Game theory for collaboration in future networks

Cooperative strategies have the great potential of improving network performance and spectrum utilization in future networking environments. This new paradigm in terms of network management, however, requires a novel design and analysis framework targeting a highly flexible networking solution with a distributed architecture. Game Theory is very suitable for this task, since it is a comprehensive mathematical tool for modeling the highly complex interactions among distributed and intelligent decision makers. In this way, the more convenient management policies for the diverse players (e.g. content providers, cloud providers, home providers, brokers, network providers or users) should be found to optimize the performance of the overall network infrastructure. The authors discuss in this chapter several Game Theory models/concepts that are highly relevant for enabling collaboration among the diverse players, using different ways to incentivize it, namely through pricing or reputation. In addition, the authors highlight several related open problems, such as the lack of proper models for dynamic and incomplete information games in this area.info:eu-repo/semantics/acceptedVersio

Game theory for cooperation in multi-access edge computing

Cooperative strategies amongst network players can improve network performance and spectrum utilization in future networking environments. Game Theory is very suitable for these emerging scenarios, since it models high-complex interactions among distributed decision makers. It also finds the more convenient management policies for the diverse players (e.g., content providers, cloud providers, edge providers, brokers, network providers, or users). These management policies optimize the performance of the overall network infrastructure with a fair utilization of their resources. This chapter discusses relevant theoretical models that enable cooperation amongst the players in distinct ways through, namely, pricing or reputation. In addition, the authors highlight open problems, such as the lack of proper models for dynamic and incomplete information scenarios. These upcoming scenarios are associated to computing and storage at the network edge, as well as, the deployment of large-scale IoT systems. The chapter finalizes by discussing a business model for future networks.info:eu-repo/semantics/acceptedVersio

Game Theory for Multi-Access Edge Computing:Survey, Use Cases, and Future Trends

Game theory (GT) has been used with significant success to formulate, and either design or optimize, the operation of many representative communications and networking scenarios. The games in these scenarios involve, as usual, diverse players with conflicting goals. This paper primarily surveys the literature that has applied theoretical games to wireless networks, emphasizing use cases of upcoming multiaccess edge computing (MEC). MEC is relatively new and offers cloud services at the network periphery, aiming to reduce service latency backhaul load, and enhance relevant operational aspects such as quality of experience or security. Our presentation of GT is focused on the major challenges imposed by MEC services over the wireless resources. The survey is divided into classical and evolutionary games. Then, our discussion proceeds to more specific aspects which have a considerable impact on the game's usefulness, namely, rational versus evolving strategies, cooperation among players, available game information, the way the game is played (single turn, repeated), the game's model evaluation, and how the model results can be applied for both optimizing resource-constrained resources and balancing diverse tradeoffs in real edge networking scenarios. Finally, we reflect on lessons learned, highlighting future trends and research directions for applying theoretical model games in upcoming MEC services, considering both network design issues and usage scenarios

Resource Allocation and Service Management in Next Generation 5G Wireless Networks

