Preliminary specification and design documentation for software components to achieve catallaxy in computational systems

This Report is about the preliminary specifications and design documentation for software components to achieve Catallaxy in computational systems. -- Die Arbeit beschreibt die Spezifikation und das Design von Softwarekomponenten, um das Konzept der Katallaxie in Grid Systemen umzusetzen. Eine Einführung ordnet das Konzept der Katallaxie in bestehende Grid Taxonomien ein und stellt grundlegende Komponenten vor. Anschließend werden diese Komponenten auf ihre Anwendbarkeit in bestehenden Application Layer Netzwerken untersucht.Grid Computing

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

Incentive Mechanisms in Peer-to-Peer Networks — A Systematic Literature Review

Centralized networks inevitably exhibit single points of failure that malicious actors regularly target. Decentralized networks are more resilient if numerous participants contribute to the network’s functionality. Most decentralized networks employ incentive mechanisms to coordinate the participation and cooperation of peers and thereby ensure the functionality and security of the network. This article systematically reviews incentive mechanisms for decentralized networks and networked systems by covering 165 prior literature reviews and 178 primary research papers published between 1993 and October 2022. Of the considered sources, we analyze 11 literature reviews and 105 primary research papers in detail by categorizing and comparing the distinctive properties of the presented incentive mechanisms. The reviewed incentive mechanisms establish fairness and reward participation and cooperative behavior. We review work that substitutes central authority through independent and subjective mechanisms run in isolation at each participating peer and work that applies multiparty computation. We use monetary, reputation, and service rewards as categories to differentiate the implementations and evaluate each incentive mechanism’s data management, attack resistance, and contribution model. Further, we highlight research gaps and deficiencies in reproducibility and comparability. Finally, we summarize our assessments and provide recommendations to apply incentive mechanisms to decentralized networks that share computational resources

A Game-Theoretic Approach to Strategic Resource Allocation Mechanisms in Edge and Fog Computing

With the rapid growth of Internet of Things (IoT), cloud-centric application management raises questions related to quality of service for real-time applications. Fog and edge computing (FEC) provide a complement to the cloud by filling the gap between cloud and IoT. Resource management on multiple resources from distributed and administrative FEC nodes is a key challenge to ensure the quality of end-user’s experience. To improve resource utilisation and system performance, researchers have been proposed many fair allocation mechanisms for resource management. Dominant Resource Fairness (DRF), a resource allocation policy for multiple resource types, meets most of the required fair allocation characteristics. However, DRF is suitable for centralised resource allocation without considering the effects (or feedbacks) of large-scale distributed environments like multi-controller software defined networking (SDN). Nash bargaining from micro-economic theory or competitive equilibrium equal incomes (CEEI) are well suited to solving dynamic optimisation problems proposing to ‘proportionately’ share resources among distributed participants. Although CEEI’s decentralised policy guarantees load balancing for performance isolation, they are not faultproof for computation offloading. The thesis aims to propose a hybrid and fair allocation mechanism for rejuvenation of decentralised SDN controller deployment. We apply multi-agent reinforcement learning (MARL) with robustness against adversarial controllers to enable efficient priority scheduling for FEC. Motivated by software cybernetics and homeostasis, weighted DRF is generalised by applying the principles of feedback (positive or/and negative network effects) in reverse game theory (GT) to design hybrid scheduling schemes for joint multi-resource and multitask offloading/forwarding in FEC environments. In the first piece of study, monotonic scheduling for joint offloading at the federated edge is addressed by proposing truthful mechanism (algorithmic) to neutralise harmful negative and positive distributive bargain externalities respectively. The IP-DRF scheme is a MARL approach applying partition form game (PFG) to guarantee second-best Pareto optimality viii | P a g e (SBPO) in allocation of multi-resources from deterministic policy in both population and resource non-monotonicity settings. In the second study, we propose DFog-DRF scheme to address truthful fog scheduling with bottleneck fairness in fault-probable wireless hierarchical networks by applying constrained coalition formation (CCF) games to implement MARL. The multi-objective optimisation problem for fog throughput maximisation is solved via a constraint dimensionality reduction methodology using fairness constraints for efficient gateway and low-level controller’s placement. For evaluation, we develop an agent-based framework to implement fair allocation policies in distributed data centre environments. In empirical results, the deterministic policy of IP-DRF scheme provides SBPO and reduces the average execution and turnaround time by 19% and 11.52% as compared to the Nash bargaining or CEEI deterministic policy for 57,445 cloudlets in population non-monotonic settings. The processing cost of tasks shows significant improvement (6.89% and 9.03% for fixed and variable pricing) for the resource non-monotonic setting - using 38,000 cloudlets. The DFog-DRF scheme when benchmarked against asset fair (MIP) policy shows superior performance (less than 1% in time complexity) for up to 30 FEC nodes. Furthermore, empirical results using 210 mobiles and 420 applications prove the efficacy of our hybrid scheduling scheme for hierarchical clustering considering latency and network usage for throughput maximisation.Abubakar Tafawa Balewa University, Bauchi (Tetfund, Nigeria

