Applications of Repeated Games in Wireless Networks: A Survey

A repeated game is an effective tool to model interactions and conflicts for players aiming to achieve their objectives in a long-term basis. Contrary to static noncooperative games that model an interaction among players in only one period, in repeated games, interactions of players repeat for multiple periods; and thus the players become aware of other players' past behaviors and their future benefits, and will adapt their behavior accordingly. In wireless networks, conflicts among wireless nodes can lead to selfish behaviors, resulting in poor network performances and detrimental individual payoffs. In this paper, we survey the applications of repeated games in different wireless networks. The main goal is to demonstrate the use of repeated games to encourage wireless nodes to cooperate, thereby improving network performances and avoiding network disruption due to selfish behaviors. Furthermore, various problems in wireless networks and variations of repeated game models together with the corresponding solutions are discussed in this survey. Finally, we outline some open issues and future research directions.Comment: 32 pages, 15 figures, 5 tables, 168 reference

Wireless Powered Sensor Networks for Internet of Things: Maximum Throughput and Optimal Power Allocation

This paper investigates a wireless powered sensor network (WPSN), where multiple sensor nodes are deployed to monitor a certain external environment. A multi-antenna power station (PS) provides the power to these sensor nodes during wireless energy transfer (WET) phase, and consequently the sensor nodes employ the harvested energy to transmit their own monitoring information to a fusion center (FC) during wireless information transfer (WIT) phase. The goal is to maximize the system sum throughput of the sensor network, where two different scenarios are considered, i.e., PS and the sensor nodes belong to the same or different service operator(s). For the first scenario, we propose a global optimal solution to jointly design the energy beamforming and time allocation. We further develop a closed-form solution for the proposed sum throughput maximization. For the second scenario in which the PS and the sensor nodes belong to different service operators, energy incentives are required for the PS to assist the sensor network. Specifically, the sensor network needs to pay in order to purchase the energy services released from the PS to support WIT. In this case, the paper exploits this hierarchical energy interaction, which is known as energy trading. We propose a quadratic energy trading based Stackelberg game, linear energy trading based Stackelberg game, and social welfare scheme, in which we derive the Stackelberg equilibrium for the formulated games, and the optimal solution for the social welfare scheme. Finally, numerical results are provided to validate the performance of our proposed schemes

Security, trust and cooperation in wireless sensor networks

Wireless sensor networks are a promising technology for many real-world applications such as critical infrastructure monitoring, scientific data gathering, smart buildings, etc.. However, given the typically unattended and potentially unsecured operation environment, there has been an increased number of security threats to sensor networks. In addition, sensor networks have very constrained resources, such as limited energy, memory, computational power, and communication bandwidth. These unique challenges call for new security mechanisms and algorithms. In this dissertation, we propose novel algorithms and models to address some important and challenging security problems in wireless sensor networks. The first part of the dissertation focuses on data trust in sensor networks. Since sensor networks are mainly deployed to monitor events and report data, the quality of received data must be ensured in order to make meaningful inferences from sensor data. We first study a false data injection attack in the distributed state estimation problem and propose a distributed Bayesian detection algorithm, which could maintain correct estimation results when less than one half of the sensors are compromised. To deal with the situation where more than one half of the sensors may be compromised, we introduce a special class of sensor nodes called \textit{trusted cores}. We then design a secure distributed trust aggregation algorithm that can utilize the trusted cores to improve network robustness. We show that as long as there exist some paths that can connect each regular node to one of these trusted cores, the network can not be subverted by attackers. The second part of the dissertation focuses on sensor network monitoring and anomaly detection. A sensor network may suffer from system failures due to loss of links and nodes, or malicious intrusions. Therefore, it is critical to continuously monitor the overall state of the network and locate performance anomalies. The network monitoring and probe selection problem is formulated as a budgeted coverage problem and a Markov decision process. Efficient probing strategies are designed to achieve a flexible tradeoff between inference accuracy and probing overhead. Based on the probing results on traffic measurements, anomaly detection can be conducted. To capture the highly dynamic network traffic, we develop a detection scheme based on multi-scale analysis of the traffic using wavelet transforms and hidden Markov models. The performance of the probing strategy and of the detection scheme are extensively evaluated in malicious scenarios using the NS-2 network simulator. Lastly, to better understand the role of trust in sensor networks, a game theoretic model is formulated to mathematically analyze the relation between trust and cooperation. Given the trust relations, the interactions among nodes are modeled as a network game on a trust-weighted graph. We then propose an efficient heuristic method that explores network heterogeneity to improve Nash equilibrium efficiency