The accelerated evolution towards next generation networks is expected to dramatically increase mobile data traffic, posing challenging requirements for future radio cellular communications. User connections are multiplying, whilst data hungry content is dominating wireless services putting significant pressure on network's available spectrum. Ensuring energy-efficient and low latency transmissions, while maintaining advanced Quality of Service (QoS) and high standards of user experience are of profound importance in order to address diversifying user prerequisites and ensure superior and sustainable network performance. At the same time, the rise of 5G networks and the Internet of Things (IoT) evolution is transforming wireless infrastructure towards enhanced heterogeneity, multi-tier architectures and standards, as well as new disruptive telecommunication technologies. The above developments require a rethinking of how wireless networks are designed and operate, in conjunction with the need to understand more holistically how users interact with the network and with each other. In this dissertation, we tackle the problem of efficient resource allocation and service management in various network topologies under a user-centric approach. In the direction of ad-hoc and self-organizing networks where the decision making process lies at the user level, we develop a novel and generic enough framework capable of solving a wide array of problems with regards to resource distribution in an adaptable and multi-disciplinary manner. Aiming at maximizing user satisfaction and also achieve high performance - low power resource utilization, the theory of network utility maximization is adopted, with the examined problems being formulated as non-cooperative games. The considered games are solved via the principles of Game Theory and Optimization, while iterative and low complexity algorithms establish their convergence to steady operational outcomes, i.e., Nash Equilibrium points. This thesis consists a meaningful contribution to the current state of the art research in the field of wireless network optimization, by allowing users to control multiple degrees of freedom with regards to their transmission, considering mobile customers and their strategies as the key elements for the amelioration of network's performance, while also adopting novel technologies in the resource management problems. First, multi-variable resource allocation problems are studied for multi-tier architectures with the use of femtocells, addressing the topic of efficient power and/or rate control, while also the topic is examined in Visible Light Communication (VLC) networks under various access technologies. Next, the problem of customized resource pricing is considered as a separate and bounded resource to be optimized under distinct scenarios, which expresses users' willingness to pay instead of being commonly implemented by a central administrator in the form of penalties. The investigation is further expanded by examining the case of service provider selection in competitive telecommunication markets which aim to increase their market share by applying different pricing policies, while the users model the selection process by behaving as learning automata under a Machine Learning framework. Additionally, the problem of resource allocation is examined for heterogeneous services where users are enabled to dynamically pick the modules needed for their transmission based on their preferences, via the concept of Service Bundling. Moreover, in this thesis we examine the correlation of users' energy requirements with their transmission needs, by allowing the adaptive energy harvesting to reflect the consumed power in the subsequent information transmission in Wireless Powered Communication Networks (WPCNs). Furthermore, in this thesis a fresh perspective with respect to resource allocation is provided assuming real life conditions, by modeling user behavior under Prospect Theory. Subjectivity in decisions of users is introduced in situations of high uncertainty in a more pragmatic manner compared to the literature, where they behave as blind utility maximizers. In addition, network spectrum is considered as a fragile resource which might collapse if over-exploited under the principles of the Tragedy of the Commons, allowing hence users to sense risk and redefine their strategies accordingly. The above framework is applied in different cases where users have to select between a safe and a common pool of resources (CPR) i.e., licensed and unlicensed bands, different access technologies, etc., while also the impact of pricing in protecting resource fragility is studied. Additionally, the above resource allocation problems are expanded in Public Safety Networks (PSNs) assisted by Unmanned Aerial Vehicles (UAVs), while also aspects related to network security against malign user behaviors are examined. Finally, all the above problems are thoroughly evaluated and tested via a series of arithmetic simulations with regards to the main characteristics of their operation, as well as against other approaches from the literature. In each case, important performance gains are identified with respect to the overall energy savings and increased spectrum utilization, while also the advantages of the proposed framework are mirrored in the improvement of the satisfaction and the superior Quality of Service of each user within the network. Lastly, the flexibility and scalability of this work allow for interesting applications in other domains related to resource allocation in wireless networks and beyond

Distributed optimisation techniques for wireless networks

Alongside the ever increasing traffic demand, the fifth generation (5G) cellular network architecture is being proposed to provide better quality of service, increased data rate, decreased latency, and increased capacity. Without any doubt, the 5G cellular network will comprise of ultra-dense networks and multiple input multiple output technologies. This will make the current centralised solutions impractical due to increased complexity. Moreover, the amount of coordination information that needs to be transported over the backhaul links will be increased. Distributed or decentralised solutions are promising to provide better alternatives. This thesis proposes new distributed algorithms for wireless networks which aim to reduce the amount of system overheads in the backhaul links and the system complexity. The analysis of conflicts amongst transmitters, and resource allocation are conducted via the use of game theory, convex optimisation, and auction theory. Firstly, game-theoretic model is used to analyse a mixed quality of service (QoS) strategic non-cooperative game (SNG), for a two-user multiple-input single-output (MISO) interference channel. The players are considered to have different objectives. Following this, the mixed QoS SNG is extended to a multicell multiuser network in terms of signal-to-interference-and-noise ratio (SINR) requirement. In the multicell multiuser setting, each transmitter is assumed to be serving real time users (RTUs) and non-real time users (NRTUs), simultaneously. A novel mixed QoS SNG algorithm is proposed, with its operating point identified as the Nash equilibrium-mixed QoS (NE-mixed QoS). Nash, Kalai-Smorodinsky, and Egalitarian bargain solutions are then proposed to improve the performance of the NE-mixed QoS. The performance of the bargain solutions are observed to be comparable to the centralised solutions. Secondly, user offloading and user association problems are addressed for small cells using auction theory. The main base station wishes to offload some of its users to privately owned small cell access points. A novel bid-wait-auction (BWA) algorithm, which allows single-item bidding at each auction round, is designed to decompose the combinatorial mathematical nature of the problem. An analysis on the existence and uniqueness of the dominant strategy equilibrium is conducted. The BWA is then used to form the forward BWA (FBWA) and the backward BWA (BBWA). It is observed that the BBWA allows more users to be admitted as compared to the FBWA. Finally, simultaneous multiple-round ascending auction (SMRA), altered SMRA (ASMRA), sequential combinatorial auction with item bidding (SCAIB), and repetitive combinatorial auction with item bidding (RCAIB) algorithms are proposed to perform user offloading and user association for small cells. These algorithms are able to allow bundle bidding. It is then proven that, truthful bidding is individually rational and leads to Walrasian equilibrium. The performance of the proposed auction based algorithms is evaluated. It is observed that the proposed algorithms match the performance of the centralised solutions when the guest users have low target rates. The SCAIB algorithm is shown to be the most preferred as it provides high admission rate and competitive revenue to the bidders