Engineering coordination : eine Methodologie für die Koordination von Planungssystemen

Planning problems, like real-world planning and scheduling problems, are complex tasks. As an efficient strategy for handing such problems is the ‘divide and conquer’ strategy has been identified. Each sub problem is then solved independently. Typically the sub problems are solved in a linear way. This approach enables the generation of sub-optimal plans for a number of real world problems. Today, this approach is widely accepted and has been established e.g. in the organizational structure of companies. But existing interdependencies between the sub problems are not sufficiently regarded, as each problem are solved sequentially and no feedback information is given. The field of coordination has been covered by a number of academic fields, like the distributed artificial intelligence, economics or game theory. An important result is, that there exist no method that leads to optimal results in any given coordination problem. Consequently, a suitable coordination mechanism has to be identified for each single coordination problem. Up to now, there exists no process for the selection of a coordination mechanism, neither in the engineering of distributed systems nor in agent oriented software engineering. Within the scope of this work the ECo process is presented, that address exactly this selection problem. The Eco process contains the following five steps. • Modeling of the coordination problem • Defining the coordination requirements • Selection / Design of the coordination mechanism • Implementation • Evaluation Each of these steps is detailed in the thesis. The modeling has to be done to enable a systemic analysis of the coordination problem. Coordination mechanisms have to respect the given situation and the context in which the coordination has to be done. The requirements imposed by the context of the coordination problem are formalized in the coordination requirements. The selection process is driven by these coordination requirements. Using the requirements as a distinction for the selection of a coordination mechanism is a central aspect of this thesis. Additionally these requirements can be used for documentation of design decisions. Therefore, it is reasonable to annotate the coordination mechanisms with the coordination requirements they fulfill and fail to ease the selection process, for a given situation. For that reason we present a new classification scheme for coordination methods within this thesis that classifies existing coordination methods according to a set of criteria that has been identified as important for the distinction between different coordination methods. The implementation phase of the ECo process is supported by the CoPS process and CoPS framework that has been developed within this thesis, as well. The CoPS process structures the design making that has to be done during the implementation phase. The CoPS framework provides a set of basic features software agents need for realizing the selected coordination method. Within the CoPS process techniques are presented for the design and implementation of conversations between agents that can be applied not only within the context of the coordination of planning systems, but for multiagent systems in general. The ECo-CoPS approach has been successfully validated in two case studies from the logistic domain.Reale Planungsprobleme, wie etwa die Produktionsplanung in einer Supply Chain, sind komplex Planungsprobleme. Eine übliche Strategie derart komplexen Problemen zu lösen, ist es diese Probleme in einfachere Teilprobleme zu zerlegen und diese dann separat, meist sequentiell, zu lösen (divide-and-conquer Strategie). Dieser Ansatz erlaubt die Erstellung von (suboptimalen) Plänen für eine Reihe von realen Anwendungen, und ist heute in den Organisationsstrukturen von größeren Unternehmen institutionalisiert worden. Allerdings werden Abhängigkeiten zwischen den Teilproblemen nicht ausreichend berücksichtigt, da die Partialprobleme sequentiell ohne Feedback gelöst werden. Die erstellten Teillösungen müssen deswegen oft nachträglich koordiniert werden. Das Gebiet der Koordination wird in verschiedenen Forschungsgebieten, wie etwa der verteilten Künstlichen Intelligenz, den Wirtschaftswissenschaften oder der Spieltheorie untersucht. Ein zentrales Ergebnis dieser Forschung ist, dass es keinen für alle Situationen geeigneten Koordinationsmechanismus gibt. Es stellt sich also die Aufgabe aus den zahlreichen vorgeschlagenen Koordinationsmechanismen eine Auswahl zu treffen, die für die aktuelle Situation den geeigneten Mechanismus identifiziert. Für die Auswahl eines solchen Mechanismus existiert bisher jedoch kein strukturiertes Verfahren für die Entwicklung von verteilten Systems und insbesondere im Bereich der Agenten orientierter Softwareentwicklung. Im Rahmen dieser Arbeit wird genau hierfür ein Verfahren vorgestellt, der ECo-Prozess. Mit Hilfe dieses Prozesses wird der Auswahlprozess in die folgenden Schritte eingeteilt: • Modellierung der Problemstellung und des relevante Kontextes • Formulierung von Anforderungen an einen Koordinationsmechanismus (coordination requirements) • Auswahl/Entwurf eines Koordinationsmechanismuses • Implementierung des Koordinationsverfahrens • Evaluation des Koordinationsverfahrens Diese Schritte werden im Rahmen der vorliegenden Arbeit detailliert beschrieben. Die Modellierung der Problemstellung stellt dabei den ersten Schritt dar, um die Problemstellung analytisch zugänglich zu machen. Koordinationsverfahren müssen die Gegebenheiten, den Kontext und die Domäne, in der sie angewendet werden sollen hinreichend berücksichtigen um anwendbar zu sein. Dieses kann über Anforderungen an den Koordinationsprozess formalisiert werden. Der von den Anforderungen getrieben Auswahlprozess ist ein Kernstück der hier vorgestellten Arbeit. Durch die Formulierung der Anforderungen und der Annotation eines Koordinationsmechanismus bezüglich der erfüllten und nicht erfüllten Anforderungen werden die Motive für Designentscheidungen dieses Verfahren expliziert. Wenn Koordinationsverfahren anhand dieser Anforderungen klassifiziert werden können, ist es weiterhin möglich den Auswahlprozess (unabhängig vom ECo-Ansatz) zu vereinfachen und zu beschleunigen. Im Rahmen dieser Arbeit wird eine Klassifikation von Koordinationsansätzen anhand von allgemeinen Kriterien vorgestellt, die die Identifikation von geeigneten Kandidaten erleichtern. Diese Kandidaten können dann detaillierter untersucht werden. Dies wurde in den vorgestellten Fallstudien erfolgreich demonstriert. Für die Unterstützung der Implementierung eines Koordinationsansatzes wird in dieser Arbeit zusätzlich der CoPS Prozess vorgeschlagen. Der CoPS Prozess erlaubt einen ganzheitlichen systematischen Ansatz für den Entwurf und die Implementierung eines Koordinationsverfahrens. Unterstürzt wird der CoPS Prozess durch das CoPS Framework, das die Implementierung erleichtert, indem es als eine Plattform mit Basisfunktionalität eines Agenten bereitstellt, der für die Koordination von Planungssystemen verantwortlich ist. Im Rahmen des CoPS Verfahrens werden Techniken für den Entwurf und die Implementierung von Konversation im Kontext des agenten-orientiertem Software Engineerings ausführlich behandelt. Der Entwurf von Konversationen geht dabei weit über Fragestellung der Formatierung von Nachrichten hinaus, wie dies etwa in den FIPA Standards geregelt ist, und ist für die Implementierung von agentenbasierten Systemen im Allgemeinen von Bedeutung. Die Funktionsweise des ECo-CoPS Ansatzes wird anhand von zweierfolgreich durchgeführten Fallstudien aus dem betriebswirtschaftlichen Kontext vorgestellt

