MIMO-OFDM Based Energy Harvesting Cooperative Communications Using Coalitional Game Algorithm

This document is the Accepted Manuscript version. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In this paper, we consider the problem of cooperative communication between relays and base station in an advanced MIMO-OFDM framework, under the assumption that the relays are supplied by electric power drawn from energy harvesting (EH) sources. In particular, we focus on the relay selection, with the goal to guarantee the required performance in terms of capacity. In order to maximize the data throughput under the EH constraint, we model the transmission scheme as a non-transferable coalition formation game, with characteristic function based on an approximated capacity expression. Then, we introduce a powerful mathematical tool inherent to coalitional game theory, namely: the Shapley value (Sv) to provide a reliable solution concept to the game. The selected relays will form a virtual dynamically-configuredMIMO network that is able to transmit data to destination using efficient space-time coding techniques. Numerical results, obtained by simulating the EH-powered cooperativeMIMO-OFDMtransmission with Algebraic Space-Time Coding (ASTC), prove that the proposed coalitional game-based relay selection allows to achieve performance very close to that obtained by the same system operated by guaranteed power supply. The proposed methodology is finally compared with some recent related state-of-the-art techniques showing clear advantages in terms of link performance and goodput.Peer reviewe

Collaborative Models for Supply Networks Coordination and Healthcare Consolidation

This work discusses the collaboration framework among different members of two complex systems: supply networks and consolidated healthcare systems. Although existing literature advocates the notion of strategic partnership/cooperation in both supply networks and healthcare systems, there is a dearth of studies quantitatively analyzing the scope of cooperation among the members and its benefit on the global performance. Hence, the first part of this dissertation discusses about two-echelon supply networks and studies the coordination of buyers and suppliers for multi-period procurement process. Viewing the issue from the same angel, the second part studies the coordination framework of hospitals for consolidated healthcare service delivery. Realizing the dynamic nature of information flow and the conflicting objectives of members in supply networks, a two-tier coordination mechanism among buyers and suppliers is modeled. The process begins with the intelligent matching of buyers and suppliers based on the similarity of users profiles. Then, a coordination mechanism for long-term agreements among buyers and suppliers is proposed. The proposed mechanism introduces the importance of strategic buyers for suppliers in modeling and decision making process. To enhance the network utilization, we examine a further collaboration among suppliers where cooperation incurs both cost and benefit. Coalitional game theory is utilized to model suppliers\u27 coalition formation. The efficiency of the proposed approaches is evaluated through simulation studies. We then revisit the common issue, the co-existence of partnership and conflict objectives of members, for consolidated healthcare systems and study the coordination of hospitals such that there is a central referral system to facilitate patients transfer. We consider three main players including physicians, hospitals managers, and the referral system. As a consequence, the interaction within these players will shape the coordinating scheme to improve the overall system performance. To come up with the incentive scheme for physicians and aligning hospitals activities, we define a multi-objective mathematical model and obtain optimal transfer pattern. Using optimal solutions as a baseline, a cooperative game between physicians and the central referral system is defined to coordinate decisions toward system optimality. The efficiency of the proposed approach is examined via a case study

Advances in Negotiation Theory: Bargaining, Coalitions and Fairness

Bargaining is ubiquitous in real-life. It is a major dimension of political and business activities. It appears at the international level, when governments negotiate on matters ranging from economic issues (such as the removal of trade barriers), to global security (such as fighting against terrorism) to environmental and related issues (e.g. climate change control). What factors determine the outcome of negotiations such as those mentioned above? What strategies can help reach an agreement? How should the parties involved divide the gains from cooperation? With whom will one make alliances? This paper addresses these questions by focusing on a non-cooperative approach to negotiations, which is particularly relevant for the study of international negotiations. By reviewing non-cooperative bargaining theory, non-cooperative coalition theory, and the theory of fair division, this paper will try to identify the connection among these different facets of the same problem in an attempt to facilitate the progress towards a unified framework.Negotiation theory, Bargaining, Coalitions, Fairness, Agreements

