Game Theory Relaunched

The game is on. Do you know how to play? Game theory sets out to explore what can be said about making decisions which go beyond accepting the rules of a game. Since 1942, a well elaborated mathematical apparatus has been developed to do so; but there is more. During the last three decades game theoretic reasoning has popped up in many other fields as well - from engineering to biology and psychology. New simulation tools and network analysis have made game theory omnipresent these days. This book collects recent research papers in game theory, which come from diverse scientific communities all across the world; they combine many different fields like economics, politics, history, engineering, mathematics, physics, and psychology. All of them have as a common denominator some method of game theory. Enjoy

Reorganization in network regions for optimality and fairness

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.Includes bibliographical references (p. 92-95).(cont.) down implicit assumptions of altruism while showing the resulting negative impact on utility. From a selfish equilibrium, with much lower global utility, we show the ability of our algorithm to reorganize and restore the utility of individual nodes, and the system as a whole, to similar levels as realized in the SuperPeer network. Simulation of our algorithm shows that it reaches the predicted optimal utility while providing fairness not realized in other systems. Further analysis includes an epsilon equilibrium model where we attempt to more accurately represent the actual reward function of nodes. We find that by employing such a model, over 60% of the nodes are connected. In addition, this model converges to a utility 34% greater than achieved in the SuperPeer network while making no assumptions on the benevolence of nodes or centralized organization.This thesis proposes a reorganization algorithm, based on the region abstraction, to exploit the natural structure in overlays that stems from common interests. Nodes selfishly adapt their connectivity within the overlay in a distributed fashion such that the topology evolves to clusters of users with shared interests. Our architecture leverages the inherent heterogeneity of users and places within the system their incentives and ability to affect the network. As such, it is not dependent on the altruism of any other nodes in the system. Of particular interest is the optimality and fairness of our design. We rigorously define ideal and fair networks and develop a continuum of optimality measures by which to evaluate our algorithm. Further, to evaluate our algorithm within a realistic context, validate assumptions and make design decisions, we capture data from a portion of a live file-sharing network. More importantly, we discover, name, quantify and solve several previously unrecognized subtle problems in a content-based self-organizing network as a direct result of simulations using the trace data. We motivate our design by examining the dependence of existing systems on benevolent Super-Peers. Through simulation we find that the current architecture is highly dependent on the filtering capability and the willingness of the SuperPeer network to absorb the majority of the query burden. The remainder of the thesis is devoted to a world in which SuperPeers no longer exist or are untenable. In our evaluation, we introduce four reasons for utility suboptimal self-reorganizing networks: anarchy (selfish behavior), indifference, myopia and ordering. We simulate the level of utility and happiness achieved in existing architectures. Then we systematically tearby Robert E. Beverly, IV.S.M

Resource allocation in networks via coalitional games

The main goal of this dissertation is to manage resource allocation in network engineering problems and to introduce efficient cooperative algorithms to obtain high performance, ensuring fairness and stability. Specifically, this dissertation introduces new approaches for resource allocation in Orthogonal Frequency Division Multiple Access (OFDMA) wireless networks and in smart power grids by casting the problems to the coalitional game framework and by providing a constructive iterative algorithm based on dynamic learning theory.  Software Engineering (Software)Algorithms and the Foundations of Software technolog

Enabling sustainable power distribution networks by using smart grid communications

Smart grid modernization enables integration of computing, information and communications capabilities into the legacy electric power grid system, especially the low voltage distribution networks where various consumers are located. The evolutionary paradigm has initiated worldwide deployment of an enormous number of smart meters as well as renewable energy sources at end-user levels. The future distribution networks as part of advanced metering infrastructure (AMI) will involve decentralized power control operations under associated smart grid communications networks. This dissertation addresses three potential problems anticipated in the future distribution networks of smart grid: 1) local power congestion due to power surpluses produced by PV solar units in a neighborhood that demands disconnection/reconnection mechanisms to alleviate power overflow, 2) power balance associated with renewable energy utilization as well as data traffic across a multi-layered distribution network that requires decentralized designs to facilitate power control as well as communications, and 3) a breach of data integrity attributed to a typical false data injection attack in a smart metering network that calls for a hybrid intrusion detection system to detect anomalous/malicious activities. In the first problem, a model for the disconnection process via smart metering communications between smart meters and the utility control center is proposed. By modeling the power surplus congestion issue as a knapsack problem, greedy solutions for solving such problem are proposed. Simulation results and analysis show that computation time and data traffic under a disconnection stage in the network can be reduced. In the second problem, autonomous distribution networks are designed that take scalability into account by dividing the legacy distribution network into a set of subnetworks. A power-control method is proposed to tackle the power flow and power balance issues. Meanwhile, an overlay multi-tier communications infrastructure for the underlying power network is proposed to analyze the traffic of data information and control messages required for the associated power flow operations. Simulation results and analysis show that utilization of renewable energy production can be improved, and at the same time data traffic reduction under decentralized operations can be achieved as compared to legacy centralized management. In the third problem, an attack model is proposed that aims to minimize the number of compromised meters subject to the equality of an aggregated power load in order to bypass detection under the conventionally radial tree-like distribution network. A hybrid anomaly detection framework is developed, which incorporates the proposed grid sensor placement algorithm with the observability attribute. Simulation results and analysis show that the network observability as well as detection accuracy can be improved by utilizing grid-placed sensors. Conclusively, a number of future works have also been identified to furthering the associated problems and proposed solutions