Contribución al modelado y al análisis mediante Teoría de Juegos de la competencia entre operadores móviles en escenarios con tecnología "small cell"

The present doctoral thesis has been realized in accordance with the research line of Economy and Regulation in Telecommunications under the doctoral programme in Telecommunications of Universitat Politècnica de València. It has been developed on the basis of various research projects, especially the "Cooperation and Opportunity for Wireless Heterogeneous Networks Project" (TIN2010-21378-C02-02), which acted as my funding agent and the "S2EuNet-Security Project" . Mobile communications have undergone notable growth from their beginning up to the present day regarding devices and bandwidth available. Service providers have now to take the challenge of such increase. New technologies are being implemented to address the challenge and all of them belong to the world of mobile communications. This thesis will focus on the solutions provided by heterogeneous nets (HetNets) and, more speci¿cally, we will look at the Small Cells technology. It is starting to be widely deployed lately and allows for a visible increase in network capacity and a resulting enhancement in availability and coverage on the user side. Abundant research has proved that the integration of these technologies within markets is technically feasible. A marketing model is however still necessary which is able to prove its economic viability. A business model was laid out where a provider sets out to deploy small cells technology and stands as an incumbent service provider. The Theory of Games was used for the analysis of such models as it allows an insight of the decisions in equilibrium when entering into a competition among themselves and try the decisions of users need to be predicted. In this way we will manage to know the effect of such decisions over the pro¿ts of all the agents in the model. A clear picture will be thus obtained of the advantages of the implementation of the new technology in the market as well as of its effects over the incumbent service providers. This thesis intends to be a contribution towards the implementation of new technologies in the market of mobile technologies through the analysis of the competence between new service providers of Small Cells and an incumbent service providers along with the behaviour of the users of mobile communications. The result show that: users get a better service, the SSP pro¿ts are guaranteed and the entrance of the SSP improves the user comfort and social welfare.Esta tesis se ha creado en el marco de la línea de investigación de Economía y Regulación de las Telecomunicaciones del programa de doctorado de Telecomunicaciones de la Universitat Politècnica de València, y se ha desarrollado en diferentes proyectos de investigación, en especial, el proyecto de "Cooperación yOportunismo enRedesde Acceso Inalámbricas y Heterogéneas" (TIN2010-21378-C02-02) y el proyecto S2EuNet-Security (FP7PEOPLE-2009- IRSES, 247083). Desde sus inicios las comunicaciones móviles han experimentado un gran crecimiento, tanto de dispositivos móviles como de cantidad de ancho de banda demandado, lo que ha provocado que los proveedores se encuentren con el desafío de hacer frente a este crecimiento. Para ello, se están implementando diferentes técnicas y tecnologías que se integran con el modeloactualdecomunicacionesmóviles.Enestatesisnoscentraremosenla solución que aportan las redes heterogéneas, especialmente en la tecnología de Small cells que se desplegado rápidamente en los últimos años y permite incrementar la capacidad de la red, así como obtener mejor disponibilidad y cobertura para los usuarios, pero falta un modelo de negocio claro donde se muestre su viabilidad económica. En esta tesis se plantea un modelo de negocio para un proveedor de servicio que despliega small cells y que compite como el proveedor de servicios incumbente. Para el análisis