Transforming Energy Networks via Peer to Peer Energy Trading: Potential of Game Theoretic Approaches

Peer-to-peer (P2P) energy trading has emerged as a next-generation energy management mechanism for the smart grid that enables each prosumer of the network to participate in energy trading with one another and the grid. This poses a significant challenge in terms of modeling the decision-making process of each participant with conflicting interest and motivating prosumers to participate in energy trading and to cooperate, if necessary, for achieving different energy management goals. Therefore, such decision-making process needs to be built on solid mathematical and signal processing tools that can ensure an efficient operation of the smart grid. This paper provides an overview of the use of game theoretic approaches for P2P energy trading as a feasible and effective means of energy management. As such, we discuss various games and auction theoretic approaches by following a systematic classification to provide information on the importance of game theory for smart energy research. Then, the paper focuses on the P2P energy trading describing its key features and giving an introduction to an existing P2P testbed. Further, the paper zooms into the detail of some specific game and auction theoretic models that have recently been used in P2P energy trading and discusses some important finding of these schemes.Comment: 38 pages, single column, double spac

Hedonic Coalition Formation for Distributed Task Allocation among Wireless Agents

Autonomous wireless agents such as unmanned aerial vehicles or mobile base stations present a great potential for deployment in next-generation wireless networks. While current literature has been mainly focused on the use of agents within robotics or software applications, we propose a novel usage model for self-organizing agents suited to wireless networks. In the proposed model, a number of agents are required to collect data from several arbitrarily located tasks. Each task represents a queue of packets that require collection and subsequent wireless transmission by the agents to a central receiver. The problem is modeled as a hedonic coalition formation game between the agents and the tasks that interact in order to form disjoint coalitions. Each formed coalition is modeled as a polling system consisting of a number of agents which move between the different tasks present in the coalition, collect and transmit the packets. Within each coalition, some agents can also take the role of a relay for improving the packet success rate of the transmission. The proposed algorithm allows the tasks and the agents to take distributed decisions to join or leave a coalition, based on the achieved benefit in terms of effective throughput, and the cost in terms of delay. As a result of these decisions, the agents and tasks structure themselves into independent disjoint coalitions which constitute a Nash-stable network partition. Moreover, the proposed algorithm allows the agents and tasks to adapt the topology to environmental changes such as the arrival/removal of tasks or the mobility of the tasks. Simulation results show how the proposed algorithm improves the performance, in terms of average player (agent or task) payoff, of at least 30.26% (for a network of 5 agents with up to 25 tasks) relatively to a scheme that allocates nearby tasks equally among agents.Comment: to appear, IEEE Transactions on Mobile Computin

Tasks for Agent-Based Negotiation Teams:Analysis, Review, and Challenges

An agent-based negotiation team is a group of interdependent agents that join together as a single negotiation party due to their shared interests in the negotiation at hand. The reasons to employ an agent-based negotiation team may vary: (i) more computation and parallelization capabilities, (ii) unite agents with different expertise and skills whose joint work makes it possible to tackle complex negotiation domains, (iii) the necessity to represent different stakeholders or different preferences in the same party (e.g., organizations, countries, and married couple). The topic of agent-based negotiation teams has been recently introduced in multi-agent research. Therefore, it is necessary to identify good practices, challenges, and related research that may help in advancing the state-of-the-art in agent-based negotiation teams. For that reason, in this article we review the tasks to be carried out by agent-based negotiation teams. Each task is analyzed and related with current advances in different research areas. The analysis aims to identify special challenges that may arise due to the particularities of agent-based negotiation teams.Comment: Engineering Applications of Artificial Intelligence, 201

