1,122 research outputs found

    Applications of Repeated Games in Wireless Networks: A Survey

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    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

    A Study of Problems Modelled as Network Equilibrium Flows

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    This thesis presents an investigation into selfish routing games from three main perspectives. These three areas are tied together by a common thread that runs through the main text of this thesis, namely selfish routing games and network equilibrium flows. First, it investigates methods and models for nonatomic selfish routing and then develops algorithms for solving atomic selfish routing games. A number of algorithms are introduced for the atomic selfish routing problem, including dynamic programming for a parallel network and a metaheuristic tabu search. A piece-wise mixed-integer linear programming problem is also presented which allows standard solvers to solve the atomic selfish routing problem. The connection between the atomic selfish routing problem, mixed-integer linear programming and the multicommodity flow problem is explored when constrained by unsplittable flows or flows that are restricted to a number of paths. Additionally, some novel probabilistic online learning algorithms are presented and compared with the equilibrium solution given by the potential function of the nonatomic selfish routing game. Second, it considers multi-criteria extensions of selfish routing and the inefficiency of the equilibrium solutions when compared with social cost. Models are presented that allow exploration of the Pareto set of solutions for a weighted sum model (akin to the social cost) and the equilibrium solution. A means by which these solutions can be measured based on the Price of Anarchy for selfish routing games is also presented. Third, it considers the importance and criticality of components of the network (edges, vertices or a collection of both) within a selfish routing game and the impact of their removal. Existing network science measures and demand-based measures are analysed to assess the change in total travel time and issues highlighted. A new measure which solves these issues is presented and the need for such a measure is evaluated. Most of the new findings have been disseminated through conference talks and journal articles, while others represent the subject of papers currently in preparation

    Improving Approximate Pure Nash Equilibria in Congestion Games

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    Congestion games constitute an important class of games to model resource allocation by different users. As computing an exact or even an approximate pure Nash equilibrium is in general PLS-complete, Caragiannis et al. (2011) present a polynomial-time algorithm that computes a (2+ϵ2 + \epsilon)-approximate pure Nash equilibria for games with linear cost functions and further results for polynomial cost functions. We show that this factor can be improved to (1.61+ϵ)(1.61+\epsilon) and further improved results for polynomial cost functions, by a seemingly simple modification to their algorithm by allowing for the cost functions used during the best response dynamics be different from the overall objective function. Interestingly, our modification to the algorithm also extends to efficiently computing improved approximate pure Nash equilibria in games with arbitrary non-decreasing resource cost functions. Additionally, our analysis exhibits an interesting method to optimally compute universal load dependent taxes and using linear programming duality prove tight bounds on PoA under universal taxation, e.g, 2.012 for linear congestion games and further results for polynomial cost functions. Although our approach yield weaker results than that in Bil\`{o} and Vinci (2016), we remark that our cost functions are locally computable and in contrast to Bil\`{o} and Vinci (2016) are independent of the actual instance of the game

    Challenges in Blockchain as a Solution for IoT Ecosystem Threats and Access Control: A Survey

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    The Internet of Things (IoT) is increasingly influencing and transforming various aspects of our daily lives. Contrary to popular belief, it raises security and privacy issues as it is used to collect data from consumers or automated systems. Numerous articles are published that discuss issues like centralised control systems and potential alternatives like integration with blockchain. Although a few recent surveys focused on the challenges and solutions facing the IoT ecosystem, most of them did not concentrate on the threats, difficulties, or blockchain-based solutions. Additionally, none of them focused on blockchain and IoT integration challenges and attacks. In the context of the IoT ecosystem, overall security measures are very important to understand the overall challenges. This article summarises difficulties that have been outlined in numerous recent articles and articulates various attacks and security challenges in a variety of approaches, including blockchain-based solutions and so on. More clearly, this contribution consolidates threats, access control issues, and remedies in brief. In addition, this research has listed some attacks on public blockchain protocols with some real-life examples that can guide researchers in taking preventive measures for IoT use cases. Finally, a future research direction concludes the research gaps by analysing contemporary research contributions