Optimization of positioning capabilities in wireless sensor networks : from power efficiency to medium access

In Wireless Sensor Networks (WSN), the ability of sensor nodes to know its position is an enabler for a wide variety of applications for monitoring, control, and automation. Often, sensor data is meaningful only if its position can be determined. Many WSN are deployed indoors or in areas where Global Navigation Satellite System (GNSS) signal coverage is not available, and thus GNSS positioning cannot be guaranteed. In these scenarios, WSN may be relied upon to achieve a satisfactory degree of positioning accuracy. Typically, batteries power sensor nodes in WSN. These batteries are costly to replace. Therefore, power consumption is an important aspect, being performance and lifetime of WSN strongly relying on the ability to reduce it. It is crucial to design effective strategies to maximize battery lifetime. Optimization of power consumption can be made at different layers. For example, at the physical layer, power control and resource optimization may play an important role, as well as at higher layers through network topology and MAC protocols. The objective of this Thesis is to study the optimization of resources in WSN that are employed for positioning purposes, with the ultimate goal being the minimization of power consumption. We focus on anchor-based positioning, where a subset of the WSN nodes know their location (anchors) and send ranging signals to nodes with unknown position (targets) to assist them in estimating it through distance-related measurements. Two well known of such measurements are received signal strength (RSS) and time of arrival (TOA), in which this Thesis focuses. In order to minimize power consumption while providing a certain quality of positioning service, in this dissertation we research on the problems of power control and node selection. Aiming at a distributed implementation of the proposed techniques, we resort to the tools of non-cooperative game theory. First, transmit power allocation is addressed for RSS based ranging. Using game theory formulation, we develop a potential game leading to an iterated best response algorithm with sure convergence. As a performance metric, we introduce the geometric dilution of precision (GDOP), which is shown to help achieving a suitable geometry of the selected anchor nodes. The proposed scheme and relative distributed algorithms provide good equilibrium performance in both static and dynamic scenarios. Moreover, we present a distributed, low complexity implementation and analyze it in terms of computational complexity. Results show that performance close to that of exhaustive search is possible. We then address the transmit power allocation problem for TOA based ranging, also resorting to a game theoretic formulation. In this setup, and also considering GDOP as performance metric, a supermodular game formulation is proposed, along with a distributed algorithm with guaranteed convergence to a unique solution, based on iterated best response. We analyze the proposed algorithm in terms of the price of anarchy (PoA), that is, compared to a centralized optimum solution, and shown to have a moderate performance loss. Finally, this dissertation addresses the effect of different MAC protocols and topologies in the positioning performance. In this direction, we study the performance of mesh and cluster-tree topologies defined in WSN standards. Different topologies place different constraints in network connectivity, having a substantial impact on the performance of positioning algorithms. While mesh topology allows high connectivity with large energy consumption, cluster-tree topologies are more energy efficient but suffer from reduced connectivity and poor positioning performance. In order to improve the performance of cluster-tree topologies, we propose a cluster formation algorithm. It significantly improves connectivity with anchor nodes, achieving vastly improved positioning performance.En les xarxes de sensors sense fils (WSN), l'habilitat dels nodes sensors per conèixer la seva posició facilita una gran varietat d'aplicacions per la monitorització, el control i l'automatització. Així, les dades que proporciona un sensor tenen sentit només si la posició pot ésser determinada. Moltes WSN són desplegades en interiors o en àrees on la senyal de sistemes globals de navegació per satèl.lit (GNSS) no té prou cobertura, i per tant, el posicionament basat en GNSS no pot ésser garantitzat. En aquests escenaris, les WSN poden proporcionar una bona precisió en posicionament. Normalment, en WSN els nodes són alimentats amb bateries. Aquestes bateries són difícils de reemplaçar. Per tant, el consum de potència és un aspecte important i és crucial dissenyar estratègies efectives per maximitzar el temps de vida de la bateria. L'optimització del consum de potència pot ser fet a diferents capes del protocol. Per exemple, en la capa física, el control de potència i l'optimització dels recursos juguen un rol important, igualment que la topologia de xarxa i els protocols MAC en les capes més altes. L'objectiu d'aquesta tesi és estudiar l¿optimització de recursos en WSN que s'utilitzen per fer posicionament, amb el propòsit de minimitzar el consum de potència. Ens focalitzem en el posicionament basat en àncora, en el qual un conjunt de nodes coneixen la seva localització (nodes àncora) i envien missatges als nodes que no saben la seva posició per ajudar-los a estimar les seves coordenades amb mesures de distància. Dues classes de mesures són la potència de la senyal rebuda (RSS) i el temps d'arribada (TOA) en les quals aquesta tesi està focalitzada. Per minimitzar el consum de potència mentre que es proporciona suficient qualitat en el posicionament, en aquesta tesi estudiem els problemes de control de potència i selecció de nodes. Tenint en compte una implementació distribuïda de les tècniques proposades, utilitzem eïnes de teoria de jocs no cooperatius. Primer, l'assignació de potència transmesa és abordada pel càlcul de la distància amb RSS. Utilitzant la teoria de jocs, desenvolupem un joc potencial que convergeix amb un algoritme iteratiu basat en millor resposta (best response). Com a mètrica d'error, introduïm la dilució de la precisió geomètrica (GDOP) que mostra quant d'apropiada és la geometria dels nodes àncora seleccionats. L'esquema proposat i els algoritmes distribuïts proporcionen una bona resolució de l'equilibri en l'escenari estàtic i dinàmic. Altrament, presentem una implementació distribuïda i analitzem la seva complexitat computacional. Els resultats obtinguts són similars als obtinguts amb un algoritme de cerca exhaustiva. El problema d'assignació de la potència transmesa en el càlcul de la distància basat en TOA, també és tractat amb teoria de jocs. En aquest cas, considerant el GDOP com a mètrica d'error, proposem un joc supermodular juntament amb un algoritme distribuït basat en millor resposta amb convergència garantida cap a una única solució. Analitzem la solució proposada amb el preu de l'anarquia (PoA), és a dir, es compara la nostra solució amb una solució òptima centralitzada mostrant que les pèrdues són moderades. Finalment, aquesta tesi tracta l'efecte que causen diferents protocols MAC i topologies en el posicionament. En aquesta direcció, estudiem les topologies de malla i arbre formant clusters (cluster-tree) que estan definides als estàndards de les WSN. La diferència entre les topologies crea diferents restriccions en la connectivitat de la xarxa, afectant els resultats de posicionament. La topologia de malla permet una elevada connectivitat entre els nodes amb gran consum d'energia, mentre que les topologies d'arbre són més energèticament eficients però amb baixa connectivitat entre els nodes i baix rendiment pel posicionament. Per millorar la qualitat del posicionament en les topologies d'arbre, proposem un algoritme de formació de clústers.Postprint (published version