Contributions to distributed MPC: coalitional and learning approaches

A growing number of works and applications are consolidating the research area of distributed control with partial and varying communication topologies. In this context, many of the works included in this thesis focus on the so-called coalitional MPC. This approach is characterized by the dynamic formation of groups of cooperative MPC agents (referred to as coalitions) and seeks to provide a performance close to the centralized one with lighter computations and communication demands. The thesis includes a literature review of existing distributed control methods that boost scalability and flexibility by exploiting the degree of interaction between local controllers. Likewise, we present a hierarchical coalitional MPC for traffic freeways and new methods to address the agents' clustering problem, which, given its combinatoria! nature, becomes a key issue for the real-time implementation of this type of controller. Additionally, new theoretical results to provide this clustering strategy with robust and stability guarantees to track changing targets are included. Further works of this thesis focus on the application of learning techniques in distributed and decentralized MPC schemes, thus paving the way for a future extension to the coalitional framework. In this regard, we have focused on the use of neural networks to aid distributed negotiations, and on the development of a multi­ agent learning MPC based on a collaborative data collection

Shapley value: its algorithms and application to supply chains

Introduction− Coalitional game theorists have studied the coalition struc-ture and the payoff schemes attributed to such coalition. With respect to the payoff value, there are number ways of obtaining to “best” distribution of the value of the game. The solution concept or payoff value distribution that is canonically held to fairly dividing a coalition’s value is called the Shapley Value. It is probably the most important regulatory payoff scheme in coali-tion games. The reason the Shapley value has been the focus of so much interest is that it represents a distinct approach to the problems of complex strategic interaction that game theory tries to solve. Objective−This study aims to do a brief literature review of the application of Shapley Value for solving problems in different cooperation fields and the importance of studying existing methods to facilitate their calculation. This review is focused on the algorithmic view of cooperative game theory with a special emphasis on supply chains. Additionally, an algorithm for the calcu-lation of the Shapley Value is proposed and numerical examples are used in order to validate the proposed algorithm. Methodology−First of all, the algorithms used to calculate Shapley value were identified. The element forming a supply chain were also identified. The cooperation between the members of the supply chain ways is simulated and the Shapley Value is calculated using the proposed algorithm in order to check its applicability. Results and Conclusions− The algorithmic approach introduced in this paper does not wish to belittle the contributions made so far but intends to provide a straightforward solution for decision problems that involve supply chains. An efficient and feasible way of calculating the Shapley Value when player structures are known beforehand provides the advantage of reducing the amount of effort in calculating all possible coalition structures prior to the Shapley.Introducción: Los teóricos del juego cooperativos han estudiado la estructura de coalición y los esquemas de pago atribuidos a esas coaliciones. En relación al valor del pago, hay varias maneras de obtener la “mejor” distribución del valor del juego. El concepto de solución o la distribución del valor de recompensa que se mantiene canónicamente para dividir justamente el valor de una coalición se llama Valor de Shapley. Es probablemente el esquema de pago más importante en los juegos cooperativos. La razón por la cual el valor de Shapley ha sido el foco de tanto interés es que representa un acercamiento distinto a los problemas de la interacción estratégica compleja que la teoría del juego intenta resolver.Objetivo: Este estudio tiene como objetivo hacer una breve revisión bibliográfica de la aplicación del Valor de Shapley para resolver problemas en diferentes campos de cooperación y la importancia de estudiar los métodos existentes para facilitar su cálculo. Esta revisión se centra en la visión algorítmica de la teoría cooperativa de juegos con un énfasis especial en las cadenas de suministro. Adicionalmente se propone un algoritmo para el cálculo del Valor de Shapley y se utilizan ejemplos numéricos para validar el algoritmo propuesto.Metodología: En primer lugar, se identificaron los algoritmos utilizados para calcular el valor de Shapley. También se identificó los elementos que forman una cadena de suministro. Luego se simula la cooperación entre los miembros de las vías de la cadena de suministro y se calcula el valor de Shapley utilizando el algoritmo propuesto para comprobar su aplicabilidad.Resultados y Conclusiones: El enfoque algorítmico introducido en este documento no pretende menospreciar las contribuciones hechas hasta ahora, pero tiene la intención de proporcionar una solución directa para problemas de decisión que involucran cadenas de suministro. Una manera eficiente y factible de calcular el valor de Shapley cuando las estructuras de jugador se conocen de antemano proporciona la ventaja de reducir la cantidad de esfuerzo en el cálculo de todas las estructuras de coalición posibles antes del Shapley