de este modelo se ha utilizado la Teoría de Juegos la cual ha permitido conocer las decisiones en equilibrio que toman los proveedores de servicio cuando compiten entre sí, así como las decisiones en equilibrio de los usuarios; de esta manera se ha obtenido el efecto de estas decisiones sobre los bene¿cios de todos los agentes del modelo y se han identi¿cado las ventajas y los inconvenientes que tiene la implementación de una nueva tecnología en el mercado. Esta tesis pretende ser una contribución al estudio de implementación de nuevas tecnologías en el mercado de comunicaciones móviles, más concretamente planteando modelos económicos que estudien su viabilidad a través del análisis de la competencia entre un nuevo proveedor se servicio de Small cells y el proveedor de servicio existente, y el comportamiento de los usuarios de comunicaciones móviles. Los resultados obtenidos muestran que los usuarios obtienen una mejor utilidad , el SSP siempre tiene unos bene¿cios garantizados, el MSP se ve obligado a competir y sus bene¿cios se ven perjudicados, además que la entrada del SSP mejora el bienestar de los usuarios y el bienestar social.Aquesta tesi s'ha creat en el marc de la línia de recerca d'Economia i Regulació de les Telecomunicacions del programa de doctorat de Telecomunicacions de la Universitat Politècnica de València, i s'ha desenvolupat en diferents projectes de recerca, especialment, el projecte de Çooperació i Oportunisme en Xarxes d'Accés Sense ¿ls i Heterogènies"(TIN2010-21378-C02-02) i el projecte S2EuNet-Security (FP7PEOPLE-2009- IRSES, 247083). Des dels seus inicis les comunicacions mòbils han experimentat un gran creixement, tant de dispositius mòbils com de quantitat d'amplada de banda demandada, la qual cosa ha provocat que els proveïdors es troben amb el desa¿amentdeferfrontaaquestcreixement.Peraaixò,s'estanimplementant diferents tècniques i tecnologies que s'integren amb el model actual de comunicacions mòbils. En aquesta tesi ens centrarem en la solució que aporten les xarxes heterogènies, especialment a la tecnologia de Small cells que s'ha desplegat ràpidament en els últims anys i permet incrementar la capacitat de la xarxa, així com obtenir millor disponibilitat i cobertura per als usuaris, però falta un model de negoci clar on es mostre la seua viabilitat econòmica. En aquesta tesi es planteja un model de negoci per a un proveïdor de servei que desplega Small cells i que competeix com el proveïdor de serveis incumbent. Per a l'anàlisi d'aquest model s'ha utilitzat la Teoria de Jocs la qual ha permès conéixer les decisions en equilibri que prenen els proveïdors de servei quan competeixen entre si, així com les decisions en equilibri dels usuaris; d'aquesta manera s'ha obtingut l'efecte d'aquestes decisions sobre els bene¿cis de tots els agents del model i s'han identi¿cat els avantatges i els inconvenients que té la implementació d'una nova tecnologia al mercat. Aquesta tesi pretén ser una contribució a l'estudi d'implementació de noves tecnologies al mercat de comunicacions mòbils, més concretament plantejant models econòmics que estudien la seua viabilitat a través de l'anàlisi de la competència entre un nou proveïdor se servei de Small cells i el proveïdor de servei existent, i el comportament dels usuaris de comunicacions mòbils. Els resultats obtinguts mostren que els usuaris obtenen una millor utilitat, el SSP sempre té uns bene¿cis garantits, el MSP es veu obligat a competir i els seus bene¿cis es veuen perjudicats, a més que l'entrada del SSP millora el benestar dels usuaris i el benestar social.Romero Chavarro, JC. (2017). Contribución al modelado y al análisis mediante Teoría de Juegos de la competencia entre operadores móviles en escenarios con tecnología "small cell" [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/8568

Resource Allocation for Multiple Access and Broadcast Channels under Quality of Service Requirements Based on Strategy Proof Pricing