Game-Theoretic Relay Selection and Power Control in Fading Wireless Body Area Networks

The trend towards personalized ubiquitous computing has led to the advent of a new generation of wireless technologies, namely wireless body area networks (WBANs), which connect the wearable devices into the Internet-of-Things. This thesis considers the problems of relay selection and power control in fading WBANs with energy-efficiency and security considerations. The main body of the thesis is formed by two papers. Ideas from probability theory are used, in the first paper, to construct a performance measure signifying the energy efficiency of transmission, while in the second paper, information-theoretic principles are leveraged to characterize the transmission secrecy at the wireless physical layer (PHY). The hypothesis is that exploiting spatial diversity through multi-hop relaying is an effective strategy in a WBAN to combat fading and enhance communication throughput. In order to analytically explore the problems of optimal relay selection and power control, proper tools from game theory are employed. In particular, non-cooperative game-theoretic frameworks are developed to model and analyze the strategic interactions among sensor nodes in a WBAN when seeking to optimize their transmissions in the uplink. Quality-of-service requirements are also incorporated into the game frameworks, in terms of upper bounds on the end-to-end delay and jitter incurred by multi-hop transmission, by borrowing relevant tools from queuing theory. The proposed game frameworks are proved to admit Nash equilibria, and distributed algorithms are devised that converge to stable Nash solutions. The frameworks are then evaluated using numerical simulations in conditions approximating actual deployment of WBANs. Performance behavior trade-offs are investigated in an IEEE 802.15.6-based ultra wideband WBAN considering various scenarios. The frameworks show remarkable promise in improving the energy efficiency and PHY secrecy of transmission, at the expense of an admissible increase in the end-to-end latency

Optimality of Event-Based Policies for Decentralized Estimation over Shared Networks