    Distributed, decentralised and compensational mechanisms for platoon formation

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    Verkehrsprobleme nehmen mit der weltweiten Urbanisierung und der Zunahme der Anzahl der Fahrzeuge pro Kopf zu. Platoons, eine Formation von eng hintereinander fahrenden Fahrzeugen, stellen sich als mögliche Lösung dar, da bestehende Forschungen darauf hinweisen, dass sie zu einer besseren Straßenauslastung beitragen, den Kraftstoffverbrauch und die Emissionen reduzieren und Engpässe schneller entlasten können. Rund um das Thema Platooning gibt es viele Aspekte zu erforschen: Sicherheit, Stabilität, Kommunikation, Steuerung und Betrieb, die allesamt notwendig sind, um den Einsatz von Platooning im Alltagsverkehr näher zu bringen. Während in allen genannten Bereichen bereits umfangreiche Forschungen durchgeführt wurden, gibt es bisher nur wenige Arbeiten, die sich mit der logischen Gruppierung von Fahrzeugen in Platoons beschäftigen. Daher befasst sich diese Arbeit mit dem noch wenig erforschten Problem der Platoonbildung, wobei sich die vorhandenen Beispiele mit auf Autobahnen fahrenden Lastkraftwagen beschäftigen. Diese Fälle befinden sich auf der strategischen und taktischen Ebene der Planung, da sie von einem großen Zeithorizont profitieren und die Gruppierung entsprechend optimiert werden kann. Die hier vorgestellten Ansätze befinden sich hingegen auf der operativen Ebene, indem Fahrzeuge aufgrund der verteilten und dezentralen Natur dieser Ansätze spontan und organisch gruppiert und gesteuert werden. Dadurch entstehen sogenannte opportunistische Platoons, die aufgrund ihrer Flexibilität eine vielversprechende Voraussetzung für alle Netzwerkarte bieten könnten. Insofern werden in dieser Arbeit zwei neuartige Algorithmen zur Bildung von Platoons vorgestellt: ein verteilter Ansatz, der von klassischen Routing-Problemen abgeleitet wurde, und ein ergänzender dezentraler kompensatorischer Ansatz. Letzteres nutzt automatisierte Verhandlungen, um es den Fahrzeugen zu erleichtern, sich auf der Basis eines monetären Austausches in einem Platoon zu organisieren. In Anbetracht der Tatsache, dass alle Verkehrsteilnehmer über eine Reihe von Präferenzen, Einschränkungen und Zielen verfügen, muss das vorgeschlagene System sicherstellen, dass jede angebotene Lösung für die einzelnen Fahrzeuge akzeptabel und vorteilhaft ist und den möglichen Aufwand, die Kosten und die Opfer überwiegt. Dies wird erreicht, indem den Platooning-Fahrzeugen eine Form von Anreiz geboten wird, im Sinne von entweder Kostensenkung oder Ampelpriorisierung. Um die vorgeschlagenen Algorithmen zu testen, wurde eine Verkehrssimulation unter Verwendung realer Netzwerke mit realistischer Verkehrsnachfrage entwickelt. Die Verkehrsteilnehmer wurden in Agenten umgewandelt und mit der notwendigen Funktionalität ausgestattet, um Platoons zu bilden und innerhalb dieser zu operieren. Die Anwendbarkeit und Eignung beider Ansätze wurde zusammen mit verschiedenen anderen Aspekten untersucht, die den Betrieb von Platoons betreffen, wie Größe, Verkehrszustand, Netzwerkpositionierung und Anreizmethoden. Die Ergebnisse zeigen, dass die vorgeschlagenen Mechanismen die Bildung von spontanen Platoons ermöglichen. Darüber hinaus profitierten die teilnehmenden Fahrzeuge mit dem auf verteilter Optimierung basierenden Ansatz und unter Verwendung kostensenkender Anreize unabhängig von der Platoon-Größe, dem Verkehrszustand und der Positionierung, mit Nutzenverbesserungen von 20% bis über 50% im Vergleich zur untersuchten Baseline. Bei zeitbasierten Anreizen waren die Ergebnisse uneinheitlich, wobei sich der Nutzen einiger Fahrzeuge verbesserte, bei einigen keine Veränderung eintrat und bei anderen eine Verschlechterung zu verzeichnen war. Daher wird die Verwendung solcher Anreize aufgrund ihrer mangelnden Pareto-Effizienz nicht empfohlen. Der kompensatorische und vollständig dezentralisierte Ansatz weißt einige Vorteile auf, aber die daraus resultierende Verbesserung war insgesamt vernachlässigbar. Die vorgestellten