Dynamic resource allocation games

In resource allocation games, selfish players share resources that are needed in order to fulfill their objectives. The cost of using a resource depends on the load on it. In the traditional setting, the players make their choices concurrently and in one-shot. That is, a strategy for a player is a subset of the resources. We introduce and study dynamic resource allocation games. In this setting, the game proceeds in phases. In each phase each player chooses one resource. A scheduler dictates the order in which the players proceed in a phase, possibly scheduling several players to proceed concurrently. The game ends when each player has collected a set of resources that fulfills his objective. The cost for each player then depends on this set as well as on the load on the resources in it – we consider both congestion and cost-sharing games. We argue that the dynamic setting is the suitable setting for many applications in practice. We study the stability of dynamic resource allocation games, where the appropriate notion of stability is that of subgame perfect equilibrium, study the inefficiency incurred due to selfish behavior, and also study problems that are particular to the dynamic setting, like constraints on the order in which resources can be chosen or the problem of finding a scheduler that achieves stability

Smart Wireless Sensor Networks

The recent development of communication and sensor technology results in the growth of a new attractive and challenging area - wireless sensor networks (WSNs). A wireless sensor network which consists of a large number of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with the ability of wireless communication and intelligent computation, these nodes become smart sensors which do not only perceive ambient physical parameters but also be able to process information, cooperate with each other and self-organize into the network. These new features assist the sensor nodes as well as the network to operate more efficiently in terms of both data acquisition and energy consumption. Special purposes of the applications require design and operation of WSNs different from conventional networks such as the internet. The network design must take into account of the objectives of specific applications. The nature of deployed environment must be considered. The limited of sensor nodes� resources such as memory, computational ability, communication bandwidth and energy source are the challenges in network design. A smart wireless sensor network must be able to deal with these constraints as well as to guarantee the connectivity, coverage, reliability and security of network's operation for a maximized lifetime. This book discusses various aspects of designing such smart wireless sensor networks. Main topics includes: design methodologies, network protocols and algorithms, quality of service management, coverage optimization, time synchronization and security techniques for sensor networks

The role of topology and contracts in internet content delivery

The Internet depends on economic relationships between ASes (Autonomous Systems), which come in different shapes and sizes - transit, content, and access networks. CDNs (Content delivery networks) are also a pivotal part of the Internet ecosystem and construct their overlays for faster content delivery. With the evolving Internet topology and traffic growth, there is a need to study the cache deployments of CDNs to optimize cost while meeting performance requirements. The bilateral contracts enforce the routing of traffic between neighbouring ASes and are applied recursively: traffic that an AS sends to its neighbour is then controlled by the contracts of that neighbour. The lack of routing flexibility, little control over the quality of the end-to-end path are some of the limitations with the existing bilateral model, and they need to be overcome for achieving end-to-end performance guarantees. Furthermore, due to general reluctance of ASes to disclose their interconnection agreements, inference of inter-AS economic relationships depend on routing and forwarding data from measurements. Since the inferences are imperfect, this necessitates building robust algorithmic strategies to characterize ASes with a significantly higher accuracy. In this thesis, we first study the problem of optimizing multi-AS deployments of CDN caches in the Internet core. Our work is of significant practical relevance since it formalizes the planning process that all CDN operators must follow to reduce the operational cost of their overlay networks, while meeting the performance requirements of their end users. Next, we focus on developing a temporal cone (TC) algorithm that detects PFS (Provider-free ASes). By delivering a significant portion of Internet traffic, PFS is highly relevant to the overall resilience of the Internet. We detect PFS from public datasets of inter-AS economic relationships, utilizing topological statistics (customer cones of ASes) and temporal diversity. Finally, we focus on a multilateral contractual arrangement and develop algorithms for optimizing the cost of transit and access ASes. In particular, we implement Bertsekas auction algorithm for the optimal cost assignment of access ASes to transit ASes. Furthermore, we implement an epsilon-greedy bandit algorithm for optimizing the price of transit ASes and show its learning potential.This work has been supported by IMDEA Networks Institute.Programa Oficial de Doctorado en Ingeniería TelemáticaPresidente: Jordi Domingo Pascual.- Secretario: Francisco Valera Pintor.- Vocal: Pedro Andrés Aranda Gutiérre