The efficient allocation of power is a major concern in today’s wireless communications systems. Due to the high demand in data rate and the scarcity of wireless resources such as power, the multi-user communication systems like the multiple access channel (MAC) and broadcast channel (BC) have become highly competitive environments for the users as well as the system itself. Theory of microeconomics and game theory provide the good analytical manner for the selfish and social welfare conflict problems. Instead of maximizing the system sum rate, our proposed system deals with fulfilling the utility (rate) requirement of all the users with efficient power allocation. The users formulate the signal to interference-plus-noise ratio (SINR) based quality-of-service (QoS) requirements. We propose the framework to allocate the power to each user with universal pricing mechanisms. The prices act as the control signal and are assumed to be some virtual currency in the wireless system. They can influence the physical layer operating points to meet the desired utility requirements. Centralized and distributed power allocation frameworks are discussed separately in the thesis with different pricing schemes. In wireless systems we have users that are rational in the game theoretic sense of making decisions consistently in pursuit of their own individual objectives. Each user’s objective is to maximize the expected value of its own payoff measured on a certain utility scale. Selfishness or self-interest is an important implication of rationality. Therefore, the mobiles which share the same spectrum have incentives to misinterpret their private information in order to obtain more utility. They might behave selfishly and show also malicious behavior by creating increased interference for other mobiles. Therefore, it is important to supervise and influence the operation of the system by pricing and priority (weights) optimization. In the centralized resource allocation, we study the general MAC and BC (with linear and nonlinear receiver) with three types of agents: the regulator, the system optimizer and the mobile users. The regulator ensures the QoS requirements of all users by clever pricing and prevents cheating. The simple system optimizer solves a certain system utility maximization problem to allocate the power with the given prices and weights (priorities). The linear and nonlinear pricing mechanisms are analyzed, respectively. It is shown that linear pricing is a universal pricing only if successive interference cancellation (SIC) for uplink transmission or dirty paper coding (DPC) for downlink transmission is applied at the base station (BS). For MAC without SIC, nonlinear pricing which is logarithmic in power and linear in prices is a universal pricing scheme. The prices, the resulting cost terms, the optimal power allocation to achieve the QoS requirement of each user in the feasible rate region are derived in closed form solutions for MAC with and without SIC using linear and nonlinear pricing frameworks, respectively. The users are willing to maximize their achievable rate and minimize their cost on power by falsely reporting their channel state information (CSI). By predicting the best cheating strategy of the malicious users, the regulator is able to detect the misbehavior and punish the cheaters. The infinite repeated game (RG) is proposed as a counter mechanism with the trigger strategy using the trigger price. We show that by anticipating the total payoff of the proposed RG, the users have no incentive to cheat and therefore our framework is strategy-proof. In the distributed resource allocation, each user allocates its own power by optimizing the individual utility function. The noncooperative game among the users is formulated. The individual prices are introduced to the utility function of each user to shift the Nash equilibrium (NE) power allocation to the desired point. We show that by implicit control of the proposed prices, the best response (BR) power allocation of each user converges rapidly. The Shannon rate-based QoS requirement of each user is achieved with minimum power at the unique NE point. We analyse different behavior types of the users, especially the malicious behavior of misrepresenting the user utility function. The resulting NE power allocation and achievable rates of all users are derived when malicious behavior exists. The strategy-proof mechanism is designed using the punishment prices when the types of the malicious users are detected. The algorithm of the strategy-proof noncooperative game is proposed. We illustrate the convergence of the BR dynamic and the Price of Malice (PoM) by numerical simulations. The uplink transmission within the single cell of heterogeneous networks is