this paper, Gnutella is no exception to this finding, and an experimental study of its user patterns shows indeed that free riding is the norm rather than the exception. If distributed systems such as Gnutella rely on voluntary cooperation, rampant free riding may eventually render them useless, as few individuals will contribute anything that is new and high quality. Thus, the current debate over copyright might become a non-issue when compared to the possible collapse of such systems. This collapse can happen because of two factors, the tragedy of the digital commons, and increased system vulnerability, which we now discuss

This paper provides an overview of research and development activities in the field of autonomous agents and multi-agent systems. It aims to identify key concepts and applications, and to indicate how they relate to one-another. Some historical context to the field of agent-based computing is given, and contemporary research directions are presented. Finally, a range of open issues and future challenges are highlighted.

Distributed denial-of-service (DDoS) is a rapidly growing problem. The multitude and variety of both the attacks and the defense approaches is overwhelming. This paper presents two taxonomies for classifying attacks and defenses, and thus provides researchers with a better understanding of the problem and the current solution space. The attack classification criteria was selected to highlight commonalities and important features of attack strategies, that define challenges and dictate the design of countermeasures. The defense taxonomy classifies the body of existing DDoS defenses based on their design decisions; it then shows how these decisions dictate the advantages and deficiencies of proposed solutions.

We describe the basic economic theory of pricing a congestible resource such as an ftp server, a router, a Web site, etc. In particular, we examine the implications of “congestion pricing” as a way to encourage efficient use of network resources. We explore the implications of flat pricing and congestion pricing for capacity expansion in centrally planned, competitive, and monopolistic environments.

Abstract — Over the Internet today, computing and communications environments are significantly more complex and chaotic than classical distributed systems, lacking any centralized organization or hierarchical control. There has been much interest in emerging Peer-to-Peer (P2P) network overlays because they provide a good substrate for creating large-scale data sharing, content distribution and application-level multicast applications. These P2P networks try to provide a long list of features such as: selection of nearby peers, redundant storage, efficient search/location of data items, data permanence or guarantees, hierarchical naming, trust and authentication, and, anonymity. P2P networks potentially offer an efficient routing architecture that is self-organizing, massively scalable, and robust in the wide-area, combining fault tolerance, load balancing and explicit notion of locality. In this paper, we present a survey and comparison of various Structured and Unstructured P2P networks. We categorize the various schemes into these two groups in the design spectrum and discuss the application-level network performance of each group.

Lack of cooperation (free riding) is one of the key problems that confronts today's P2P systems. What makes this problem particularly difficult is the unique set of challenges that P2P systems pose: large populations, high turnover, asymmetry of interest, collusion, zero-cost identities, and traitors. To tackle these challenges we model the P2P system using the Generalized Prisoner's Dilemma (GPD), and propose the Reciprocative decision function as the basis of a family of incentives techniques. These techniques are fully distributed and include: discriminating server selection, maxflowbased subjective reputation, and adaptive stranger policies. Through simulation, we show that these techniques can drive a system of strategic users to nearly optimal levels of cooperation.

In this paper we discuss a number of previously unaddressed issues that arise in automated negotiation among self-interested agents whose rationality is bounded by computational complexity. These issues are presented in the context of iterative task allocation negotiations. First, the reasons why such agents need to be able to choose the stage and level of commitment dynamically are identified. A protocol that allows such choices through conditional commitment breaking penalties is presented. Next, the implications of bounded rationality are analyzed. Several tradeoffs between allocated computation and negotiation benefits and risk are enumerated, and the necessity of explicit local deliberation control is substantiated. Techniques for linking negotiation items and multiagent contracts are presented as methods for escaping local optima in the task allocation process. Implementing both methods among self-interested bounded rational agents is discussed. Finally, the ...

Despite their many advantages, e-Businesses lag behind brick and mortar businesses in several fundamental respects. This paper concerns one of these: relationships based on trust and reputation. Recent studies on simple reputation systems for e-Businesses such as eBay have pointed to the importance of such rating systems for deterring moral hazard and encouraging trusting interactions. However, despite numerous studies on trust and reputation systems, few have taken studies across disciplines to provide an integrated account of these concepts and their relationships. This paper first surveys existing literatures on trust, reputation and a related concept: reciprocity. Based on sociological and biological understandings of these concepts, a computational model is proposed. This model can be implemented in a real system to consistently calculate agents ’ trust and reputation scores. 1.

Game theory is one of the key paradigms behind many scientific disciplines from biology to behavioral sciences to economics. In its evolutionary form and especially when the interacting agents are linked in a specific social network the underlying solution concepts and methods are very similar to those applied in non-equilibrium statistical physics. This review gives a tutorial-type overview of the field for physicists. The first four sections introduce the necessary background in classical and evolutionary game theory from the basic definitions to the most important results. The fifth section surveys the topological complications implied by non-mean-field-type social network structures in general. The next three sections discuss in detail the dynamic behavior of three prominent classes of models: the Prisoner’s Dilemma, the Rock–Scissors–Paper game, and Competing Associations. The major theme of the review is in what sense and how the graph structure of interactions can modify and enrich the picture of long term behavioral patterns emerging in evolutionary games.

Abstract not found