Mechanismen stellen einen neuartigen Ansatz zur Bildung von Platoons dar und geben einen aussagekräftigen Einblick in die Mechanik und Anwendbarkeit von Platoons. Dies schafft die Voraussetzungen für zukünftige Erweiterungen in der Planung, Konzeption und Implementierung effektiverer Infrastrukturen und Verkehrssysteme.Traffic problems have been on the rise corresponding with the increase in worldwide urbanisation and the number of vehicles per capita. Platoons, which are a formation of vehicles travelling close together, present themselves as a possible solution, as existing research indicates that they can contribute to better road usage, reduce fuel consumption and emissions and decongest bottlenecks faster. There are many aspects to be explored pertaining to the topic of platooning: safety, stability, communication, controllers and operations, all of which are necessary to bring platoons closer to use in everyday traffic. While extensive research has already made substantial strides in all the aforementioned fields, there is so far little work on the logical grouping of vehicles in platoons. Therefore, this work addresses the platoon formation problem, which has not been heavily researched, with existing examples being focused on large, freight vehicles travelling on highways. These cases find themselves on the strategic and tactical level of planning since they benefit from a large time horizon and the grouping can be optimised accordingly. The approaches presented here, however, are on the operational level, grouping and routing vehicles spontaneously and organically thanks to their distributed and decentralised nature. This creates so-called opportunistic platoons which could provide a promising premise for all networks given their flexibility. To this extent, this thesis presents two novel platoon forming algorithms: a distributed approach derived from classical routing problems, and a supplementary decentralised compensational approach. The latter uses automated negotiation to facilitate vehicles organising themselves in a platoon based on monetary exchanges. Considering that all traffic participants have a set of preferences, limitations and goals, the proposed system must ensure that any solution provided is acceptable and beneficial for the individual vehicles, outweighing any potential effort, cost and sacrifices. This is achieved by offering platooning vehicles some form of incentivisation, either cost reductions or traffic light prioritisation. To test the proposed algorithms, a traffic simulation was developed using real networks with realistic traffic demand. The traffic participants were transformed into agents and given the necessary functionality to build platoons and operate within them. The applicability and suitability of both approaches were investigated along with several other aspects pertaining to platoon operations such as size, traffic state, network positioning and incentivisation methods. The results indicate that the mechanisms proposed allow for spontaneous platoons to be created. Moreover, with the distributed optimisation-based approach and using cost-reducing incentives, participating vehicles benefited regardless of the platoon size, traffic state and positioning, with utility improvements ranging from 20% to over 50% compared to the studied baseline. For time-based incentives the results were mixed, with the utility of some vehicles improving, some seeing no change and for others, deteriorating. Therefore, the usage of such incentives would not be recommended due to their lack of Pareto-efficiency. The compensational and completely decentralised approach shows some benefits, but the resulting improvement was overall negligible. The presented mechanisms are a novel approach to platoon formation and provide meaningful insight into the mechanics and applicability of platoons. This sets the stage for future expansions into planning, designing and implementing more effective infrastructures and traffic systems
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