The Wikipedia is a collaborative encyclopedia: anyone can contribute to its articles simply by clicking on an "edit" button. The open nature of the Wikipedia has been key to its success, but has also created a challenge: how can readers develop an informed opinion on its reliability? We propose a system that computes quantitative values of trust for the text in Wikipedia articles; these trust values provide an indication of text reliability.The system uses as input the revision history of each article, as well as information about the reputation of the contributing authors, as provided by a reputation system. The trust of a word in an article is computed on the basis of the reputation of the original author of the word, as well as the reputation of all authors who edited text near the word. The algorithm computes word trust values that vary smoothly across the text; the trust values can be visualized using varying text-background colors. The algorithm ensures that all changes to an article's text are reflected in the trust values, preventing surreptitious content changes.We have implemented the proposed system, and we have used it to compute and display the trust of the text of thousands of articles of the English Wikipedia. To validate our trust-computation algorithms, we show that text labeled as low-trust has a significantly higher probability of being edited in the future than text labeled as high-trust.

We consider the problem of optimal real-time scheduling of periodic and sporadic tasks for identical multiprocessors. A number of recent papers have used the notions of fluid scheduling and deadline partitioning to guarantee optimality and improve performance. In this paper, we develop a unifying theory with the DP-FAIR scheduling policy and examine how it overcomes problems faced by greedy scheduling algorithms. We then present a simple DP-FAIR scheduling algorithm, DP-WRAP, which serves as a least common ancestor to many recent algorithms. We also show how to extend DP-FAIR to the scheduling of sporadic tasks with arbitrary deadlines.

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We consider the problem of optimal real-time scheduling of periodic and sporadic tasks on identical multiprocessors. A number of recent papers have used the notions of fluid scheduling and deadline partitioning to guarantee optimality and improve performance. This article develops a unifying theory with the DP-FAIR scheduling policy and examines how it overcomes problems faced by greedy scheduling algorithms. In addition, we present DP-WRAP, a simple DP-FAIR scheduling algorithm which serves as a least common ancestor to other recent algorithms. The DP-FAIR scheduling policy is extended to address the problem of scheduling sporadic task sets with arbitrary deadlines.

Algorithmic-based user incentives ensure the trustworthiness of evaluations of Wikipedia entries and Google Maps business information.

In content-driven reputation systems for collaborative content, users gain or lose reputation according to how their contributions fare: authors of long-lived contributions gain reputation, while authors of reverted contributions lose reputation. Existing content-driven systems are prone to Sybil attacks, in which multiple identities, controlled by the same person, perform coordinated actions to increase their reputation. We show that content-driven reputation systems can be made resistent to such attacks by taking advantage of the fact that the reputation increments and decrements depend on content modifications, which are visible to all.We present an algorithm for content-driven reputation that prevents a set of identities from increasing their maximum reputation without doing any useful work. Here, work is considered useful if it causes content to evolve in a direction that is consistent with the actions of high-reputation users. We argue that the content modifications that require no effort, such as the insertion or deletion of arbitrary text, are invariably non-useful. We prove a truthfullness result for the resulting system, stating that users who wish to perform a contribution do not gain by employing complex contribution schemes, compared to simply performing the contribution at once. In particular, splitting the contribution in multiple portions, or employing the coordinated actions of multiple identities, do not yield additional reputation. Taken together, these results indicate that content-driven systems can be made robust with respect to Sybil attacks.

Abstract. The emergence of high-performance open-source storage systems is allowing application and middleware developers to consider nonstandard storage system interfaces. In contrast to the practice of virtually always designing for file-like byte-stream interfaces, co-designed domainspecific storage system interfaces are becoming increasingly common. However, in order for developers to evolve interfaces in high-availability storage systems, services are needed for in-vivo interface evolution that allows the development of interfaces in the context of a live system. Current clustered storage systems that provide interface customizability expose primitive services for managing ad-hoc interfaces. For maximum utility, the ability to create, evolve, and deploy dynamic storage interfaces is needed. However, in large-scale clusters, dynamic interface instantiation will require system-level support that ensures interface version consistency among storage nodes and client applications. We propose that storage systems should provide services that fully manage the life-cycle of dynamic interfaces that are aligned with the common branchand-merge form of software maintenance, including isolated development workspaces that can be combined into existing production views of the system.

At CloudFlare [1, 2], we are about a year into our public release. Over the last six months we've seen exponential growth. Cloud-Flare provides a content delivery network currently serving over ten billion page views/month to over 200 million unique visitors. During July 2011 approximately ten percent of all people on the Internet visited a CloudFlare powered site at least once. Figure 1 shows monthly page views served by CloudFlare over the past year.We run a highly customized software stack on a limited number of powerful physical servers deployed in twelve data centers on three continents. The upshot of all of this is that we've been forced to rapidly code, and re-code, to take full advantage of 24 plus cores per machine.This experience report is a very brief survey of the programming models and debugging methodology CloudFlare uses. We first describe two ways in which CloudFlare deals with concurrency issues. We then compare bugs and features in two applications which are representative of the above paradigms.