El valor de Shapley: sus algoritmos y aplicación en cadenas de suministro

Introduction: Coalitional game theorists have studied the coalition structure and the payoff schemes attributed to such coalition. With respect to the payoff value, there are number ways of obtaining to “best” distribution of the value of the game. The solution concept or payoff value distribution that is canonically held to fairly dividing a coalition’s value is called the Shapley Value. It is probably the most important regulatory payoff scheme in coalition games. The reason the Shapley value has been the focus of so much interest is that it represents a distinct approach to the problems of complex strategic interaction that game theory tries to solve.Objective: This study aims to do a brief literature review of the application of Shapley Value for solving problems in different cooperation fields and the importance of studying existing methods to facilitate their calculation. This review is focused on the algorithmic view of cooperative game theory with a special emphasis on supply chains. Additionally, an algorithm for the calculation of the Shapley Value is proposed and numerical examples are used in order to validate the proposed algorithm.Methodology: First of all, the algorithms used to calculate Shapley value were identified. The element forming a supply chain were also identified. The cooperation between the members of the supply chain ways is simulated and the Shapley Value is calculated using the proposed algorithm in order to check its applicability.Results and Conclusions: The algorithmic approach introduced in this paper does not wish to belittle the contributions made so far but intends to provide a straightforward solution for decision problems that involve supply chains. An efficient and feasible way of calculating the Shapley Value when player structures are known beforehand provides the advantage of reducing the amount of effort in calculating all possible coalition structures prior to the Shapley.Introducción: Los teóricos del juego cooperativos han estudiado la estructura de coalición y los esquemas de pago atribuidos a esas coaliciones. En relación al valor del pago, hay varias maneras de obtener la “mejor” distribución del valor del juego. El concepto de solución o la distribución del valor de recompensa que se mantiene canónicamente para dividir justamente el valor de una coalición se llama Valor de Shapley. Es probablemente el esquema de pago más importante en los juegos cooperativos. La razón por la cual el valor de Shapley ha sido el foco de tanto interés es que representa un acercamiento distinto a los problemas de la interacción estratégica compleja que la teoría del juego intenta resolver.Objetivo: Este estudio tiene como objetivo hacer una breve revisión bibliográfica de la aplicación del Valor de Shapley para resolver problemas en diferentes campos de cooperación y la importancia de estudiar los métodos existentes para facilitar su cálculo. Esta revisión se centra en la visión algorítmica de la teoría cooperativa de juegos con un énfasis especial en las cadenas de suministro. Adicionalmente se propone un algoritmo para el cálculo del Valor de Shapley y se utilizan ejemplos numéricos para validar el algoritmo propuesto.Metodología: En primer lugar, se identificaron los algoritmos utilizados para calcular el valor de Shapley. También se identificó los elementos que forman una cadena de suministro. Luego se simula la cooperación entre los miembros de las vías de la cadena de suministro y se calcula el valor de Shapley utilizando el algoritmo propuesto para comprobar su aplicabilidad.Resultados y Conclusiones: El enfoque algorítmico introducido en este documento no pretende menospreciar las contribuciones hechas hasta ahora, pero tiene la intención de proporcionar una solución directa para problemas de decisión que involucran cadenas de suministro. Una manera eficiente y factible de calcular el valor de Shapley cuando las estructuras de jugador se conocen de antemano proporciona la ventaja de reducir la cantidad de esfuerzo en el cálculo de todas las estructuras de coalición posibles antes del Shapley.