Essays on Bounded Rationality and Strategic Behavior in Experimental and Computational Economics.

Chapter 1 evaluates coordination among agents in environments with congestion effects. This paper discusses how people implicitly learn to coordinate their actions when such coordination is beneficial but difficult. During a series of experiments involving human subjects and simulated agents, subjects repeatedly update their strategies during play of the El Farol Bar Game. A subject is able to partially observe her opponents’ previous strategies and payoffs before setting her strategy for the next round of play. Play did not converge to the stage game’s pure strategy Nash equilibrium. Also, subjects routinely imitated the most successful strategies. This flocking behavior led to socially inefficient outcomes. Economic agents often face situations in which they must simultaneously interact in a variety of strategic environments, and yet they have only limited cognitive resources to compete in these varied settings. Chapters 2 through 4 consider how boundedly rational agents allocate scarce cognitive resources in strategic environments characterized by multiple simultaneously played games. Chapter 2 builds a framework that encapsulates a complex adaptive system defined by finite automaton strategies. Chapter 3 considers the evolution of strategies in the presence of cognitive costs in both single-game and multiple-game settings. When facing costs, a player’s strategy population quickly converges to a largely homogenous pool of rather simplified strategies that utilize only 14 percent of their cognitive power. There is evidence of both positive and negative strategic complementarities in the two game environments. Strategies perform better in each game within the two-game {Prisoner’s Dilemma, Stag Hunt} setting than they do when playing each game individually. Conversely, performance is impaired in each game of the two-game {Stag Hunt, Chicken} environment relative to the single game settings. Chapter 4 uses the evolved strategies to evaluate the impact of experience in multiple game environments. Experience in Prisoner’s Dilemma translates well into other games in two-game environments, while experience in Stag Hunt handicaps performance in other games. In multiple game settings, since a strategy’s actions are applied in different games, the context of actions is important. Chapters 3 and 4 address this issue by comparing the natural outcome context to the cooperate/defect context.Ph.D.EconomicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/86359/1/leady_1.pd