment users can achieve larger flow rates by properly emphasizing the corresponding term in their utility functions, but that this can only be done at the expense of an increase in the expected delay. Next, we considered a general network structure with multiple links, multiple nodes, and multiple competing users. We proved the existence of a unique Nash equilibrium. We also investigated many of its intuitive properties. We also extended the model to a network where multiple teams of users compete with each other while cooperating within the teams to optimize a team level performance. For this model, we studied the Noninferior Nash solution and compared its results with the standard Nash equilibrium solution

Techniques d'ingénierie de trafic dynamique pour l'internet

Network convergence and new applications running on end-hosts result in increasingly variable and unpredictable traffic patterns. By providing origin-destination pairs with several possible paths, Dynamic Load-Balancing (DLB) has proved itself an excellent tool to face this uncertainty. The objective in DLB is to distribute traffic among these paths in real-time so that a certain objective function is optimized. In these dynamic schemes, paths are established a priori and the amount of traffic sent through each of them depends on the current traffic demand and network condition. In this thesis we study and propose various DLB mechanisms, differing in two important aspects. The first difference resides in the assumption, or not, that resources are reserved for each path. The second lies on the objective function, which clearly dictates the performance obtained from the network. However, a performance benchmarking of the possible choices has not been carried out so far. In this sense, for the case in which no reservations are performed, we study and compare several objective functions, including a proposal of ours. We will also propose and study a new distributed algorithm to attain the optimum of these objective functions. Its advantage with respect to previous proposals is its complete self-configuration (i. E. Convergence is guaranteed without any parametrization). Finally, we present the first complete comparative study between DLB and Robust Routing (a fixed routing configuration for all possible traffic demands). In particular, we analyze which scheme is more convenient in each given situation, and highlight some of their respective shortcomings and virtues.Avec la multiplication des services dans un même réseau et les diversités des applications utilisées par les usagers finaux, le trafic transporté est devenu très complexe et dynamique. Le Partage de la Charge Dynamique (PCD) constitue une alternative intéressante pour résoudre cette problématique. Si une paire Source-Destination est connectée par plusieurs chemins, le problème est le suivant : comment distribuer le trafic parmi ces chemins de telle façon qu’une fonction objective soit optimisé. Dans ce cas les chemins sont fixés a priori et la quantité de trafic acheminée sur chaque route est déterminée dynamiquement en fonction de la demande de trafic et de la situation actuelle du réseau. Dans cette thèse nous étudions puis nous proposons plusieurs mécanismes de PCD. Tout d'abord, nous distinguons deux types d’architecture : celles dans lesquelles les ressources sont réservées pour chaque chemin, et celles pour lesquelles aucune réservation n'est effectuée. La simplification faite dans le premier type d’architecture nous permet de proposer l'utilisation d'un nouveau mécanisme pour gérer les chemins. Partant de ce mécanisme, nous définissons un nouvel algorithme de PCD. Concernant la deuxième architecture, nous étudions et comparons plusieurs fonctions objectives. À partir de notre étude, nous proposons un nouvel algorithme distribué permettant d’atteindre l'optimum de ces fonctions objectives. La principale caractéristique de notre algorithme, et son avantage par rapport aux propositions antérieures, est sa capacité d'auto-configuration, dans la mesure où la convergence de l'algorithme est garantie sans aucun besoin de réglage préalable de ses paramètres

Algorithmic Graph Theory

The main focus of this workshop was on mathematical techniques needed for the development of efficient solutions and algorithms for computationally difficult graph problems. The techniques studied at the workshhop included: the probabilistic method and randomized algorithms, approximation and optimization, structured families of graphs and approximation algorithms for large problems. The workshop Algorithmic Graph Theory was attended by 46 participants, many of them being young researchers. In 15 survey talks an overview of recent developments in Algorithmic Graph Theory was given. These talks were supplemented by 10 shorter talks and by two special sessions