Abstract. Current Online social networks (OSN) are web services run on logically centralized infrastructure. Large OSN sites use content distribution networks and thus distribute some of the load by caching for performance reasons, nevertheless there is a central repository for user and application data. This centralized nature of OSNs has several drawbacks including scalability, privacy, dependence on a provider, need for being online for every transaction, and a lack of locality. There have thus been several efforts toward decentralizing OSNs while retaining the functionalities offered by centralized OSNs. A decentralized online social network (DOSN) is a distributed system for social networking with no or limited dependency on any dedicated central infrastructure. In this chapter we explore the various motivations of a decentralized approach to online social networking, discuss several concrete proposals and types of DOSN as well as challenges and opportunities associated with decentralization.

bstract-In peer-to-peer storage systems, peers replicate each others' data in order to increase availability. If the matching is done centrally, the algorithm can optimize data availability in an equitable manner for all participants. However, if matching is decentralized, the peers' selfishness can greatly alter the results, leading to performance inequities that can render the system unreliable and thus ultimately unusable.We analyze the problem using both theoretical approaches !complexity analysis for the centralized system, game theory for the decentralized one) and simulation. We prove that the problem of optimizing availability in a centralized system is NP-hard. In decentralized settings, we show that the rational behavior of selfish peers will be to replicate only with similarly-available peers. Compared to the socially-optimal solution, highly available peers have their data availability increased at the expense of decreased data availability for less available peers. The price of anarchy is high: unbounded in one model, and linear with the number of time slots in the second model.We also propose centralized and decentralized heuristics that, according to our experiments, converge fast in the average case.The high price of anarchy means that a completely decentralized system could be too hostile for peers with low availability, who could never achieve satisfying replication parameters. Moreover, we experimentally show that even explicit consideration and exploitation of diurnal patterns of peer availability has a small effect on the data availability-except when the system has truly global scope. Yet a fully centralized system is infeasible, not only because of problems in information gathering, but also the complexity of optimizing availability. The solution to this dilemma is to create system-wide cooperation rules that allow a decentralized algorithm, but also limit the selfishness of the participants.

Models of computational trust support users in taking decisions. They are commonly used to guide users' judgements in online auction sites; or to determine quality of contributions in Web 2.0 sites. However, most existing systems require historical information about the past behavior of the specific agent being judged. In contrast, in real life, to anticipate and to predict a stranger's actions in absence of the knowledge of such behavioral history, we often use our "instinct"-essentially stereotypes developed from our past interactions with other "similar" persons. In this paper, we propose StereoTrust, a computational trust model inspired by stereotypes as used in real-life. A stereotype contains certain features of agents and an expected outcome of the transaction. When facing a stranger, an agent derives its trust by aggregating stereotypes matching the stranger's profile. Since stereotypes are formed locally, recommendations stem from the trustor's own personal experiences and perspective. Historical behavioral information, when available, can be used to refine the analysis. According to our experiments using Epinions.com dataset, StereoTrust compares favorably with existing trust models that use different kinds of information and more complete historical information.

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International audienceWe study two problems directly resulting from organizational decentralization of the grid. Firstly, the problem of fair scheduling in systems in which the grid scheduler has complete control of processors' schedules. Secondly, the problem of fair and feasible scheduling in decentralized case, in which the grid scheduler can only suggest a schedule, which can be later modified by a processor's owner. Using game theory, we show that scheduling in decentralized case is analogous to the prisoner's dilemma game. Moreover, the Nash equilibrium results in significant performance drop. Therefore, a strong community control is required to achieve acceptable performance