Cyber-physical systems often consist of multiple non-collocated components that sense, exchange information and act as a team through a network. Although this new paradigm provides convenience, flexibility and robustness to modern systems, design methods to achieve optimal performance are elusive as they must account for certain detrimental characteristics of the underlying network. These include constrained connectivity among agents, rate-limited communication links, physical noise at the antennas, packet drops and interference. We propose a new class of problems in optimal networked estimation where multiple sensors operating as a team communicate their measurements to a fusion center over an interference prone network modeled by a collision channel. Using a team decision theoretic approach, we characterize jointly optimal communication policies for one-shot problems under different performance criteria. First we study the problem of estimating two independent continuous random variables observed by two different sensors communicating with a fusion center over a collision channel. For a minimum mean squared estimation error criterion, we show that there exist team-optimal strategies where each sensor uses a threshold policy. This result is independent of the distribution of the observations and, can be extended to vector observations and to any number of sensors. Consequently, the existence of team-optimal threshold policies is a result of practical significance, because it can be applied to a wide class of systems without requiring collision avoidance protocols. Next we study the problem of estimating independent discrete random variables over a collision channel. Using two different criteria involving the probability of estimation error, we show the existence of team-optimal strategies where the sensors either transmit all but the most likely observation; transmit only the second most likely observation; or remain always silent. These results are also independent of the distributions and are valid for any number of sensors. In our analysis, the proof of the structural result involves the minimization of a concave functional, which is an evidence of the inherent complexity of team decision problems with nonclassical information structure. In the last part of the dissertation, the assumption on the cooperation among sensors is relaxed, and we show that similar structural results can also be obtained for systems with one or more selfish sensors. Finally the assumption of the independence is lifted by introducing the observation of a common random variable in addition to the private observations of each sensor. The structural result obtained provides valuable insights on the characterization of team-optimal policies for a general correlation structure between the observed random variables

Channel Access in Wireless Networks: Protocol Design of Energy-Aware Schemes for the IoT and Analysis of Existing Technologies

The design of channel access policies has been an object of study since the deployment of the first wireless networks, as the Medium Access Control (MAC) layer is responsible for coordinating transmissions to a shared channel and plays a key role in the network performance. While the original target was the system throughput, over the years the focus switched to communication latency, Quality of Service (QoS) guarantees, energy consumption, spectrum efficiency, and any combination of such goals. The basic mechanisms to use a shared channel, such as ALOHA, TDMA- and FDMA-based policies, have been introduced decades ago. Nonetheless, the continuous evolution of wireless networks and the emergence of new communication paradigms demand the development of new strategies to adapt and optimize the standard approaches so as to satisfy the requirements of applications and devices. This thesis proposes several channel access schemes for novel wireless technologies, in particular Internet of Things (IoT) networks, the Long-Term Evolution (LTE) cellular standard, and mmWave communication with the IEEE802.11ad standard. The first part of the thesis concerns energy-aware channel access policies for IoT networks, which typically include several battery-powered sensors. In scenarios with energy restrictions, traditional protocols that do not consider the energy consumption may lead to the premature death of the network and unreliable performance expectations. The proposed schemes show the importance of accurately characterizing all the sources of energy consumption (and inflow, in the case of energy harvesting), which need to be included in the protocol design. In particular, the schemes presented in this thesis exploit data processing and compression techniques to trade off QoS for lifetime. We investigate contention-free and contention-based chanel access policies for different scenarios and application requirements. While the energy-aware schemes proposed for IoT networks are based on a clean-slate approach that is agnostic of the communication technology used, the second part of the thesis is focused on the LTE and IEEE802.11ad standards. As regards LTE, the study proposed in this thesis shows how to use machine-learning techniques to infer the collision multiplicity in the channel access phase, information that can be used to understand when the network is congested and improve the contention resolution mechanism. This is especially useful for massive access scenarios; in the last years, in fact, the research community has been investigating on the use of LTE for Machine-Type Communication (MTC). As regards the standard IEEE802.11ad, instead, it provides a hybrid MAC layer with contention-based and contention-free scheduled allocations, and a dynamic channel time allocation mechanism built on top of such schedule. Although this hybrid scheme is expected to meet heterogeneous requirements, it is still not clear how to develop a schedule based on the various traffic flows and their demands. A mathematical model is necessary to understand the performance and limits of the possible types of allocations and guide the scheduling process. In this thesis, we propose a model for the contention-based access periods which is aware of the interleaving of the available channel time with contention-free allocations