exactly the same model as MAC. Therefore, the results of the pricing-based power allocation for MAC can be implemented into heterogeneous networks. Femtocells deployed in the Macrocell network provide better indoor coverage to the user equipments (UEs) with low power consumption and maintenance cost. The industrial vendors show great interest in the access mode, called the hybrid access, in which the macrocell UEs (MUEs) can be served by the nearby Femtocell Access Point (FAP). By adopting hybrid access in the femtocell, the system energy efficiency is improved due to the short distance between the FAP and MUEs while at the same time, the QoS requirements are better guaranteed. However, both the Macrocell base station (MBS) and the FAP are rational and selfish, who maximize their own utilities. The framework to successively apply the hybrid access in femtocell and fulfill the QoS requirement of each UE is important. We propose two novel compensation frameworks to motivate the hybrid access of femtocells. To save the energy consumption, the MBS is willing to motivate the FAP for hybrid access with compensation. The Stackelberg game is formulated where the MBS serves as the leader and the FAP serves as the follower. The MBS maximizes its utility by choosing the compensation prices. The FAP optimizes its utility by selecting the number of MUEs in hybrid access. By choosing the proper compensation price, the optimal number of MUEs served by the FAP to maximize the utility of the MBS coincides with that to maximize the utility of the FAP. Numerous simulation results are conducted, showing that the proposed compensation frameworks result in a win-win solution. In this thesis, based on game theory, mechanism design and pricing framework, efficient power allocation are proposed to guarantee the QoS requirements of all users in the wireless networks. The results are applicable in the multi-user systems such as heterogeneous networks. Both centralized and distributed allocation schemes are analyzed which are suitable for different communication scenarios.Aufgrund der hohen Nachfrage nach Datenrate und wegen der Knappheit an Ressourcen in Funknetzen ist die effiziente Allokation von Leistung ein wichtiges Thema in den heutigen Mehrnutzer-Kommunikationssystemen. Die Spieltheorie bietet Methoden, um egoistische und soziale Konfliktsituationen zu analysieren. Das vorgeschlagene System befasst sich mit der Erfüllung der auf Signal-zu-Rausch-und-Interferenz-Verhältnis (SINR) basierenden Quality-of-Service (QoS)-Anforderungen aller Nutzer mittels effizienter Leistungsallokation, anstatt die Übertragungsrate zu maximieren. Es wird ein Framework entworfen, um die Leistungsallokation mittels universellen Pricing-Mechanismen umzusetzen. In der Dissertation werden zentralisierte und verteilte Leistungsallokationsalgorithmen unter Verwendung verschiedener Pricing-Ansätze diskutiert. Die Nutzer in Funksystemen handeln rational im spieltheoretischen Sinne, indem sie ihre eigenen Nutzenfunktionen maximieren. Die mobilen Endgeräte, die dasselbe Spektrum nutzen, haben den Anreiz durch bewusste Fehlinterpretation ihrer privaten Informationen das eigene Ergebnis zu verbessern. Daher ist es wichtig, die Funktionalität des Systems zu überwachen und durch Optimierung des Pricings und Priorisierungsgewichte zu beeinflussen. Für den zentralisierten Ressourcenallokationsansatz werden der allgemeine Mehrfachzugriffskanal (Multiple Access Channel, MAC) und der Broadcastkanal (BC) mit linearen bzw. nichtlinearen Empfängern untersucht. Die Preise, die resultierenden Kostenterme und die optimale Leistungsallokation, mit der die QoS-Anforderungen in der zulässigen Ratenregion erfüllt werden, werden in geschlossener Form hergeleitet. Lineare und nichtlineare Pricing-Ansätze werden separat diskutiert. Das unendlich oft wiederholte Spiel wird vorgeschlagen, um Spieler vom Betrügen durch Übermittlung falscher Kanalinformationen abzuhalten. Für die verteilten Ressourcenvergabe wird das nichtkooperative Spiel in Normalform verwendet und formuliert. Die Nutzer wählen ihre Sendeleistung zur Maximierung ihrer eigenen Nutzenfunktion. Individuelle Preise werden eingeführt und so angepasst, dass die QoS-Anforderungen mit der Leistungsallokation im eindeutigen Nash-Gleichgewicht erfüllt werden. Verschiedene Arten des Nutzerverhaltens werden bezüglich der Täuschung ihrer Nutzenfunktion analysiert, und ein Strategy-Proof-Mechanismus mit Strafen wird entwickelt. Die Ergebnisse für den MAC sind anwendbar auf heterogene Netzwerke, wobei zwei neuartige Ansätze zur Kompensation bereitgestellt werden, die den hybriden Zugang zu Femtozell-Netzwerken motivieren. Mithilfe des Stackelberg-Spiels wird gezeigt, dass die vorgeschlagenen Ansätze in einer Win-Win-Situation resultieren